dissertations on digital forensics

Research Trends, Challenges, and Emerging Topics in Digital Forensics: A Review of Reviews

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An Insightful Analysis of Digital Forensics Effects on Networks and Multimedia Applications

• Review Article
• Published: 31 January 2023
• Volume 4 , article number  186 , ( 2023 )

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• Aishwarya Rajeev   ORCID: orcid.org/0000-0003-1938-3964 1 , 2 &
• P. Raviraj 3  

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Humans have benefited greatly from technology, which has helped to raise standards of living and make important discoveries. But there are a lot of hazards associated with using it. The prevalence of digital video through mobile smartphone applications like WhatsApp and YouTube as well as web-based multimedia platforms are likewise gaining in importance as crucial. But there are also global security issues that are arising. These difficulties could cause significant issues, especially in cases where multimedia is a crucial factor in criminal decision-making, such as in child pornography and movie piracy. Consequently, copyright protection and video authentication are required in order to strengthen the reliability of using digital video in daily life. A tampered film may contain the relevant evidence in a legal dispute to convict someone of a violation or clear a guilty party of wrongdoing. Hence, to develop it is crucial to have reliable forensic techniques that would enhance the justice administration systems and enable them to reach just verdicts. This article discusses numerous forensic analysis fields, including network forensics, audio forensics, and video forensics. In this study, many algorithms such as Random Forest, Multilayer Perceptron (MLP), and Convolutional Recurrent Neural Networks (CRNN) are used for implementing different types of forensic analysis. Also, image fusion is used which can provide more information than a single image and extract features from the original images. This study came to the conclusion that the random forest provides the finest results for network forensic analysis with an accuracy of 98.02 percent. A lot of work has been done during the past years, through an analysis of current methods and machine learning strategies in the field of video source authentication and the study aims to provide a thorough summary of that work.

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Wen CY, Chen JK. Multi-resolution image fusion technique and its application to forensic science. Forensic Sci Int. 2004;140:217–32.

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Ali Z, Imran M, Alsulaiman M. An automatic digital audio authentication/forensics system. IEEE Access. 2017. https://doi.org/10.1109/ACCESS.2017.2672681 .

Gangwar A, Fidalgo E, Alegre E, Gonzáles V. Castro, pornography and child sexual abuse detection in image and video: a comparative evaluation, Proceedings of the 8th International Conference on Imaging for Crime Detection and Prevention, ISBN: 978-1-78561-687-7. 2017, pp. 37–42.

Perez M, Avila S, Moreira D, Moraes D, Testoni V, Valle E, Goldenstein S, Rocha A. Video pornography detection through deep learning techniques and motion information. Neurocomputing. 2017;230:279–93.

Slay J. Towards developing network forensic mechanism for botnet activities in the IoT based on machine learning techniques, Mobile networks and management. In: 9th international conference, MONAMI (2017), Melbourne, Australia, December 13–15; 2017. Proceedings. Springer. Vol. 235, p. 30.

Xiao J, Li S and Xu Q. Video Based Evidence analysis and extraction in digital forensics investigation. IEEE Access; 2019.

Hosler B, Mayer O, Bayar B, Zhao X, Chen C, Shackleford JA, Stamm MC. A video camera model identification system using deep learning and Fusion. In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE; 2019. pp. 8271–8275.

Chhabra GS, Singh VP, Singh M. Cyber forensics framework for big data analytics in IoT environment using machine learning. Multimed Tools Appl. 2020;79:15881–900.

Orozco ALS, Huamán CQ, Álvarez DP, Villalba LJG. A machine learning forensics technique to detect post-processing in digital videos. Future Gener Computer Syst. 2020;111:199–212.

Qamhan MA, Altaheri H, Meftah AH, Muhammad G, Alotaibi YA. Digital audio forensics: microphone and environment classification using deep learning. IEEE Access. 2021. https://doi.org/10.1109/ACCESS.2021.3073786 .

Sachdeva S, Ali A. Machine learning with digital forensics for attack classification in the cloud network environment. Int J Syst Assur Eng Manag. 2022;13(Suppl 1):S156–65.

Abbasi A, Javed AR, Yasin A, Jalil Z, Kryvinska N, Tariq U. A large-scale benchmark dataset for anomaly detection and rare event classification for audio forensics. IEEE Access. 2022. https://doi.org/10.1109/ACCESS.2022.3166602 .

Akbari Y, Al-Maadeed S, Elharrouss O, Khelifi F, Lawgaly A, Bouridane A. Digital forensic analysis for source video identification: a survey. Forensic Sci Int: Digital Investig. 2022;41:301390.

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Akbari Y, Al-Maadeed S, Almaadeed N, Al-ali A, Khelifi F, Lawgaly A, et al. A new forensic video database for source smartphone identification: description and analysis. IEEE Access. 2022. https://doi.org/10.1109/ACCESS.2022.3151406 .

Neale C, Kennedy I, Price B, Yijun Yu, Nuseibh B. The case for zero trust digital forensics. Sci Int: Digit Investig. 2022;40:301352.

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This article is part of the topical collection “Advances in Computational Intelligence for Artificial Intelligence, Machine Learning, Internet of Things and Data Analytics” guest edited by S. Meenakshi Sundaram, Young Lee and Gururaj K S.

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Rajeev, A., Raviraj, P. An Insightful Analysis of Digital Forensics Effects on Networks and Multimedia Applications. SN COMPUT. SCI. 4 , 186 (2023). https://doi.org/10.1007/s42979-022-01599-8

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Chris Sanders

Information Security Analyst, Author, and Instructor

A Cognitive Skills Assessment of Digital Forensic Analysts – My Doctoral Dissertation

• Posted on December 9, 2021 December 9, 2021

In September of this year, I successfully defended my doctoral dissertation, earning the title of Doctor of Education from Baylor University. In this post, I’m sharing the entirety of that dissertation freely to benefit the information security community. I’ll also provide recommendations on relevant sections of the work based on your role. Finally, I’ll talk a bit about the past, present, and future of my research.

I believe this dissertation represents a significant step forward in understanding the cognitive skills that high-performing analysts rely on when conducting security investigations. The findings here help establish analytic doctrine and should yield significant improvements in how analysts are trained when considered thoughtfully by educators. Similarly, analysts who better understand their own cognitive skills stand to increase their metacognitive awareness. This knowledge has the potential to improve analyst performance as well as their ability to communicate with peers and mentor less experienced practitioners. This paper also further establishes the field of human-centric investigation theory research.

Let’s get straight to the point. You can download my complete dissertation paper for free at the link below.

