A Review-Botnet Detection and Suppression in Clouds

Internet security problems remain a major challenge with many security concerns such as Internet worms, spam, and phishing attacks. Botnets is well-organized distributed network attacks, consist of a large number of bots that generate huge volumes of spam or launch Distributed Denial of Service (DDoS) attacks on victim hosts. Botnet attacks degrade the status of Internet security. Clouds provide botmaster with an ideal environment of rich computing resources where it can easily deploy or remove C&C server and perform attacks.  It is of vital importance for cloud service providers to detect botnet,  prevent attack,  and trace back to the botmaster.  It also becomes necessary to detect and suppress these bots to protect the clouds. This paper provides the various botnet detection techniques and the comparison of various botnet detection techniques. It also provides the botnet suppression technique in cloud. Keywords: Cloud computing, network security, botnet, botmmaster, botnet detection, botnet suppressio

Design and implementation of an extrusion-based break-in detector for personal computers

An increasing variety of malware, such as worms, spyware and adware, threatens both personal and business computing. Remotely controlled bot networks of compromised systems are growing quickly. In this paper, we tackle the problem of automated detection of break-ins caused by unknown malware targeting personal computers. We develop a host based system, BINDER (Break-IN DEtectoR), to detect break-ins by capturing user unintended malicious outbound connections (referred to as extrusions). To infer user intent, BINDER correlates outbound connections with user-driven input at the process level under the assumption that user intent is implied by user-driven input. Thus BINDER can detect a large class of unknown malware such as worms, spyware and adware without requiring signatures. We have successfully used BINDER to detect real world spyware on daily used computers and email worms on a controlled testbed with very small false positives