Intrusion detection with neural networks
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
IEEE Network: The Magazine of Global Internetworking
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Intrusion detection systems (IDSs) offer the potential advantages of reducing manpower needed in monitoring, increasing detection efficiency, providing data that would otherwise not be available, helping the Information Security community learn about new vulnerabilities, and providing legal evidence. This technology has improved over time, but it unfortunately is beset with many inherent limitations. Examples include commercial products with insufficient capability to detect many attacks, lack of empirical testing, inability to handle encrypted traffic, and susceptibility to attack. Intrusion detection technology is, however, at a crossroads; governments' efforts to protect critical infrastructures are resulting in increased funding in this area. Additionally, deploying this technology advantageously within an organization involves a steep learning curve - integrating this technology into operational environments requires many cultural changes. Despite the many associated limitations in this technology, therefore, organizations should immediately start deploying it and integrating it into the mainstream of their operational activity.