Visualization of wormholes in sensor networks
Proceedings of the 3rd ACM workshop on Wireless security
Detecting Flaws and Intruders with Visual Data Analysis
IEEE Computer Graphics and Applications
The feasibility of launching and detecting jamming attacks in wireless networks
Proceedings of the 6th ACM international symposium on Mobile ad hoc networking and computing
IEEE Computer Graphics and Applications
Visualization assisted detection of sybil attacks in wireless networks
Proceedings of the 3rd international workshop on Visualization for computer security
Security Data Visualization
Applied Security Visualization
Applied Security Visualization
Visual Analytics: Scope and Challenges
Visual Data Mining
Sensor network security: a survey
IEEE Communications Surveys & Tutorials
Securing wireless sensor networks: a survey
IEEE Communications Surveys & Tutorials
A Survey of Visualization Systems for Network Security
IEEE Transactions on Visualization and Computer Graphics
Sybil attack detection through global topology pattern visualization
Information Visualization
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Security concerns are a major deterrent in many applications wireless sensor networks are envisaged to support. To date, various security mechanisms have been proposed for these networks dealing with either Medium Access Control (MAC) layer or network layer security issues, or key management problems. Security visualization is the latest weapon that has been added in the arsenal of a security officer who is tasked with detecting network anomalies by analyzing large amounts of audit data. This paper proposes a novel security visualization system for analyzing and detecting complex patterns of sensor network attacks, called SRNET. Both selective forwarding and jamming attacks are identified through visualizing and analyzing network traffic data on multiple coordinated views, namely the multidimensional crossed view, the crossed view perspective, and the track area view. Through simulations, we demonstrate that SRNET is able to help detect and further identify the root cause of the aforementioned sensor network attacks.