Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Bro: a system for detecting network intruders in real-time
SSYM'98 Proceedings of the 7th conference on USENIX Security Symposium - Volume 7
Agent societies and social networks for ubiquitous computing
Personal and Ubiquitous Computing
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As cyber security is a major challenge in the widespread deployment of the latest technologies, the importance of selecting the open ports for a given web filter cannot be overemphasized. A network administrator would want to select a combination of ports that would be most beneficial to the users and these ports would be treated as least vulnerable. However, this is not a trivial task and can be very time-consuming, O(n!), if brute force or other naïve approaches are used to select a given number of ports from 65,536 ports available. As genetic algorithms (GAs) are commonly used to obtain near-optimal solution for complex and time-consuming tasks, this paper proposes a GA for the selection of open ports for a web filter. The gene value for each port is based on the malicious issues associated with the port and the importance of the port to the client using the web filter. The proposed algorithm is implemented in Java, and the simulation results show that GA is very accurate in identifying open ports for a given web filter.