As the development of cyber technologies, the risk of cybercrime, cyberespionage, cyberterrorism, and advanced persistent threats is also increasing greatly. In particular, the attack techniques as well as the speed in launching these attacks are rapidly improving. As both volume and complexity of malware attacks increase, traditional analytic tooling and infrastructure have become difficult to keep up. Big data analytics are being developed as a promising way to address these challenges. Due to the characteristics of big data, such as huge amount of data and sheer breadth and coverage, Cybersecurity analytics for big data can provide unprecedented cybersecurity capabilities to proactively monitor, analyze, and mitigate sophisticated and advanced cybersecurity threats and exploitations. This workshop aims to exploit big data analytics capabilities including innovative techniques, metrics, and behavior analysis to address the cybersecurity challenges. Contributions that push the state of the art in all facets of big data cybersecurity analytics are encouraged and welcomed.
Topics of interest include but not limited to:
1.Big data theory for cybersecurity
2.Data aggregation and correlations of big data sensors
3.Big data visualization for cybersecurity
4.Knowledge representation and visualization of behavior of autonomic systems and services
5.Big data cybersecurity computational models
6.Data mining, stochastic analysis and prediction
7.Advanced Persistent Threat (APT) modeling and analysis
8.Data Science and Analytics in Security Informatics
9.Privacy, security, trust, and risk in big data
10.Data integrity, matching, and sharing
06月26日
2017
06月29日
2017
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