DOWNLOAD: The Analyst Mindset: A Cognitive Task Assessment of Digital Forensic Analysts

Despite significant investment in cyber security, the industry is unable to stem the tide of damaging attacks against computer networks. This unfortunate situation is, in part, because cyber security exists in a state of cognitive crisis defined by tacit knowledge and poorly understood processes. At the heart of the crisis are digital forensic analysts that identify and investigate intrusions. Unfortunately, even skilled analysts in these roles are often unable to explain how they go about the process of finding intruders and assessing their foothold on a network. Without this knowledge, professional and academic educators are unable to build a standardized industry-accepted curriculum for the identification and training of new analysts. While there have been some attempts to inventory the skills, processes, and knowledge required to serve in the digital forensic analyst role, no current efforts provide a thorough, research-backed accounting of the profession with consideration for cognitive skill elements.

This problem of practice study details a cognitive skills assessment of the digital forensic analyst profession by leveraging two Cognitive Task Analysis (CTA) research methods. The Simplified Precursor, Action, Result, Interpretation (PARI) method provided a framework for eliciting procedural skills, and the Critical Decision Method (CDM) supported the discovery of decision-making skills. Using these techniques, interviews conducted with expert analyst practitioners revealed four unique procedural skill categories, characteristics of two significant facets of analyst decision making, and numerous subcategory elements that describe additional dimensions of expert analyst performance. The results converged on a model of diagnostic inquiry that represents the relationships between how analysts formed investigative questions, interpreted evidence, assessed the disposition of events, and chose their next investigative actions. These findings establish explicit knowledge that provides a foundational understanding of how skilled analysts perform investigations. They also lay new groundwork for cyber security’s emergence from its cognitive crisis, with implications for educators and practitioners alike.

Reading Guide

If you’re reading this as an information security practitioner, I recommend reading Chapter 1 (Introduction) for an overview, Chapter 2 (Literature Review) for background information, and then focusing on Chapter 4 (Findings) and the appendices referenced in it. Keep in mind that it is a research document, not a teaching document. It describes the process and results of my research on analyst cognitive processes and is narrowly scoped to the findings that I uncovered. These findings have significant value to analysts and those who support them but are not necessarily meant to be handed to an entry-level analyst on their own. If you want to learn to be an analyst, I recommend my Investigation Theory class, where much of my research (including this dissertation) manifests with learning in mind. It is here that these concepts are scaffolded by other relevant knowledge, paired with examples and demonstrations, and tied to specific learning objectives so that analysts can wield them properly.

If you’re reading this as an educator, then I recommend reading Chapter 1 (Introduction), Chapter 4 (Findings), and Chapter 5 (Distribution of Findings) . My primary goal with this research was to identify analyst cognitive skills so that we may better teach those skills to others. I expect that this work will find a home in many community college and university courses that have investigative components. If you do end up building curriculum components around these concepts, I’d love to hear about your approach .

If you’re reading this as an academic researcher, then I recommend reading the entire document so that you may understand my methods as well as the results I uncovered. I put extra effort into describing my cognitive task analysis strategy. My experience as a 15+ year practitioner before moving into the academic research space is atypical but allowed me to conduct this research through a unique lens that would not be possible by researchers lacking professional experience. I tried my best to elaborate on my research methods to highlight how I deployed my expertise to design the study and conduct data collection and analysis. I hope this work will help bring the academic and practitioner communities closer together.

My Research and How I Got Here

I struggled tremendously when I first began my analyst career. I could not understand how investigators took inputs and used them to pivot between various data sources and find evidence of compromise. I distinctly remember sitting in a state of paralysis, starting at a blank search bar, not knowing what to do next. I didn’t have access to many highly skilled people, and those who were could not effectively explain how they connected the dots. I was told to watch how they did their work, play around in the data, and I would eventually figure it out. I eventually did figure it out, but that path was much longer and more frustrating than it should have been. Worse yet, I was continually told that good analysts were born with a particular set of traits, and without them, someone’s chance of doing the job well was limited.

Over time, I recognized that information security is in a state of cognitive crisis. So much of the knowledge we rely on is tacit and unavailable to those seeking the practice this craft. That negatively affects everyone attempting to enter the field, but it affects those who are already marginalized even more. As my interests turned from computers to the humans using them, I felt a desire to make these tacit processes explicit, which led me on a long and challenging journey that included researching and writing the dissertation you see attached to this post. Along this path, I learned that digital forensic investigations are not art, although there is room for creativity to guide an analyst’s path. I also learned that digital forensic investigations are not science, but we can use scientific processes to study how humans can better bridge the gap between perception and reality. Digital forensic analysis is engineering. With the right people in the room asking the right questions, nothing a computer does cannot be explained. That means that the only thing standing between me and knowing what happened is my own ability to understand evidence and behavior. These realizations empowered me, dramatically changed my career trajectory, and are why you’re reading this.

Why an Education Doctorate?

I once read that everything exciting happens on the fringes of where two things meet; the middle is boring because everything is the same. While I’m not sure I agree with that idea completely, I know that most of my professional curiosity is stimulated at the borders shared by cyber security, cognitive psychology, and education. Every investigation involves a human sitting at a console looking at data. Ultimately, those humans have the most to say about whether a compromise is fully discovered and contained.

Paul L. Kirk was a biochemist, criminologist, and early pioneer of forensic science. He was also a successor of Edmund Locard, who is considered by many to be the father of modern forensic science. In 1953, Kirk invoked Locard’s Exchange Principle when he wrote a now-famous quote describing the relationship between an investigator, a criminal, and the evidence they leave behind. I’ve taken the liberty of updating his quote to make it more relevant to modern digital forensics.

Wherever they pivot, whatever they access, whatever they leave behind, even unconsciously, will serve as a silent witness against them. Not only their authentications or their executions, but the packets they transmit, the files they change, the tool marks they leave, and the data they upload or download. All of these and more bear mute witness against them. This is evidence that does not forget. It is not confused by the excitement of the moment. It is not absent because human witnesses are. It is factual evidence. Digital evidence cannot perjure itself and it cannot be wholly absent. Only human failure to find, study, and understand evidence can diminish its value. Chris Sanders, Revised from Paul L. Kirk (1953)

I find the last line of that quote (unchanged from its original version) the most impactful. Ultimately, many of the issues cyber security faces in its cognitive crisis are education problems. We must better understand how and why experts do the things they do to teach them to other people and refine them; something that we’re currently failing at.

Therefore, cyber security is the medium for my work, cognitive psychology provides the framework for understanding how analysts perform, and my findings are expressed through education. My choice to pursue a doctorate in education was primarily focused on the outputs I hope to achieve from my research; a more clear establishment of the human-centric investigation theory research field, a more formal digital forensics analytic doctrine, and the methods to help people learn that doctrine.

What’s next?

While a doctorate is a terminal degree, the document encapsulating it is only the beginning. I plan to continue my research focused on different facets of how analysts perform investigations and strategies for teaching investigation concepts. As a matter of fact, I have ongoing research projects as you read this post.

