A graph-based system for network-vulnerability analysis
Proceedings of the 1998 workshop on New security paradigms
Scalable, graph-based network vulnerability analysis
Proceedings of the 9th ACM conference on Computer and communications security
Automated Generation and Analysis of Attack Graphs
SP '02 Proceedings of the 2002 IEEE Symposium on Security and Privacy
Using Model Checking to Analyze Network Vulnerabilities
SP '00 Proceedings of the 2000 IEEE Symposium on Security and Privacy
Efficient Minimum-Cost Network Hardening Via Exploit Dependency Graphs
ACSAC '03 Proceedings of the 19th Annual Computer Security Applications Conference
A Systematic Approach to Multi-Stage Network Attack Analysis
IWIA '04 Proceedings of the Second IEEE International Information Assurance Workshop (IWIA'04)
Managing attack graph complexity through visual hierarchical aggregation
Proceedings of the 2004 ACM workshop on Visualization and data mining for computer security
SWAN: A Secure Wireless LAN Architecture
LCN '04 Proceedings of the 29th Annual IEEE International Conference on Local Computer Networks
A Host-Based Approach to Network Attack Chaining Analysis
ACSAC '05 Proceedings of the 21st Annual Computer Security Applications Conference
Value Driven Security Threat Modeling Based on Attack Path Analysis
HICSS '07 Proceedings of the 40th Annual Hawaii International Conference on System Sciences
ICNC '07 Proceedings of the Third International Conference on Natural Computation - Volume 05
A Vulnerability and Exploit Independent Approach for Attack Path Prediction
CITWORKSHOPS '08 Proceedings of the 2008 IEEE 8th International Conference on Computer and Information Technology Workshops
Computational Intelligence Pc Tools [Books in Brief]
IEEE Transactions on Neural Networks
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In recent years there has been an immense proliferation of wireless networks and they are becoming increasingly vulnerable to attacks. Thus there is a serious need to secure such networks from attacks. Usually an attacker can penetrate into a network by utilizing a chain of exploits. An exploit is a small piece of code that makes use of vulnerabilities present in a service or in a system. Each exploit in the chain has a set of preconditions and effects and lays the groundwork for the subsequent exploits. Application of such a chain of exploits generates a set of attack states or network states which form a path called the attack path and combining many such attack paths produces an attack graph. A lot of research has been done on issues such as scalable and time efficient ways of generation of attack graphs in wired network in contrast to that in wireless scenario. Moreover, the need is to identify the path that may be chosen by the attacker to comprise a target system in less time and effort. The proposed methodology in this paper aims as finding out the optimal or risk-prone attack path that the attacker may choose to penetrate a wireless network. The generation of attack paths in a wireless network is itself a difficult proposition due to networks inherent dynamic nature and ever changing topology. In this work, the Particle Swarm Optimization (PSO) technique has been employed for finding out the optimal attack path using an attack vector metric. The effort required on the part of the attacker to compromise a target system has been termed as an attack vector. The wireless nodes have been assigned severity measures obtained from customized risk parameters which serve as an input to the modified PSO technique. A case study has also been presented to demonstrate the efficacy of the proposed methodology.