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活动简介

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.

征稿信息

重要日期

2017-04-10
初稿截稿日期
2017-04-27
初稿录用日期

征稿范围

 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

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重要日期
  • 会议日期

    06月26日

    2017

    06月29日

    2017

  • 04月10日 2017

    初稿截稿日期

  • 04月27日 2017

    初稿录用通知日期

  • 06月29日 2017

    注册截止日期

主办单位
University of Illinois
承办单位
中国科学院信息工程研究所
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