As part of this continued work, I’m seeking research partners who might want to work or collaborate. This includes:

• Universities who may be interested in providing graduate students to assist in research projects. These students will be compensated for their time and can come from a variety of subject areas like psychology, sociology, or education. They do not have to posses prior cyber security experience, but should be interested in the field and have some exposure to quantitative and qualitative research techniques. These opportunities are remote/online under the Applied Network Defense research umbrella.
• Businesses that wish to provide access to analysts for research subjects. A unique challenge of conducting analyst-centric research is finding enough analysts to serve as research subjects. This is particularly the case when I need to conduct research focused on several analysts within a single security operations center. If your organization is interested in providing analysts for these studies, please reach out. Depending on the scope of the research, there may be some costs associated with participation. However, as part of participating, you’ll receive free and discounted training courses along with priority access to research findings, as well as consulting from me on how to leverage the results meaningfully in your security team.

Please contact me directly if you are interested in either of these opportunities.

My Acknowledgments

While my acknowledgments are included in the dissertation document itself, I thought it important to also include them here just like I do with in all the blog posts that have accompanied the release of my books.

I would like to thank the people who helped make this document possible and contributed to the positive step forward it represents. First and foremost, thank you to my wife Ellen, who I kept awake countless nights by storming into the bedroom rambling on and on about the ideas running through my head following late classes.

Nobody becomes a scholar alone, and I was fortunate to have several amazing people on this journey with me. I want to extend my gratitude to my doctoral colleagues who made this whole experience more enjoyable. I also want to thank my instructors at Baylor who shepherded me along this scholarly experience, with special thanks to my advisor, Dr. Sandi Cooper. I don’t fit the mold of a typical education student, and I appreciate all of you opening up your mind to learn from me as I did from you.

I want to pay special tribute to my students, whose success helps motivate me, including anyone who has ever taken one of my classes, read one of my books, or sat in on one of my conference presentations. Additionally, I want to thank my colleagues that served as sounding boards and provided feedback on my ideas.

This whole project started over a decade ago when I was a struggling young analyst trying to learn the craft. Someone told me that you are either born with the skills needed to do this job, or you are not. I thought that was nonsense, and I have spent the rest of my career gathering the knowledge and data to prove it. The document you are about to read is a step along that path. I don’t remember the name of the person who told me that, but I want to thank them too.

Download and Citation

You can download my complete dissertation paper for free at this link .

The paper will be available in the Baylor and ProQuest databases on December 19th, 2021/

You may cite this work as:

Sanders, C. (2021). The analyst mindset: A cognitive task assessment of digital forensic analysts [Doctoral dissertation, Baylor University]. https://chrissanders.org

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Data privacy preservation in digital forensics investigation

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Ayush Kumar Verma , Krishnan Ramanathan; Data privacy preservation in digital forensics investigation. AIP Conf. Proc. 3 October 2022; 2519 (1): 030051. https://doi.org/10.1063/5.0109813

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As we know, in a digital forensic investigation, the investigators extract evidence from different types of digital media. However, the extraction method itself unlocks the way for digital forensic investigators to encroach the privacy of the individual. To detect fraud, an investigator collects and analyzes the digital evidence connected to the fraud that has taken place and presents it in court to prove convict. There are no legal or technical structures in place that can keep a check on the investigation procedures to prevent this breach of privacy. Privacy of personal data of a user is stated in the United Nations Declaration of Human Rights. In this ever-changing world, the increasing use of computing devices creates vast volumes of personal data, and correspondingly, in digital investigation, there is an increased presumption of accountability and protection for the rights of a user governing data privacy. So, in this research study, we have tried to respond to this concern by analyzing the perceptions about data privacy preservation and issues related to digital forensics investigation from three perspectives, i.e., user, forensic investigator, and technology, and put forward a framework that respects user privacy as well as ensures a forensically sound digital investigation.

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Forensics Digest

All about Forensics

Recent Dissertation Topics in Forensic Science

This article serves as a compass, guiding readers through a diverse array of recent dissertation topics that encapsulate the multifaceted nature of forensic research. From digital forensics to forensic psychology, the chosen dissertation topics reflect the evolving challenges and advancements in solving complex legal puzzles.

Forensic DNA Analysis:

• “Next-Generation Sequencing (NGS) in Forensic DNA Profiling: Opportunities and Challenges”
• “The Impact of DNA Transfer and Secondary DNA Transfer in Forensic Investigations”
• “Ethical Implications of DNA Phenotyping: A Critical Analysis”

Digital Forensics:

• “Artificial Intelligence in Digital Forensic Analysis: A Comprehensive Review”
• “Cloud Forensics: Investigating Digital Crimes in Cloud Computing Environments”
• “Deepfake Detection Techniques: Safeguarding Digital Evidence Integrity”

Forensic Anthropology:

• “Facial Approximation in Forensic Anthropology: Integrating 3D Modeling Techniques”
• “The Role of Forensic Anthropologists in Mass Graves Investigations”
• “Advancements in Skeletal Trauma Analysis for Forensic Purposes”

Forensic Toxicology:

• “Metabolomics in Forensic Toxicology: Profiling Endogenous and Exogenous Compounds”
• “Designer Drugs: Analytical Approaches for the Detection of Novel Psychoactive Substances”
• “Forensic Challenges in Analyzing Postmortem Fluids for Toxicological Investigations”

Forensic Psychology:

• “The Impact of Jury Bias on Forensic Psychologists’ Testimonies: A Case Study Analysis”
• “Virtual Reality Applications in Forensic Psychology Training: Enhancing Investigative Skills”
• “Exploring the Ethical Dilemmas in Forensic Psychological Assessments”

Forensic Pathology:

• “Cardiac Biomarkers in Forensic Pathology: Exploring their Role in Cause of Death Determination”
• “The Use of Postmortem Imaging in Forensic Pathology: A Comparative Analysis”
• “Forensic Aspects of Pediatric Traumatic Brain Injuries: Patterns and Challenges”

Forensic Odontology:

• “Age Estimation in Subadults: Integrating Dental and Skeletal Methods in Forensic Odontology”
• “Digital Methods in Bite Mark Analysis: Enhancing Accuracy and Reliability”
• “Role of Dental Records in Disaster Victim Identification: A Global Perspective”

Forensic Entomology:

• “Forensic Entomogenomics: Unraveling New Dimensions in Time of Death Estimation”
• “Environmental Factors Influencing Insect Colonization on Decomposing Remains: A Forensic Study”
• “The Use of Entomotoxicology in Forensic Investigations: Current Trends and Applications”

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January 7, 2024 at 2:22 am

thank you for this post. I needed to submit a topic for my dissertation on Monday and you guys saved me big time

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Dissertations / Theses on the topic 'Digital Forensic investigations'

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Marziale, Lodovico. "Advanced Techniques for Improving the Efficacy of Digital Forensics Investigations." ScholarWorks@UNO, 2009. http://scholarworks.uno.edu/td/1027.

