Mobile Agent-Based Anomaly Detection and Verification System for Smart Home Sensor Networks

Puts forward a detailed mobile agent-enabled anomaly detection and verification system for resource constrained sensor networks

Includes a number of algorithms on multi-aspect anomaly detection in sensor networks

Presents several algorithms on mobile agent transmission optimization in resource constrained sensor networks

Highlights an algorithm on mobile agent-enabled in situ verification of anomalous sensor nodes

Offers a detailed Petri Net-based formal modeling and analysis of the proposed system

Includes an algorithm on fuzzy logic-based cross-layer anomaly detection and mobile agent transmission optimization

Autorentext

Dr. Muhammad Usman

Muhammad Usman received his Ph.D. degree from the School of Information and Communication Technology, Griffith University, Australia. He has obtained Juniper Networks, USA, certifications as an internet specialist and internet associate in enterprise routing and switching. He is a member of the Network Security Research Group and the Institute for Integrated and Intelligent Systems (IIIS), Griffith University, Australia. He is also a member of the Computer Science Teacher Association endorsed by the Association for Computing Machinery (ACM), USA. He is currently associated with the Department of Computer Sciences, Quaid-I-Azam University, Pakistan, as an Assistant Professor. His current research interests are Security and Privacy, Cloud Computing, Internet of Things, Distributed Systems, and Modeling and Analysis. He has published over twenty five research papers for international journals and conferences including prestigious journals such as IEEE Transactions on Consumer Electronics. He has been a recipient of several honors, awards, and grants throughout his industrial and academic career.

Vallipuram Muthukkumarasamy

Vallipuram Muthukkumarasamy obtained his B.Sc. in Engineering from the University of Peradeniya, Sri Lanka and his Ph.D. from Cambridge University, England. He is currently attached to the School of Information and Communication Technology, Griffith University, Australia as an Associate Professor. His current research areas include the investigation of security issues in wireless networks, sensor networks, trust management in mobile ad hoc networks (MANETs), key establishment protocols and medical sensors. He currently heads the Network Security Research Group at the Institute for Integrated and Intelligent Systems at Griffith University. Also providing leadership with regard to innovative learning and teaching practices, he has received a number of best teacher awards.

Dr. Xin-Wen Wu

Xin-Wen Wu received his Ph.D. degree from the Chinese Academy of Sciences, Beijing. He has worked in the University of California at San Diego (as a postdoctoral researcher), the Chinese Academy of Sciences, and the University of Melbourne (as a research fellow). He was also affiliated with the University of Ballarat, Australia. He joined Griffith University, Australia, in 2010, as a faculty member at the School of Information and Communication Technology. His research interests include cyber security and data privacy, applied cryptography, coding techniques, and information theory and its applications. He has published extensively in these areas, including three books and over eighty research papers in leading journals of IEEE, Springer, and Elsevier, in addition to proceedings of international conferences. He is a senior member of IEEE.

Ms. Surraya Khanum

Surraya Khanum received her M.S. (Computer Science) from International Islamic University,Islamabad, Pakistan. She has been associated with Griffith University, Australia as a visiting research associate. She has also worked as a Lecturer at King Khalid University, Saudi Arabia and as a Visiting Lecturer at Department of Computer Sciences, Quaid-I-Azam University, Pakistan. She has published numerous research papers, predominantly in the domains of mobile agent-based distributed systems and intrusion detection systems.

Inhalt
Introduction.- Background.- Abnormality Identication and Conrmation System.- First-Order Abnormalities: Agent Transmission Optimization.- Cross-Layer Identication and Transmission of Agent Using Fuzzy Logic.- Conclusions.