TO Overcome UDP Flooding Attacks in IP Multimedia Subsystem (NGN) using the Genetic Intrusion Detection Systems (IDS)

Generation Partnership Project to provide the access networks services and telecommunication services, plans to merge services like multimedia, data and voice conversation under one umbrella. In this research, network based anomaly detection system is proposed by using Genetic Algorithm rules to avoid such attacks like UDP Flooding which cause the DoS and DDoS attacks keeping in view to secure the IMS and also discussed the complete overview of IMS (NGN) based network architecture, their DoS and DDoS attacks which cause the unavailability of services to the users.IMS inherits many security issues because the billions users are in the form to interact with IMS to get large No of services like multimedia, data or voice conversation. Due the large usage of IMS services there is also the availability of malicious user to attack the IMS services and make the services unavailable for the intended user, which reduces the performance of IMS. IMS based abnormality detection method is proposed using GA as abnormality detector. Genetic Intrusion Detection system effectively detects intrusive attack in IMS system and shows low false positive results.

生成伙伴项目（Generation Partnership Project）计划提供接入网服务与电信服务，并将多媒体、数据与语音通话等服务整合为统一服务体系。本研究提出了一种基于遗传算法（Genetic Algorithm, GA）规则的网络异常检测系统，以抵御UDP泛洪等会引发拒绝服务（Denial of Service, DoS）与分布式拒绝服务（Distributed Denial of Service, DDoS）攻击的行为，旨在保障IP多媒体子系统（IP Multimedia Subsystem, IMS）的安全；同时还完整阐述了基于下一代网络（Next Generation Network, NGN）的IMS网络架构，以及会导致用户无法获取服务的DoS与DDoS攻击的全貌。IMS面向数十亿用户提供多媒体、数据或语音通话等海量服务，因此存在诸多安全隐患。随着IMS服务使用量的激增，恶意用户可借机攻击IMS服务，致使目标用户无法正常使用服务，进而降低IMS的整体性能。本研究提出了一种基于GA的IMS异常检测方法。基于遗传算法的入侵检测系统可有效检测IMS系统中的入侵攻击，且误报率较低。