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VHDL Modeling of Intrusion Detection & Prevention System (IDPS) – A Neural Network Approach

机译:入侵检测与防御系统(IDPS)的VHDL建模–神经网络方法

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The rapid development and expansion of World Wide Web and network systems have changed the computing world in the last decade and also equipped the intruders and hackers with new facilities for their destructive purposes. The cost of temporary or permanent damages caused by unauthorized access of the intruders to computer systems has urged different organizations to increasingly implement various systems to monitor data flow in their network. The systems are generally known as Intrusion Detection System (IDS).Our objective is to implement an artificial network approach to the design of intrusion detection and prevention system and finally convert the designed model to a VHDL (Very High Speed Integrated Circuit Hardware Descriptive Language) code. This feature enables the system to suggest proper actions against possible attacks. The promising results of the present study show the potential applicability of ANNs for developing practical IDSs.
机译:在过去的十年中,万维网和网络系统的迅速发展和扩展改变了计算世界,并且还为入侵者和黑客提供了具有破坏性目的的新功能。入侵者未经授权访问计算机系统所造成的暂时性或永久性损害的成本,促使不同组织越来越多地实施各种系统来监视其网络中的数据流。该系统通常被称为入侵检测系统(IDS)。我们的目标是实施一种人工网络方法来设计入侵检测和防御系统,最后将设计模型转换为VHDL(超高速集成电路硬件描述语言)码。此功能使系统可以建议针对可能的攻击采取的适当措施。本研究的有希望的结果显示了人工神经网络在开发实用IDS中的潜在适用性。

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