We are currently experiencing an exponential growth in using advanced cybertechnologies and the amount of data being generated. We are generating around 2.5 quintillion bytes of data every day, which means more than 90% of world data has been created in the last two years alone. With this huge amount of data, that we refer to as Big Data, many challenges and opportunities arise due to the size, heterogeneity, dynamism, and the speed at which this data generated. As we continue to rely on cyber technology and its services, we are facing with the increased risk of cybercrime, cyberterrorism, cyberespionage, and advanced persistent threats where bad actors are rapidly improving their attack techniques and their speed in launching these attacks. In the past, the attackers go through at least three phases before they launch their attacks (probing, constructing and launching attacks). Now, bad actors go directly to launch their attacks in one phase. Furthermore, the number of hackers and attacks are increasing rapidly more than ever before. Cybersecurity analytics for big data with its huge amount of data and its sheer breadth and coverage can provide unprecedented cybersecurity capabilities to proactively monitor, analyze, and mitigate sophisticated and advanced cybersecurity threats and exploitations.

We aim developing and deploying the big data cybersecurity analytics to enable NETCOM analysts to integrate and correlate internal events, external events, and all alerts generated from existing cyber monitoring and security tools to obtain full visibility of potential threats against their cyberinfrastructures and their services.

The goal of this workshop is to address innovative techniques, metrics, and behavior analysis that can exploit big data analytics capabilities to address the cybersecurity challenges facing cyberspace resources and services.

Topics of interest include, but are not limited to:
* Big Data Theory for Cyber Security
- Metrics,
-Data Aggregation and Correlations of big data sensors
* Big Data Visualization for Cybersecurity
- Full visibility into the behavior of cyberspace resources and services
- Knowledge representation and visualization of behavior of autonomic systems and services
* Big Data Cybersecurity Computational Models
- Map/Reduce
- Data Streaming
- Parallel/Distributed Algorithms
* Anomaly Behavior Analysis
- Data mining, stochastic analysis and prediction
- Advanced Persistent Threat (APT) modeling and analysis
- Sensor data collectors
- Data Science and Analytics in Security Informatics
* Human Behavior and Factors in the Security Applications
- Privacy, security, trust, and risk in big data
- Data integrity, matching, and sharing
- Social impact


SUBMISSION AND PUBLICATION

The papers must be formatted in a two-column layout up to 6 pages and must follow the IEEE proceedings format. All manuscripts will be reviewed and judged on merits including originality, significance, interest, correctness, clarity, and relevance to the broader community. Submitted papers must include original work and may not be under consideration for another workshop, conference or journal during the IWBDAC 2016 review process.

Authors should submit their papers electronically following the instructions from the ISI 2016 conference web site (http://www.isi-conf.org/). At least one author for each of the accepted papers is expected to present their work at the workshop.
The accepted papers from IWBDAC 2016, ISI 2016 and its affiliated workshops will be published by the IEEE Press in formal Proceedings. IEEE ISI Proceedings are EI-indexed.

IMPORTANT DATES

Full paper submission: May 16, 2016
Author notification: July 1, 2016
Camera-ready version due: July 10, 2016