基于人工智能的新型入侵检测体系结构研究

S. Khanji, A. Khattak
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引用次数: 0

摘要

人工智能(AI)是一种变革性技术,在工业、社会、智能和数字应用中有可能取代人类的任务和活动。网络入侵检测对于识别关键基础设施中的网络攻击至关重要,在这些基础设施中,可以使用人工智能进行网络流量的动态收集和分析。在本文中,我们开发了一种新的入侵检测架构,以减少通过组织网络基础设施的恶意流量。我们建议设计基于人工智能的场景,用于智能自我保护或警报系统,以方便应对实际的网络攻击。该系统将利用机器学习算法——随机森林——为发现新的攻击提供更大的灵活性,并确保训练系统在未来预测它们。此外,我们在python上设计了垃圾邮件过滤程序来检测垃圾邮件,因为电子邮件是威胁关键基础设施安全的主要攻击媒介之一。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Towards a Novel Intrusion Detection Architecture using Artificial Intelligence
Artificial intelligence (AI) is a transformative technology for potential replacement of human tasks and activities within industrial, social, intellectual, and digital applications. Network intrusion detection is crucial to identify cyber-attacks in critical infrastructures where a dynamic collection and analysis of network traffic can be conducted using AI. In this research paper we develop a novel intrusion detection architecture to mitigate malicious traffic passing through cyber infrastructure of an organization. We propose to design scenarios based on AI for intelligent self-protection or alert system that will facilitate countering actual cyber-attacks. The system will utilize machine learning algorithm - Random Forest - to offer more flexibility to discover new attacks and to ensure training the system to predict them in the future. Moreover, we design spam filtering program on python to detect spam emails as per email is one of the main attacking vectors that threatens the security of critical infrastructures.
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