Biblio

P2P botnet has become one of the most serious threats to today's network security. It can be used to launch kinds of malicious activities, ranging from spamming to distributed denial of service attack. However, the detection of P2P botnet is always challenging because of its decentralized architecture. In this paper, we propose a two-stage P2P botnet detection method which only relies on several traffic statistical features. This method first detects P2P hosts based on three statistical features, and then distinguishes P2P bots from benign P2P hosts by means of another two statistical features. Experimental evaluations on real-world traffic datasets shows that our method is able to detect hidden P2P bots with a detection accuracy of 99.7% and a false positive rate of only 0.3% within 5 minutes.

Every so often papers are published presenting a new extension for modelling cyber security requirements in Business Process Model and Notation (BPMN). The frequent production of new extensions by experts belies the need for a richer and more usable representation of security requirements in BPMN processes. In this paper, we present our work considering an analysis of existing extensions and identify the notational issues present within each of them. We discuss how there is yet no single extension which represents a comprehensive range of cyber security concepts. Consequently, there is no adequate solution for accurately specifying cyber security requirements within BPMN. In order to address this, we propose a new framework that can be used to extend, visualise and verify cyber security requirements in not only BPMN, but any other existing modelling language. The framework comprises of the three core roles necessary for the successful development of a security extension. With each of these being further subdivided into the respective components each role must complete.