De, Souza Pedro. "A Chain of findings for digital investigations." Diss., University of Pretoria, 2013. http://hdl.handle.net/2263/40842.

Hansen, Tone. "A Digital Tool to Improve the Efficiency of IT Forensic Investigations." Thesis, Högskolan i Halmstad, Akademin för informationsteknologi, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-40232.

Patterson, Farrah M. "The implications of virtual environments in digital forensic investigations." Master's thesis, University of Central Florida, 2011. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/4819.

Liljekvist, Erika, and Oscar Hedlund. "Uncovering Signal : Simplifying Forensic Investigations of the Signal Application." Thesis, Högskolan i Halmstad, Akademin för informationsteknologi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-44835.

Hargreaves, C. J. "Assessing the Reliability of Digital Evidence from Live Investigations Involving Encryption." Thesis, Department of Informatics and Sensors, 2009. http://hdl.handle.net/1826/4007.

Hargreaves, Christopher James. "Assessing the reliability of digital evidence from live investigations involving encryption." Thesis, Cranfield University, 2009. http://dspace.lib.cranfield.ac.uk/handle/1826/4007.

Roussel, Bruno. "Les investigations numériques en procédure pénale." Thesis, Bordeaux, 2020. http://www.theses.fr/2020BORD0075.

Montasari, Reza. "The Comprehensive Digital Forensic Investigation Process Model (CDFIPM) for digital forensic practice." Thesis, University of Derby, 2016. http://hdl.handle.net/10545/620799.

Sanyamahwe, Tendai. "Digital forensic model for computer networks." Thesis, University of Fort Hare, 2011. http://hdl.handle.net/10353/d1000968.

Etow, Tambue Ramine. "IMPACT OF ANTI-FORENSICS TECHNIQUES ON DIGITAL FORENSICS INVESTIGATION." Thesis, Linnéuniversitetet, Institutionen för datavetenskap och medieteknik (DM), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-97116.

Alqahtany, Saad. "A forensically-enabled IaaS cloud computing architecture." Thesis, University of Plymouth, 2017. http://hdl.handle.net/10026.1/9508.

Sonnekus, Michael Hendrik. "A comparison of open source and proprietary digital forensic software." Thesis, Rhodes University, 2015. http://hdl.handle.net/10962/d1017939.

Van, Ramesdonk Paul. "Continued forensic development - investigation into current trends and proposed model for digital forensic practitioners." Master's thesis, University of Cape Town, 2016. http://hdl.handle.net/11427/20707.

Rule, Samantha Elizabeth. "A Framework for using Open Source intelligence as a Digital Forensic Investigative tool." Thesis, Rhodes University, 2015. http://hdl.handle.net/10962/d1017937.

Wang, Mengmeng, and 王萌萌. "Temporal analysis on HFS+ and across file systems in digital forensic investigation." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2013. http://hub.hku.hk/bib/B50900122.

Barbosa, Akio Nogueira. "Método para ranqueamento e triagem de computadores aplicado à perícia de informática." Universidade de São Paulo, 2015. http://www.teses.usp.br/teses/disponiveis/3/3141/tde-14062016-081553/.

Al, Mutawa Noora Ahmad Khurshid. "Integrating behavioural analysis within the digital forensics investigation process." Thesis, University of Central Lancashire, 2018. http://clok.uclan.ac.uk/25412/.

LeRoi, Jack. "A forensic investigation of the electrical properties of digital audio recording." Thesis, University of Colorado at Denver, 2014. http://pqdtopen.proquest.com/#viewpdf?dispub=1556863.

In media forensics, the devices; e.g. computers, smart phones, still/video cameras, audio recorders, and software; e.g. video, audio, and graphics editors, file and disk utilities, mathematical computation applications, are, for the most part, black boxes. The design specifications are usually proprietary and the operating specifications may be incomplete, inaccurate, or unavailable. This makes it difficult to validate the technology, but using it without validation could discredit a practitioner's findings or testimony. The alternative is to test the device or program to determine relevant characteristics of its performance.

An important and common device in media forensics is the portable digital audio recorder used to record surveillance and interviews. This type can also be used to record the alternating current (AC) waveform from the mains power. While small variations in the AC frequency (ENF) can be forensically important, distortion in the recording can affect its value in adjudication or investigation. A method is presented to evaluate aspects of a recorder's operation that can cause distortion. Specifically, the method measures the noise generated by the recorder's electronics in its input and amplifier circuits. The method includes a procedure to isolate the recorder from environmental sources of noise. The method analyzes the broadband noise floor produced by the range of recording conditions and recorder settings. It also analyzes the noise amplitude for the harmonics for the mains frequency.

Ademu, Inikpi. "A comprehensive digital forensics investigation model and guidelines for establishing admissible digital evidence." Thesis, University of East London, 2013. http://roar.uel.ac.uk/3992/.

Homem, Irvin. "Towards Automation in Digital Investigations : Seeking Efficiency in Digital Forensics in Mobile and Cloud Environments." Licentiate thesis, Stockholms universitet, Institutionen för data- och systemvetenskap, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-130742.

Al-Morjan, Abdulrazaq Abdulaziz. "An investigation into a digital forensic model to distinguish between 'insider' and 'outsider'." Thesis, De Montfort University, 2010. http://hdl.handle.net/2086/4402.

Nikooazm, Elina. "Validation des logiciels d'expertise judiciaire de preuves informatiques." Thesis, Paris 2, 2015. http://www.theses.fr/2015PA020021.

Mankantshu, Mninawe Albert. "Investigating the factors that influence digital forensic readiness in a South African organisation." Master's thesis, University of Cape Town, 2014. http://hdl.handle.net/11427/8504.

AlMarri, Saeed. "A structured approach to malware detection and analysis in digital forensics investigation." Thesis, University of Bedfordshire, 2017. http://hdl.handle.net/10547/622529.

Hewling, Moniphia Orlease. "Digital forensics : an integrated approach for the investigation of cyber/computer related crimes." Thesis, University of Bedfordshire, 2013. http://hdl.handle.net/10547/326231.

Waltereit, Marian [Verfasser], and Torben [Akademischer Betreuer] Weis. "On the Digital Forensic Investigation of Hit-And-Run Accidents / Marian Waltereit ; Betreuer: Torben Weis." Duisburg, 2021. http://d-nb.info/1236539818/34.

Nordin, Anton, and Felix Liffner. "Forensiska Artefakter hos Mobila Applikationer : Utvinning och Analys av Applikationen Snapchat." Thesis, Högskolan i Halmstad, Akademin för informationsteknologi, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-40207.

Federici, Corrado <1965&gt. "The twofold role of Cloud Computing in Digital Forensics: target of investigations and helping hand to evidence analysis." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2014. http://amsdottorato.unibo.it/6694/.

Jones, Eric Douglas. "Forensic Investigation of Stamped Markings Using a Large-Chamber Scanning Electron Microscope and Computer Analysis for Depth Determination." TopSCHOLAR®, 2013. http://digitalcommons.wku.edu/theses/1237.

