By Pawel Skrobanek (editor)
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Additional info for Intrusion Detection Systems
People involved in AI seem much more interested in other applications, although in many ways cybersecurity should be a natural domain of application for AI. The problem may lie more with cybersecurity than the AI community. Cybersecurity projects the impression of a chaotic world devoid of coherence and lacking codification. As a result of that situation, most of the attempts to introduce AI in intrusion detection consisted in trying to apply existing tools developed or used in AI to cybersecurity.
E. its function may not be limited to protection. 8. Conclusions Cybersecurity is a real challenge and the future of the internet partially depends on how that challenge is met. For a long time it has been clear that the cybersecurity response to the fast evolving threat needs to be much smarter than has been the case. ] are not addressed, a set of blunt solutions will likely be applied to solve problems at the expense of much of what we love about today’s information ecosystem”. This chapter focused on anomaly-based intrusion detection.
The content in this paper divided into 7 sections. Firstly, the section is introduction. Secondly, the section is the related work. Thirdly, this section will explain about our architecture and model description. Fourthly, the section is architecture analysis. Fifthly, the section is analytical result. Sixthly, the section is our architecture proofing. And the last section is conclusion, recommendation and future work. 2. Related work. The research in the field of the intrusion detection system that use the agent-based detection representative program technology can be separated to 3 levels, approach level , , , , ,  implementation level , , and evaluation level , .
Intrusion Detection Systems by Pawel Skrobanek (editor)