| Title | Demystifying the Cyber Attribution: An Exploratory Study |
| Publication Type | Conference Paper |
| Year of Publication | 2020 |
| Authors | Jaafar, Fehmi, Avellaneda, Florent, Alikacem, El-Hackemi |
| Conference Name | 2020 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech) |
| Keywords | attack patterns, attribution, composability, Cyber Attacks, Cyber attributtions, Data analysis, face recognition, Human Behavior, Information systems, machine learning, machine learning algorithms, metadata, Metrics, pubcrawl, Regulation, Tools |
| Abstract | 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. |
| DOI | 10.1109/DASC-PICom-CBDCom-CyberSciTech49142.2020.00022 |
| Citation Key | jaafar_demystifying_2020 |
Demystifying the Cyber Attribution: An Exploratory Study