Homem, Irvin. "LEIA: The Live Evidence Information Aggregator : A Scalable Distributed Hypervisor‐based Peer‐2‐Peer Aggregator of Information for Cyber‐Law Enforcement I." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-177902.

Breitinger, Frank [Verfasser], Stefan [Akademischer Betreuer] Katzenbeisser, Harald [Akademischer Betreuer] Baier, and Felix [Akademischer Betreuer] Freiling. "On the utility of bytewise approximate matching in computer science with a special focus on digital forensics investigations / Frank Breitinger. Betreuer: Stefan Katzenbeisser ; Harald Baier ; Felix Freiling." Darmstadt : Universitäts- und Landesbibliothek Darmstadt, 2014. http://d-nb.info/1110901852/34.

Bouchaud, François. "Analyse forensique des écosystèmes intelligents communicants de l'internet des objets." Thesis, Lille, 2021. http://www.theses.fr/2021LILUI014.

Lalanne, Vincent. "Gestion des risques appliquée aux systèmes d’information distribués." Thesis, Pau, 2013. http://www.theses.fr/2013PAUU3052/document.

Arthur, Kweku Kwakye. "Considerations towards the development of a forensic evidence management system." Diss., 2010. http://hdl.handle.net/2263/26567.

Alharbi, Soltan Abed. "Proactive System for Digital Forensic Investigation." Thesis, 2014. http://hdl.handle.net/1828/5237.

Grobler, Cornelia Petronella. "DFMF : a digital forensic management framework." Thesis, 2012. http://hdl.handle.net/10210/6365.

Adedayo, Oluwasola Mary. "Reconstruction in Database Forensics." Thesis, 2015. http://hdl.handle.net/2263/43777.

Fei, B. K. L. (Bennie Kar Leung). "Data visualisation in digital forensics." Diss., 2007. http://hdl.handle.net/2263/22996.

Delgado, Manuel. "Combater o crime económico com armas digitais: o papel do open-source." Master's thesis, 2012. http://hdl.handle.net/10071/8063.

Valjarevic, Aleksandar. "A comprehensive and harmonised digital forensic investigation process model." Thesis, 2015. http://hdl.handle.net/2263/50812.

Pooe, El Antonio. "Developing a multidisciplinary digital forensic readiness model for evidentiary data handling." Thesis, 2018. http://hdl.handle.net/10500/25316.

張緹柔. "A Study on Investigation and Digital Forensic for Wireless Cyber Crime." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/k5896p.

Ndara, Vuyani. "Computer seizure as technique in forensic investigation." Diss., 2014. http://hdl.handle.net/10500/13277.

Bernardo, Bruno Miguel Vital. "Toolbox application to support and enhance the mobile device forensics investigation process - breaking through the techniques available." Master's thesis, 2021. http://hdl.handle.net/10362/113177.

Joshi, Abhishek Shriram. "Image Processing and Super Resolution Methods for a Linear 3D Range Image Scanning Device for Forensic Imaging." 2013. http://hdl.handle.net/1805/3414.

Breitinger, Frank. "On the utility of bytewise approximate matching in computer science with a special focus on digital forensics investigations." Phd thesis, 2014. https://tuprints.ulb.tu-darmstadt.de/4055/1/20140717_Dissertation_Breitinger_final.pdf.

Lochner, Hendrik Thomas. "Kartering van selfoontegnologie." Diss., 2007. http://hdl.handle.net/10500/554.

Home > Eberly College of Arts and Sciences > Departments > Forensic and Investigative Science > Forensic and Investigative Science Graduate Theses and Dissertations

Forensic and Investigative Science Graduate Theses and Dissertations

Theses/dissertations from 2023 2023.

Strengthening the Interpretation of Glass and Paint Evidence Through the Study of Random Frequency of Occurrence and Analytical Information , Lauryn C. Alexander

Quantifying Variation in High-Quality Footwear Replicate Impressions , Samantha K. Brady

Development of a Mass Transfer Correction Factor in a Thermodynamic Model to Explain the Weathering Patterns of Ignitable Liquids on Household Substrates at Elevated Temperatures , Max T. Denn

The Influence of Instrumental Sources of Variance on Mass Spectral Comparison Algorithms , Isabel Cristina Galvez Valencia

Finite Element Modeling and Analysis of Breech Face Impressions , James A. Hamilton

An Assessment of the Forensic Aspects of Genetic Genealogy , Sarah Hester

Footwear Image Quality Classification: Using Subjective Assessments and Objective Image Metrics to Predict Impression Quality , En-Tni Lin

Interpretation of the Tandem Mass Spectrum of the Novel Psychoactive Substance 5F-APP-PINACA, PX-2 , Christopher S. Poulos

Computerized Trajectory Analysis for Firearms Examiners , Baillie E. Poulton

Enhancing the forensic comparison process of common trace materials through the development of practical and systematic methods , Meghan Nicole Prusinowski

Evaluating the Degradation Relationship Between Latent Print Impressions and Touch DNA Under Varying Environmental Conditions , Katrina M. Rupert B.S.

Estimate of the Random Match Frequency of Acquired Characteristics in a Forensic Footwear Database , Alyssa N. Smale

Analysis of ‘touch’ DNA recovered from metal substrates: an investigation into cfDNA-metal interactions and the efficacy of different collection techniques on DNA yield , Jessica E. Thornton

Analysis of the Effect of Rate of Fire on the Reproducibility of Breech Face Impressions , Kayla Ann Trimble

Assessment of Acquisition, Retention, and Evolution of Randomly Acquired Characteristics with Wear , Nathaniel Weston

Evaluation of emerging screening technologies for the on-site detection and identification of methamphetamine and its precursors in simulated clandestine lab operations , Alexis Nicole Wilcox

Theses/Dissertations from 2022 2022

Development of an Expert Algorithm for Substance Identification (EASI) to Discriminate between Spectrally Similar Fentanyl Analogs in Mass Spectrometry , Alexandra Adeoye

Evaluating the Validity and Reliability of Textile and Paper Fracture Characteristics in Forensic Comparative Analysis , Zachary Bailey Andrews

mtDNA Heteroplasmy in Hair Shafts versus Buccal Swabs for Forensic Applications , Sara R. Bodnar

Integration of Spectroscopic and Mass Spectrometric Tools for the Analysis of Novel Psychoactive Substances in Forensic and Toxicology Applications , Travon Cooman

Electrochemical and mass spectrometry methods for identification of gunshot residues (GSR) in forensic investigations , Kourtney A. Dalzell

Assessment of QuEChERS extraction protocol for the LC-MS/MS detection of emerging fentanyl analogs in biological specimens for clinical and forensic purposes , Kylea M. Morris

