Signal processing techniques have been applied recently for analyzing and detecting network anomalies due to their potential to find novel or unknown intrusions. In this paper, we...
Computer security systems protect computers and networks from unauthorized use by external agents and insiders. The similarities between computer security and the problem of prote...
Stephanie Forrest, Steven A. Hofmeyr, Anil Somayaj...
The value of an intrusion detection sensor is often associated with its data collection and analysis features. Experience tells us such sensors fall under a range of different typ...
Siraj A. Shaikh, Howard Chivers, Philip Nobles, Jo...
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. Intrusion detection has been extensively studied in the last two decades. However, most existing intrusion detection techniques detect limited number of attack types and ...
Abstract. Flow-based intrusion detection has recently become a promising security mechanism in high speed networks (1-10 Gbps). Despite the richness in contributions in this field...
Anna Sperotto, Ramin Sadre, Frank van Vliet, Aiko ...
In this paper we present our original methodology, in which Matching Pursuit is used for networks anomaly and intrusion detection. The architecture of anomaly-based IDS based on si...
Lukasz Saganowski, Michal Choras, Rafal Renk, Wito...
As an immune inspired algorithm, the Dendritic Cell Algorithm (DCA) has been applied to a range of problems, particularly in the area of intrusion detection. Ideally, the intrusio...
Due to the increasing demands for network security, distributed intrusion detection has become a hot research topic in computer science. However, the design and maintenance of the...
Data mining for intrusion detection can be divided into several sub-topics, among which unsupervised clustering has controversial properties. Unsupervised clustering for intrusion...