Advancements in Cyber Crime Investigations and Modern Data Analytics (eBook, PDF)
Redaktion: Shandilya, Shishir Kumar; Gupta, V. B.; Sujay, Devangana
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Advancements in Cyber Crime Investigations and Modern Data Analytics (eBook, PDF)
Redaktion: Shandilya, Shishir Kumar; Gupta, V. B.; Sujay, Devangana
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This book presents a fresh perspective on combating cybercrime, showcasing innovative solutions from experts across various fields. With the integration of artificial intelligence (AI), contemporary challenges are addressed with state-of-the-art strategies.
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This book presents a fresh perspective on combating cybercrime, showcasing innovative solutions from experts across various fields. With the integration of artificial intelligence (AI), contemporary challenges are addressed with state-of-the-art strategies.
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Produktdetails
- Produktdetails
- Verlag: Taylor & Francis
- Seitenzahl: 186
- Erscheinungstermin: 27. Dezember 2024
- Englisch
- ISBN-13: 9781040263556
- Artikelnr.: 72481173
- Verlag: Taylor & Francis
- Seitenzahl: 186
- Erscheinungstermin: 27. Dezember 2024
- Englisch
- ISBN-13: 9781040263556
- Artikelnr.: 72481173
- Herstellerkennzeichnung Die Herstellerinformationen sind derzeit nicht verfügbar.
Dr Shishir Kumar Shandilya Dr. Shishir Kumar Shandilya, is an Associate Professor in the School of Data Science and Forecasting at Devi Ahilya University in India. He is also a Visiting Professor at Liverpool Hope University in the United Kingdom. He is a Cambridge University-certified professional teacher and trainer, a TEDx speaker, an ACM Distinguished Speaker, and a senior member of IEEE. Shandilya is a NASSCOM-certified master trainer for security analysts in SOC (SSC/Q0909: 7 NVEQF Level 7). He has received the IDA Teaching Excellence Award for distinctive use of technology in teaching by the Indian Didactics Association in Bangalore (2016), and the Young Scientist Award for two consecutive years, 2005 and 2006, by the MP Science Congress and MP Council of Science and Technology. He is a highly regarded author with published research works in reputable academic publishers such as Springer, IGI-USA, River Denmark, and Prentice Hall of India. Dr. Shandilya also has international and national patents and copyrights granted for adaptive cyber defense methods. His research interest includes adaptive defense, advanced digital investigation and forensic methods, explainable artificial intelligence, privacy-preserving computing, nature-inspired cryptography (NIC), and Nature-inspired cyber security (NICS). Devangana Sujay Devangana Sujay is an independent researcher in the field of digital forensics. Her research topics range from admissibility of digital evidence to child sexual abuse material and privacy preservation. Her core competencies relate to digital forensics, cyber security, and cyber law. She works at SECURE - Centre of Excellence in Cybersecurity as a coordinator and has done studies in the area of digital forensics. She has also had the experience of working with the Data Security Council of India as Technology Policy Intern. Her other affiliations include being an active member of WiCyS-Women in Cybersecurity and BBWIC-Breaking Barriers Women in Cybersecurity. Dr VB Gupta Dr. V.B. Gupta, is a Professor and Head of the School of Data Science and Forecasting at Devi Ahilya Vishwavidyalaya (DAVV) in Indore, India. He has Ph.D. from the Indian Institute of Technology, Delhi, and has over 30 years of experience in teaching and research. His areas of specialization include data science, mathematical modeling, simulation, environmental management, technology diffusion and systems engineering. Dr. Gupta has published over 70 research papers in national and international journals and conferences. He is a member of the System Dynamics Society of India and has reviewed several research papers submitted in national and international journals. He has served as member of several academic committees of University Grants Commission, New Delhi. He developed several P.G. programmes. Dr. Gupta is a passionate advocate for the use of mathematical modeling and simulation to solve real-world problems. He is a strong believer in the power of education to transform lives and societies.
About the Editors. List of Contributors. Acknowledgements. 1. Introduction
to Cybercrime Investigation: A Modern Approach. 2. Privacy-based Triage of
Suspicious Activity Report using Offline Large Language Models. 3. A
Comprehensive Survey of Technological Approaches in the Detection of CSAM.
4. Advanced Mobile Forensics - Beyond Tool Automation. 5. Digital
Forensics: Extracting Information from Devices. 6. Data Driven Forensics
Unveiling Hidden Depths of Financial Crimes. 7. Unmasking the Threat: A
Viewpoint on AI-based Deepfake Financial Crimes. 8. Machine Learning in AI
in Cyber Crime Detection.
to Cybercrime Investigation: A Modern Approach. 2. Privacy-based Triage of
Suspicious Activity Report using Offline Large Language Models. 3. A
Comprehensive Survey of Technological Approaches in the Detection of CSAM.
4. Advanced Mobile Forensics - Beyond Tool Automation. 5. Digital
Forensics: Extracting Information from Devices. 6. Data Driven Forensics
Unveiling Hidden Depths of Financial Crimes. 7. Unmasking the Threat: A
Viewpoint on AI-based Deepfake Financial Crimes. 8. Machine Learning in AI
in Cyber Crime Detection.
About the Editors. List of Contributors. Acknowledgements. 1. Introduction
to Cybercrime Investigation: A Modern Approach. 2. Privacy-based Triage of
Suspicious Activity Report using Offline Large Language Models. 3. A
Comprehensive Survey of Technological Approaches in the Detection of CSAM.
4. Advanced Mobile Forensics - Beyond Tool Automation. 5. Digital
Forensics: Extracting Information from Devices. 6. Data Driven Forensics
Unveiling Hidden Depths of Financial Crimes. 7. Unmasking the Threat: A
Viewpoint on AI-based Deepfake Financial Crimes. 8. Machine Learning in AI
in Cyber Crime Detection.
to Cybercrime Investigation: A Modern Approach. 2. Privacy-based Triage of
Suspicious Activity Report using Offline Large Language Models. 3. A
Comprehensive Survey of Technological Approaches in the Detection of CSAM.
4. Advanced Mobile Forensics - Beyond Tool Automation. 5. Digital
Forensics: Extracting Information from Devices. 6. Data Driven Forensics
Unveiling Hidden Depths of Financial Crimes. 7. Unmasking the Threat: A
Viewpoint on AI-based Deepfake Financial Crimes. 8. Machine Learning in AI
in Cyber Crime Detection.