Analysis of Forensically Relevant Evidence Using Electrochemistry, Spectroscopy, and Mass Spectrometry Tools , Colby Edward Ott

Identifying and Minimizing Sources of Variability Within Modern Spectroscopic Techniques for the Forensic Analysis of Glass , Oriana Christy Ovide

Analyzing the viability of direct PCR for use in conjunction with cyanoacrylate enhanced fingerprints , Coral M. Smith

Expanding the Capabilities of Firearm Investigations: Novel Sampling and Analytical Methods for Gunshot Residue Evidence , Courtney Helen Vander Pyl

Theses/Dissertations from 2021 2021

Quantitation of Fentanyl and Metabolites from Blow Fly Tissue and Development Effects of Fentanyl on Lucilia sericata , Joseph Allen Cox

Characterization of Modern Ammunition and Background Profiles: A Novel Approach and Probabilistic Interpretation of Inorganic Gunshot Residue , Korina Layli Menking-Hoggatt

Theses/Dissertations from 2020 2020

Prevalence of Pores in Latent Fingerprints , Rachel E. Ball

Statistical Assessment of the Significance of Fracture Fits in Trace Evidence , Evie K. Brooks

American Population Study of Pigmentation Based Genotype Interpretation for Phenotypic Determination of Hair and Eye Color using HIrisPlex , Emma Leigh Combs

Structural Characterization of Emerging Synthetic Drugs , Jay Tyler Davidson

Validation of Fast Spectrochemical Screening Methods for the Identification of Counterfeit Pharmaceutical Packaging , Emily Ann Haase

Evaluating the Use of the M-Vac® Wet Vacuum System to Recover DNA from Cotton Fabric , Phillip Reilly Irion

Evaluating the Accuracy of Firearm Examiner Conclusions using Cartridge Case Reproductions , Eric Freeman Law

Evaluation of the Performance of Probabilistic Genotyping Software on Complex Mixture Samples , Kristen Newland

Statistical Evaluation of Randomly Acquired Characteristics on Outsoles with Implications Regarding Chance Co-Occurrence and Spatial Randomness , Nicole Richetelli

Spatio-Temporal Analysis of Crime Incidents for Forensic Investigation , Jamie Spencer Spaulding

The Effects of Household Substrates on the Evaporation of Ignitable Liquids at Temperatures up to 210℃ , Caitlyn Wensel

Theses/Dissertations from 2019 2019

Immunomagnetic Beads Coupled with Anti-PH-20 Antibodies to Isolate Sperm from DNA Mixtures for Sexual Assault Kit Application , Kayla Becks

In vitro metabolism of the synthetic cannabinoids PX-1, PX-2, PX-3 and a comparison of their clearance rates in human liver microsomes , Travon Cooman

The Effects Hot Water Kill Time has on DNA Degradation and STR Profiling from Lucilia sericata (Diptera: Calliphoridae) Crop Contents , Nicholas Alexander Haas

Identification of Burnt Smokeless Gunpowders Through Physical Characteristics , Cameron Taylor Hartwig

Modeling Movement of Criminals through Burglary Scenes , Veronica L. Herrmann

The Evaluation of the RapidHITTM 200 on Degraded Biological Samples , Alice Kim

Screening Sexual Assault Evidence with Low Concentrations of Male DNA Utilizing the RapidHIT 200 and ParaDNA Intelligence Test , Taylor L. Koepfler

Electrochemical detection of fentanyl using screen-printed carbon electrodes with confirmatory analysis of fentanyl and its analogs in oral fluid using liquid chromatography-tandem mass spectrometry , Colby E. Ott

Assessing the reliability of physical end matching and chemical comparison of pressure sensitive tapes , Meghan Nicole Prusinowski

Chemical Analysis of Firearm Discharge Residues Using Laser Induced Breakdown Spectroscopy , Courtney Helen Vander Pyl

Theses/Dissertations from 2018 2018

Understanding the Novice Decision-Making Process in Forensic Footwear Examinations: Accuracy and Decision Rules , Madonna A. Nobel

Inclusion of 9 mm Firearm Type Using Quantitative Class Characteristics , Young Wang

Theses/Dissertations from 2017 2017

The Analysis of the Fatty Acid Content of Fingerprint Residues Using Gas ChromatographyMass Spectrometry , Ashley R. Cochran

The Analysis of 2,5-Dimethoxy-N-(N-methoxybenzyl) phenethylamine (NBOMe) Isomers Using Traditional and Fast Gas Chromatography-Mass Spectrometry , J. Tyler Davidson

Effect of Chamber Pressure on the Quality of Breech Face and Firing Pin Impressions , James A. Hamilton

AFIS Based Likelihood Ratios for Latent Fingerprint Comparisons , Shreya Sateesh Kamath

The Assessment of Fingerprint Quality for a More Effective Match Score in Minutiae-Based Matching Performers , Alyshia Meyers

Evidence Utility in Forensic Intelligence Models , Jamie S. Spaulding

Theses/Dissertations from 2016 2016

Determining the Angle of Impact from the Analysis of Bullets Following Perforation with Glass , Roger L. Jeffreys II

Determining the Number of Test Fires Needed to Represent the Variability Present Within a Firearm , Eric Law

The evaluation and interpretation of controls used in three commercially available quantification kits for forensic DNA analysis , Stephanie R. Schottke

Theses/Dissertations from 2015 2015

How Well Are Your Police Doing?: The Relationship Between Fear of Crime and Perceptions of the Police , Erin Bixler

Evaluation of the Effectiveness of Recovery Methods of Trace Evidence for Pollen Particles , Christie Cyktor

Estimation of changes in breech face and firing pin marks over consecutive discharges and its impact on 2D correlation systems , Justin Kirk

You Can't Fight City Hall: Organization and Success in West Virginia , Theodore Malone

Development and Evaluation of an Objective Method for Forensic Examination of Human Head Hairs Using Texture-Based Image Analysis , Allyce S. McWhorter

Social Structure and Clearance Rates: The Effect of Neighborhood Characteristics on Aggravated Assault Case Outcome , Brad Silberzahn

Digital Image Transformations and Image Stacking of Latent Prints Processed Using Multiple Physical and Chemical Techniques , Danielle Tague

"Man of the House": A Turning Point That Leads to Criminal Behavior? , Delia A. Trickett

Theses/Dissertations from 2014 2014

Quantifying the Limits of Fingerprint Variability , Michael Fagert

A Survey on the Microscopical and Chemical Analysis of Synthetic Wig Fibers , Theresa A. Joslin

Theses/Dissertations from 2013 2013

Reproducibility of Retention Indices Examining Column Type , Amanda M. Cadau

Swedish Legislation Targeting Trafficking for Sexual Exploitation and the Possibilities for Implementation in Estonia , Jennifer E. Lyall

Evaluating the Intra-variability and Inter-variability of Fibers in Cotton T-shirts using Microspectrophotometry , Brianne Miller

