Dark Web Pattern Recognition and Crime Analysis Using Machine Intelligence

  • 5h 49m
  • Om Kumar C.U., P. William, Romil Rawat, Shrikant Telang, Upinder Kaur
  • IGI Global
  • 2022

Data stealing is a major concern on the internet as hackers and criminals have begun using simple tricks to hack social networks and violate privacy. Cyber-attack methods are progressively modern, and obstructing the attack is increasingly troublesome, regardless of whether countermeasures are taken. The Dark Web especially presents challenges to information privacy and security due to anonymous behaviors and the unavailability of data. To better understand and prevent cyberattacks, it is vital to have a forecast of cyberattacks, proper safety measures, and viable use of cyber-intelligence that empowers these activities.

Dark Web Pattern Recognition and Crime Analysis Using Machine Intelligence discusses cyberattacks, security, and safety measures to protect data and presents the shortcomings faced by researchers and practitioners due to the unavailability of information about the Dark Web. Attacker techniques in these Dark Web environments are highlighted, along with intrusion detection practices and crawling of hidden content. Covering a range of topics such as malware and fog computing, this reference work is ideal for researchers, academicians, practitioners, industry professionals, computer scientists, scholars, instructors, and students.

About the Author

Romil Rawat is currently working as Assistant Professor in Shri Vaishnav Vidyapeeth Vishwavidyalaya, Indore, India. He attended several research programs and received research grants from USA, Germany, Italy and UK. The Author has research alignment towards Cyber Security, IoT, Dark Web Crime analysis and investigation techniques, and working towards tracing of illicit anonymous contents of cyber terrorism and criminal activities. He also chaired International Conferences and Hosted several research events including National and International Research Schools, PhD colloquium, Workshops, training programs. He also published several Research Patents.

Shrikant Telang is currently working as Assistant Professor in Shri Vaishnav Vidyapeeth Vishwavidyalaya, Indore, India. He attended several research programs. The Author has research alignment towards Cyber Security, IoT, Dark Web Crime analysis and investigation techniques, and working towards tracing illicit anonymous contents of cyber terrorism and criminal activities. He also joins International Conferences and several research events including National and International Research Schools, Workshops, training programs. He also published several Research Patents.

P. William is working as an Assistant Professor, Department of Information Technology, Sanjivani College of Engineering, SPPU Pune. He received his Bachelor of Engineering in Computer Science and Engineering from CSVTU, Bhilai in 2013 and Master of Technology in Computer Science and Engineering from CSVTU, Bhilai in 2017. He is currently pursuing his Ph. D. in the Department of Computer Science and Engineering from School of Engineering & Information Technology, MATS University, Raipur. He has published many papers in Scopus indexed journals and IEEE Conferences. His field of research includes Natural Language Processing, Machine learning, Soft Computing, Cyber Security and Cloud Computing. He has been associated with numerous Multi-National Companies including IBM, TCS etc. and Educational Groups. A focused and hardworking professional with experience in taking Corporate Trainings. He is a Life Member of Quality Circle Forum of India (QCFI) and member of various other professional bodies.

Upinder Kaur is working as an Assistant Professor in the Department of Computer Science and Engineering, Akal University, Bathinda, Punjab, India. She received her Ph. D. Degree at Department of Computer Science and Applications, Kurukshetra University, Kurukshetra. She is in teaching since October 2006. She holds Master of Technology (M. Tech.) degree in Computer Science and Engineering from MMEC, Mullana, Ambala, India. Her main research interests are in the areas of Distributed Computing, Distributed Data Structures, Cloud Computing, Data Science and Analytics, ML/DL. Currently working on the research issues in applications of deep learning in agriculture and health care. She has attended many National and International Conferences/workshops and she has more than 25 research papers in national / international journals and conferences. She has also a member of IEEE, ACM and supervising three Ph.D. Scholars and several graduate and undergraduate students in multi-cloud domain and data science in agriculture and deep learning in bio-signals.

Om Kumar C.U. has specialized in the domain of Cyber Security at Anna University, Chennai (2016-2020) for obtaining a Ph.D. His B.Tech in CSE (2006-10) and M.Tech in CSE (2011-2013) with First class with Distinction were from colleges affiliated to JNTU- Anantapur. Hisinitial stint at Teaching was at SRM- Easwari Engineering College, Chennai from (2013-2016) proved my teaching potential and made me choose Teaching as my profession. His research interest spans across IoT and Deep Learning in particular. Major research contributions have been published by 3 SCI journals (Journal of Super Computing Springer, Computer Communications Elsevier, Computational Intelligence Wiley). He holds 6 Scopus publications as of date. Have published two books pertaining to Anna university syllabus of CSE. Received accolades through acknowledgment from Oxford publications for reviewing the book titled ‘Programming and Data Structures’ by Dr. Thareja. He is a peer-review member of Concurrency and Computation Wiley, Microprocessor and MicroSystem Elsevier, and Automated Intelligence and Humanized Computing Springer. He is an editorial member of Medicon and Machine Learning Research journals.

In this Book

  • Multi-Access Edge and Fog Computing Technique Analysis for Security and Privacy of 6G-Driven Vehicular Communication Network in Industry 5.0 Internet
  • Minimum Prediction Error at an Early Stage in Darknet Analysis
  • An Efficient Technique for Passive Image Forgery Detection Using Computational Intelligence
  • Machine Learning Models in Detecting Cyber Crimes and Cyber Terrorism in India
  • Overview of Web Dawdler Outline and FKNN Utilizing Cluster-Based Secret Net
  • Crowdfunded Assassinations and Propaganda by Dark Web Cyber Criminals
  • Neural Net Architecture Strategy Identifying Zero-Day Attacks in the Dark Web
  • Implementation of Machine Learning Techniques for Analyzing Crime and Dark Web Data
  • Image Processing for Criminal Pattern Detection Using Machine Learning in the Dark Web
  • A Fuzzy-GA for Predicting Terrorist Networks in Social Media
  • Crime Detection on Social Networks Using AI and ML Techniques
  • Ranking for Better Indexing in the Hidden Web
  • Internet of Things Security Challenges and Concerns for Cyber Vulnerability
  • Cyber Security for Secured Smart Home Applications Using Internet of Things, Dark Web, and Blockchain Technology in the Future
  • Forecasting the Traits of Cyber Criminals Based on Case Studies
  • Dark Web for the Spread of Illegal Activities Using Tor
  • Compilation of References
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