采用蜜罐和群体智能的入侵检测系统

Gurdip Kaur, Meenu Khurana, Monika Sethi
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引用次数: 5

摘要

随着网络和Internet流量的增加和规模的增大,为了减少入侵检测和诊断所需的开销,对入侵检测的需求日益增长,这使得公共服务器越来越容易受到未经授权的访问和入侵。除了为客户端维护低延迟和低性能之外,过滤未经授权的访问已成为服务器管理员的主要关注点之一。蜜罐是为监视和记录探测、攻击或危害它们的实体的活动而设置的诱饵计算机资源。根据定义,蜜罐上的活动可以被认为是可疑的,因为良性用户与这些系统交互没有任何意义。蜜罐有许多形状和大小;示例包括数据库中的虚拟项、低交互网络组件(如预配置的流量接收器)或具有实际操作系统和服务的完全交互主机。蜜罐易于使用,捕获所需的信息,主要用于企业公司保护其网络免受在线黑客和未经授权的用户的攻击。大多数蜜罐都是在防火墙程序中安装和配置的,这样可以更好地控制它们。在本文中,我们提出了向前和向后蚂蚁(群体智能)以及蜜罐的概念,通过遵循预先建立的负载平衡器和入侵检测系统的概念来检测网络入侵。
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Intrusion detection system using honeypots and swarm intelligence
As the number and size of the Network and Internet traffic increase and the need for the intrusion detection grows in step to reduce the overhead required for the intrusion detection and diagnosis, it has made public servers increasingly vulnerable to unauthorized accesses and incursion of intrusions. In addition to maintaining low latency and poor performance for the client, filtering unauthorized accesses has become one of the major concerns of a server administrator. Honeypots are decoy computer resources set up for the purpose of monitoring and logging the activities of entities that probe, attack or compromise them. Activities on honeypots can be considiered suspicious by definition, as there is no point for benign users to interact with these systems. Honeypots come in many shapes and sizes; examples include dummy items in a database, low-interaction network components like preconfigured traffic sinks, or full-interaction hosts with real operating systems and services. Honeypots are easy to use, capture the required information and mainly used by the corporate companies to secure their networks from the online hackers and unauthorized users. Most honeypots are installed and configured inside the firewall programs so that they can be better controlled. In this paper, we are proposing the concept of Forward and Backward Ants (Swarm Intelligence) along with Honeypots to detect the network intrusion by following a pre-established concept of load balancer and Intrusion Detection System.
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