Efficient Computer Forensic Analysis Using Machine Learning Approaches

Toraskar, Tanmay; Bhangale, Ujwala; Patil, Suchitra; More, Nilkamal

doi:10.1109/ibssc47189.2019.8973099

Cited by 3 publications

(4 citation statements)

References 3 publications

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“…According to Toraskar et al (2019), the SOM mappings generated by MATLAB were clustered, demonstrating the viability of using SOM with enumerated artefacts and metadata in criminal investigations. However, the research cautions that it may be difficult to acquire a perfect mapping if the groupings are unique.…”

Section: Metadata Analysis Using Machine Learningmentioning

confidence: 99%

“…The research of Toraskar et al (2019) contributes significantly to the application of machine learning and forensic tools in digital forensic analysis. This study acknowledges the limitations of existing tools and introduces a novel method for clustering data using SOM.…”

Section: Metadata Analysis Using Machine Learningmentioning

confidence: 99%

“…The proposed implementation of the tool included HTML input and output in the form of tables and timelines, enabling examiners to efficiently manage criminal evidence. Walny et al (2020) state that one of Toraskar et al (2019) research's strengths is the use of taffy.js as a database library, which improves the tool's performance and reduces downtime, resulting in a system that runs smoothly. On top of that, the offline feature of the application protects the system from online malware and hackers, while the .csv export feature enables the secure storage of data.…”

Section: Chain Of Custodymentioning

confidence: 99%

“…Machine Learning in Digital Forensics (Toraskar et al, 2019) Demonstrated SOM viability in criminal investigations.…”

Section: Lowmentioning

confidence: 99%

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A Comprehensive Analysis of the Role of Artificial Intelligence and Machine Learning in Modern Digital Forensics and Incident Response

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Section: Metadata Analysis Using Machine Learningmentioning

confidence: 99%

Section: Metadata Analysis Using Machine Learningmentioning

confidence: 99%

Section: Chain Of Custodymentioning

confidence: 99%

“…Machine Learning in Digital Forensics (Toraskar et al, 2019) Demonstrated SOM viability in criminal investigations.…”

Section: Lowmentioning

confidence: 99%

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A Comprehensive Analysis of the Role of Artificial Intelligence and Machine Learning in Modern Digital Forensics and Incident Response

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et al. 2023

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Enhancing Forensic Analysis Using a Machine Learning-based Approach

Benkerroum,

Chougdali

2023

2023 6th International Conference on Advanced Communication Technologies and Networking (CommNet)

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Unveiling the Dynamic Landscape of Digital Forensics: The Endless Pursuit

Zareen,

Aslam,

Tahir

et al. 2024

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The invention of transistors in the 1940s marked the beginning of a technological revolution that has impacted every aspect of our lives. However, along with the positive advancements, the malicious use of computing technologies has become a serious concern. The international community has been actively collaborating to develop digital forensics techniques to combat the unlawful use of these technologies. However, the evolution of digital forensics has often lagged behind the rapid developments in computing technologies. In addition to their harmful use, computing devices are increasingly involved in crime scenes and accidents, necessitating digital forensics to reconstruct events. This paper provides a comprehensive review of the development of computing technologies from the 1940s to the present, highlighting the trends in their malicious use and the corresponding advancements in digital forensics. The paper also discusses various institutes, laboratories, organizations, and training setups established at national and international levels for digital forensics purposes. Furthermore, it explores the initial legislations related to computer-related crimes and the standards associated with digital forensics. These reviews and discussions conclude at identifying the shortfalls in digital forensics and proposes an all-inclusive digital forensics process model meeting these shortfalls while complying to international standards and meeting regulatory and legal requirements of digital forensics.

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Efficient Computer Forensic Analysis Using Machine Learning Approaches

Cited by 3 publications

References 3 publications

A Comprehensive Analysis of the Role of Artificial Intelligence and Machine Learning in Modern Digital Forensics and Incident Response

A Comprehensive Analysis of the Role of Artificial Intelligence and Machine Learning in Modern Digital Forensics and Incident Response

Enhancing Forensic Analysis Using a Machine Learning-based Approach

Unveiling the Dynamic Landscape of Digital Forensics: The Endless Pursuit

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