A low-effort data mining approach to labeling network event records in a WLAN is proposed. The problem being addressed is often observed in an AI and data mining strategy to netwo...
Taghi M. Khoshgoftaar, Chris Seiffert, Naeem Seliy...
Abstract. We propose a novel framework of autonomic intrusion detection that fulfills online and adaptive intrusion detection in unlabeled audit data streams. The framework owns a...
Abstract— In this paper, we consider the problem of detecting intrusions initiated by cooperative malicious nodes in infrastructure-based networks. We achieve this objective by s...
Mona Mehrandish, Hadi Otrok, Mourad Debbabi, Chadi...
Abstract. Data mining, which aims at extracting interesting information from large collections of data, has been widely used as an effective decision making tool. Mining the datas...
The popularity of computer networks broadens the scope for network attackers and increases the damage these attacks can cause. In this context, Intrusion Detection Systems (IDS) a...