This book presents the latest research on honeypots and their applications. After introducing readers to the basic concepts of honeypots and common types, it reviews various honeypot frameworks such as web-server-based, client-based, shadow and artificially intelligent honeypots. In addition, it offers extensive information on the contribution of honeypots in some of the most popular malware research area such as DDoS, Worm, APT, forensics and Bot attacks. The book subsequently tackles the issue of honeypot countermeasures, shows many of the tricks often used by hackers to discover honeypots, and proposes a counter-countermeasure to help conceal them. It then puts forward a new framework that integrates various novel concepts, and which can feasibly be used for the detection of potential ransomware and bitcoin. As such, the book provides non-experts with a concise guide to honeypots, and will also benefit practitioners working on security systems.

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Chee Keong NG completed his Master of IT at Deakin University, Australia. He is now pursuing his PHD in Philosophy (IT). His research interests include honeypots, ransomware and deep learning.

Dr Lei Pan received his Ph.D. in Computer Forensics from Deakin University, Melbourne, Australia, in 2008. He currently teaches at Deakin University, Burwood, Victoria, Australia, where he offers courses on cybersecurity. His research interests include cybersecurity and privacy, software security testing, and the applications of analytics in security and privacy. He is also an active cybersecurity educator on futurelearn.com. Professor Yang Xiang received his PhD in Computer Science from Deakin University, Australia and is currently the Dean of the Digital Research & Innovation Capability Platform at Swinburne University of Technology, Australia. His research interests include network and system security, data analytics, distributed systems, and networking. Further, he is a Senior Member of the IEEE.

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