Theses/Dissertations from 2012 2012

Evaluation of the Use of Raman Spectroscopic Techniques in Ink Analyses , Patricia T. Elswick

Uncertainty Considerations with the GRIM , Eric L. Everts

Pre and Post Blast Chemical Comparison of the Intra- and Inter-Variability of Metal Pipes Commonly Used in Pipe Bombs , Mandi Hellested

Recovery of DNA Profiles from Fingerprints on Paper after the Application of Ninhydrin or DFO Given Certain Time Periods , Marco Colin Lovejoy

Evaluating the Ability of Different Weak Acids When Combined with Hydrogen Peroxide to Develop Latent Fingerprints on Post-Fired Cartridge Cases , Casey Nicholas Oleksa

Theses/Dissertations from 2010 2010

Preliminary Study on the Reliability of AFIX Tracker for Lip Print Examination , Kelli E. Edmiston

Transfer and Persistence of Gunshot Residue Particles , DeAnna M. Wallace

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Digital forensics assists in the analysis, inspection, identification, and preservation of evidence (digital) collected on a wide variety of devices. It’s the professional domain of studying, identifying, conserving, protecting, extracting, documenting, and creating digital information in different ways. The goal is to evaluate the information as part of the civil or criminal investigation once it has been turned into contextual information using appropriate kinds of rationale . In digital forensics, the tasks below must be completed.

• Analysis of text, images and videos
• Cracking passwords
• Clustering files
• Searching data
• Executable analysis

Through this article, we will provide you with expert analysis on various digital forensics project topics and doing research on them. We claim to be one of the best project supporters in the world mainly due to the following reasons.

As we are in the field of guiding research projects in topics related to digital forensics for more than 15 years we have gained huge expertise and ample field knowledge to aid and assist you throughout your research. We are ready to offer you the following

What we support for digital forensics projects? 

• Comparative study on different digital forensic project topics through case studies
• The mechanisms, process model and methodologies followed in digital forensics
• Tools including the testing tools, new algorithms, techniques and process of validation involved in digital forensics
• Acknowledgement and standardization methods used

In this regard, you can get complete technical support along with ultimate assistance in collecting resources, conducting surveys for data collection, making Crisp algorithms and codes implementation in real-time, project simulation, writing thesis and paper publication , and many more. So you can approach us with huge confidence. Let us now have an overview of digital forensics. 

Overview of Digital Forensics 

Read the overview here. We provide you with the research agenda consisting of some basic categories that are important in any digital forensics project topics below

• Modelling the cases
• Modelling the process of investigation
• SAN and NAS
• IDS based automatic data collection
• Investigating the server and non-work station
• Tools for simultaneous working on evidence and images
• Providing the timeline of user history
• Generating traffic
• Carving and imaging in parallel
• Analysis of RAM
• Legal implications
• Interrupting execution for real-time acquisition
• Collecting evidence without permanent memory
• Honeypots in control and investigation mechanism
• Capture devices in network audit attempts based on hardware
• Control systems based on IDS
• Radio frequency forensics at 900 MHz

Recent advancements in science and technology have taken these basic processes of digital forensics given above to the next level. Huge scope of research and development can be observed in digital forensics project topics . So we suggest you take up research in any digital forensic project topics which are sure to give you a promising career. Let us now have a look at the major steps involved in digital forensics,

What are the important steps in digital forensics? 

As we stated before, digital forensics involves identifying evidence, acquiring and analyzing them, and finally presenting the most needed interpretations for further study. In this aspect let us now look into these significant processes in detail.

• The first step in the process of digital forensic investigation is identifying the evidences
• Evidences are different for different scenarios and you should be able to look into to the situations promptly
• In case of illegal graphic images you shall see the web history and various image files
• For intrusions look into rootkits, logs and hidden files
• In case of intelligence see the documents and emails
• After identifying the evidences the second step involved is acquiring them
• First of all the state of computer should be prevented from getting altered
• Bitwise copying of hard disc and copying memory before the system gets turned off is recommended
• The network connection States have to be saved and connection with the network have to be terminated
• While copying hard disk you should boot it in reliable media like Linux live CD and DOS floppy
• Be sure to detach the hard disc and place it in any trusted systems
• Evidence analysis is primarily based on the skill sets of an analyst and the nature of evidence collected
• Higher importance have to be given to aggregation of evidences, correlating them, filtering, transforming and generating metadata
• In pre analysis period or during acquisition you shall give priority 2 aggregation and transformation of evidence using data recovery and unification processes
• Also while generating metadata be sure to categorise, index and hash them
• Understanding the difference between evidence and data plays a key role in utilisation of information for evidence mapping, contextualization and isolation
• The final step in the digital forensic processes is the presentation of information
• While presenting information be sure to create reports on trusted evidences
• It is also the duty of a digital forensic analyst to present the role played by a given evidence in the case being investigated

Usually, these are the four steps involved in digital forensics. The analysts train themselves by handling various cases and having deep analysis over them. In order to get the perspective of experienced analysts and Research experts , you shall reach out to us at any time. We are here to support you in every aspect of your project. Let us now see the challenges and issues in digital forensics.

Despite the advancement of digital information forensics , a variety of difficulties persist. Let us see some of the important digital forensics issues faced these days. 

Challenges in digital forensics 

• Establishing approaches that adapt well over unexpected and previous unforeseen digital threats
• Building approaches that extend well enough to large amounts of biometric information among different population groupings
• Quantifying patterns in electronically altered information to verify the abuser of an attack
• Providing security of biometrics information and making it threat resistant
• Providing anonymity and confidential details in social media could reveal critical personal information

As we have handled ample projects in digital forensics , we are highly qualified and able to solve any kind of issues associated with them. Now let us look into different digital forensics datasets. What are the existing data sets for digital forensics projects?

Available Datasets for Digital Forensics

• It consists of 11530 images
• 27450 ROI annotated objects
• 6929 segments
• These are available in 20 classes
• It contains 9963 images
• 24640 annotated objects in more than 20 different classes

You can get a more detailed description of these datasets, their usage, source, and discovery once you reach out to us. We are here to give you practical descriptions and simple explanations to help you in using such datasets . Let us now talk about various methodologies in digital forensics

What are the methods for digital forensics? 

