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Information
Special Issues
Digital Forensic Investigation and Incident Response
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Digital Forensic Investigation and Incident Response

A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Information Security and Privacy".

Deadline for manuscript submissions: 30 November 2024 | Viewed by 3439

Special Issue Editors

Prof. Dr. Cihan Varol

E-Mail Website
Guest Editor
Department of Computer Science, Sam Houston State University, Huntsville, TX 77340, USA
Interests: digital forensics; cybersecurity; data cleaning; data quality
Dr. Amar Rasheed

E-Mail Website
Guest Editor
Department of Computer Science, Sam Houston State University, Huntsville, TX 77340, USA
Interests: cybersecurity; hardware security and forensics; malware analysis
Dr. Umit Karabiyik

E-Mail Website
Guest Editor
Department of Computer and Information Technology, Purdue University, West Lafayette, IN 47907, USA
Interests: digital forensics; artificial intelligence
Special Issues, Collections and Topics in MDPI journals
Dr. Narasimha Shashidhar

E-Mail Website
Guest Editor
Department of Computer Science, Sam Houston State University, Huntsville, TX 77340, USA
Interests: digital forensics; cybersecurity; malware analysis
Prof. Dr. Rui Zhang

E-Mail Website
Guest Editor
Institute of Information Engineering, Chinese Academy of Sciences, Beijing 100093, China
Interests: information security and privacy

Special Issue Information

Dear Colleagues,

Digital forensics investigation and incident response play a critical role in addressing the evolving landscape of cyber threats. As technology advances, so do the methods and strategies employed by malicious actors. This Special Issue aims to showcase the latest research and advancements in digital forensics and incident response, providing a platform for researchers and practitioners to exchange knowledge and ideas.

Topics of interest:

We invite submissions in, but not limited to, the following areas:

  • Digital Forensics Techniques:
    • Memory forensics
    • Disk and file system analysis
    • Network forensics
    • Mobile and IoT device forensics
    • Cloud forensics
  • Incident Response Strategies:
    • Threat intelligence and information sharing
    • Automation in incident response
    • Incident detection and analysis
    • Cyber threat hunting
  • Forensic Challenges in Emerging Technologies:
    • Blockchain and cryptocurrency investigations
    • AI and machine learning in digital forensics
    • 5G and its impact on investigations
    • Challenges in forensics for edge computing environments
  • Case Studies and Best Practices:
    • Real-world examples of successful digital investigations
    • Lessons learned from incident response scenarios
    • Best practices for improving cybersecurity posture

Prof. Dr. Cihan Varol
Dr. Amar Rasheed
Dr. Umit Karabiyik
Dr. Narasimha Shashidhar
Prof. Dr. Rui Zhang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Information is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • digital forensics
  • digital investigation
  • incident response
  • AI in digital forensics

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (1 paper)

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Review

25 pages, 397 KiB  
Review
Cybercrime Intention Recognition: A Systematic Literature Review
by Yidnekachew Worku Kassa, Joshua Isaac James and Elefelious Getachew Belay
Information 2024, 15(5), 263; https://doi.org/10.3390/info15050263 - 5 May 2024
Cited by 2 | Viewed by 2783
Abstract
In this systematic literature review, we delve into the realm of intention recognition within the context of digital forensics and cybercrime. The rise of cybercrime has become a major concern for individuals, organizations, and governments worldwide. Digital forensics is a field that deals [...] Read more.
In this systematic literature review, we delve into the realm of intention recognition within the context of digital forensics and cybercrime. The rise of cybercrime has become a major concern for individuals, organizations, and governments worldwide. Digital forensics is a field that deals with the investigation and analysis of digital evidence in order to identify, preserve, and analyze information that can be used as evidence in a court of law. Intention recognition is a subfield of artificial intelligence that deals with the identification of agents’ intentions based on their actions and change of states. In the context of cybercrime, intention recognition can be used to identify the intentions of cybercriminals and even to predict their future actions. Employing a PRISMA systematic review approach, we curated research articles from reputable journals and categorized them into three distinct modeling approaches: logic-based, classical machine learning-based, and deep learning-based. Notably, intention recognition has transcended its historical confinement to network security, now addressing critical challenges across various subdomains, including social engineering attacks, artificial intelligence black box vulnerabilities, and physical security. While deep learning emerges as the dominant paradigm, its inherent lack of transparency poses a challenge in the digital forensics landscape. However, it is imperative that models developed for digital forensics possess intrinsic attributes of explainability and logical coherence, thereby fostering judicial confidence, mitigating biases, and upholding accountability for their determinations. To this end, we advocate for hybrid solutions that blend explainability, reasonableness, efficiency, and accuracy. Furthermore, we propose the creation of a taxonomy to precisely define intention recognition, paving the way for future advancements in this pivotal field. Full article
(This article belongs to the Special Issue Digital Forensic Investigation and Incident Response)
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