Biblio

Current cyber attribution approaches proposed to use a variety of datasets and analytical techniques to distill the information that will be useful to identify cyber attackers. In contrast, practitioners and researchers in cyber attribution face several technical and regulation challenges. In this paper, we describe the main challenges of cyber attribution and present a state of the art of used approaches to face these challenges. Then, we will present an exploratory study to perform cyber attacks attribution based on pattern recognition from real data. In our study, we are using attack pattern discovery and identification based on real data collection and analysis.

A cyber attack is a malicious and deliberate attempt by an individual or organization to breach the integrity, confidentiality, and/or availability of data or services of an information system of another individual or organization. Being able to attribute a cyber attack is a crucial question for security but this question is also known to be a difficult problem. The main reason why there is currently no solution that automatically identifies the initiator of an attack is that attackers usually use proxies, i.e. an intermediate node that relays a host over the network. In this paper, we propose to formalize the problem of identifying the initiator of a cyber attack. We show that if the attack scenario used by the attacker is known, then we are able to resolve the cyber attribution problem. Indeed, we propose a model to formalize these attack scenarios, that we call attack patterns, and give an efficient algorithm to search for attack pattern on a communication history. Finally, we experimentally show the relevance of our approach.