• Outgoing firewalls can be used for inspecting the outbound communications
• Encrypted communications can be intercepted using man in the middle attack
• Intruder targets for the system or set and activities of the intruders are monitored
• It also aims in identifying the intruder
• System and log files integrity has to be monitored
• Sensitive file alterations must be alerted to the administrator
• Examination and identification of hosts for guarding against unauthorized access
• Determination of hosts and their respective services along with the purpose

For algorithms, codes, and programming languages used in these methodologies, you can contact our technical support team.  Does digital forensics need coding?  Of course yes. So let us now talk about the best programming languages for all digital forensic project topics

Best Programming Languages for Digital Forensics Projects 

• C++ is commonly characterized as C’s brother
• It consists of some mixes of advanced math which are like meth and steroids
• C++ is a superb programming language that is mainly dependent on the source code of C
• Many operating systems are built on the C programming language
• It’s a lightweight, adaptable, and effective programming language which can handle a wide range of functions like cryptographic, image analysis, and sockets network
• SQL is extensively utilized for data maintenance and retrieval as a result of recent proliferation of data storage devices
• Attackers are also progressively influencing the language in order to destroy or steal information
• SQL injections, for instance, make use of SQL deficiencies to extract or change information stored on computers
• This is a programming language for building web pages on the web server
• Since PHP is used to develop the majority of websites, knowing how to defend against attackers is a must
• DDoS (denial-of-service) cyber-attacks, for instance, are designed to render web programs inaccessible to the authorized consumers
• You could create powerful alternatives to safeguard online applications using PHP programming experience along with abilities in all other languages including JavaScript
• The Java programming language provides numerous applications in different fields of cyber security
• For illustration, digital attackers utilize it to invert copyrighted software programs in order to find and expose weak points
• When it comes to payloads management, penetration testers frequently utilize Java to configure high-scaling hosts
• Mastering Java enables pen testing simpler, which is among the most important jobs of a cyber-security practitioner
• Java coding is used by professional ethical hackers to demonstrate effective, ethical systems
• Java is a great suggestion for cyber specialists since it is more dynamic than languages such as C++
• Ethical hackers can use Java to design vulnerability testing applications that can run on a variety of systems
• JavaScript is an advanced programming language that is known as the web’s “lingua franca” 
• The Internet runs on JavaScript, which is its fundamental technology
• The language is what gives websites their interaction
• Cross-site scripting, for instance, is an attack based on JavaScript where the attacker injects malware into a website
• If you’d like to grab cookies, target event controllers, and perform cross-site scripting, JavaScript is the way to go
• JavaScript libraries include NodeJS, jQuery and ReactJS
• As a consequence of the language’s extensive use, programs and infrastructure that employ it are prime target

The list of excellent computer languages for forensic science presented here is by no means comprehensive. You might discover one language better suited to any particular function than most others, depending on your individual utilization. 

How about using python for digital forensics?

• Python is a powerful programming language which is gaining in popularity amongst cyber security professionals
• It’s getting more popular thanks to its emphasis on readability of coding, precise and uncomplicated syntax, and a large variety of libraries
• You would use the language to transmit TCP packets to systems, analyse viruses, and build intrusion detection mechanisms without relying on third-party utilities

In these ways, every programming language has its own advantages and limitations with respect to digital forensics . We have been using python in projects of digital forensics for many years and so we are very well experienced in using python libraries and tools for these projects . Now we will provide you some more insight into using python for digital forensics research. 

Why Python for Digital forensics projects? 

The following are some of the distinctive aspects of the Python programming language which makes it an excellent choice for digital forensics project management

• Numerous pre-installed modules – Python’s extensive built-in modules are a fantastic tool for conducting a full digital forensic examination
• Syntax Simplicity – Python’s syntax is clear in comparison to many other languages, making it much easier to understand and utilize during digital forensics
• Support and Help – As Python is an open source software, it has a large development and users to support it

Also, you can get advice from the experts who have been handling python projects since their inception into the digital field. We will also give you tips regarding code implementation and algorithm writing. Let us now talk about python programming especially in digital forensics

Digital forensics using Python programming

• Once it comes to digital forensic, network security, and penetration testing, experts typically rely on a variety of programming languages, tools and software platforms
• In digital forensics, Parrot Security OS, Kali Linux, MetaSploit, and a range of additional technologies are utilized
• These tools include pre-installed programs that consumers can utilize regardless of understanding the internal design, algorithms or computational strategy for execution

Python is thus a popular programming language for tasks such as cyber defense, penetration testing, and digital forensics . All of the below tasks can indeed be accomplished without the need for a third-party solution and utilizing Python’s basic programming

• Simulation of attacks and Port scanning
• Web browser fingerprints and cloned websites
• Website load creation and testing
• Scanning of wireless networks and mail server access
• Developing methods for detecting and preventing intrusions
• Traffic transmission in the network

Interact with our technical experts to have much more ideas on the successful digital forensics project implemented using python in real-time . You can get our engineers deep insights into python forensic tools. Let us now look into the digital forensics python libraries

Python Libraries for Digital Forensics 

• A Python-based internet traffic analysis and manipulation program
• Scapy allows researchers to investigate packet manipulations
• In addition, you could decode and collect packets from a variety of protocols
• In contrast to Dshell, it gives a researcher comprehensive analysis on internet traffic
• It also can map mostly with services of a third party software or OS fingerprinting.
• This is a Python-based network forensic investigation toolset
• It was created by the US Military Research Lab and made open-source in the year 2014
• The use of this toolbox simplifies forensic inquiry
• dns – Extract DNS-related queries with dns
• large-flows – Compile a list of netflows
• protocols – Non-standard protocols should be identified
• ReservedIPs – Looks for solutions to DNS issues
• rip-http – tool for extracting files from HTTP transmission

These are the python libraries used in digital forensic projects . There are also additional, open-source, and free libraries for python programming which are of immense importance in digital forensics. In this respect, let us have a look at the python-imaging library below.

Python Imaging Library

• Data is stored in both basic and complicated data structures, such as databases and JPEG images
• Simple desktop programs can be used to access them, and advanced analysis tools could be used to acquire the complicated operations
• Users can use the Python language to develop techniques with the python imaging library
• It can handle a wide range of file types

What is python forensic? You can get expert solutions to such frequently asked questions from us. In this regard, the Python Imaging Library or PIL operation is described here

• The first step in python imaging library operation is the forensic image import
• Then the imported images are used along with PIL for data extraction
• Then the data is represented in the form of arrays
• Data organisation for analysing forensic evidences is the final step

Usually, we provide complete descriptions of all python libraries and tools suitable for digital forensics to our customers. For your doubts on the installation of the python imaging library, network project topics you shall readily contact us. Our technical support team is happy to guide you. Let us now talk about recent digital forensics project topics

Latest Digital Forensics Project Topics

• Safeguarding of vital infrastructure and cyber warfare
• Reaction to an emergency and real-time analysis
• Methodologies for event redevelopment
• Key Infrastructure Security and data Warfare
• Traffic flow evaluation, attribution and traceback
• Portable and small-scale electronics and large scale research
• Analysis of the system files and storage
• Retention and conservation of forensic evidence
• “File carving” is the process of extracting files from data chunks
• Data exploration, mining, concealment and retrieval

Do you have any problems with your digital forensics project Topics ? Our experts are here to offer you answer to all of your research questions so that you can improve the performance of your design. We can help you with research on any of the above areas. With our knowledge, we have the ability to develop your research in any digital forensic project area .