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MTD 2018 : 5th ACM Workshop on Moving Target Defense

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Link: http://csis.gmu.edu/MTD-2018/
 
When Oct 15, 2018 - Oct 19, 2018
Where Toronto, Canada
Submission Deadline Jul 8, 2018
Notification Due Jul 30, 2018
Final Version Due Aug 19, 2018
 

Call For Papers

The static nature of current computing systems has made them easy to attack and hard to defend. Adversaries have an asymmetric advantage in that they have the time to study a system, identify its vulnerabilities, and choose the time and place of attack to gain the maximum benefit. The idea of moving-target defense (MTD) is to impose the same asymmetric disadvantage on attackers by making systems dynamic and therefore harder to explore and predict. With a constantly changing system and its ever-adapting attack surface, attackers will have to deal with significant uncertainty just like defenders do today. The ultimate goal of MTD is to increase the attackers' workload so as to level the cybersecurity playing field for defenders and attackers – ultimately tilting it in favor of the defender.

The workshop seeks to bring together researchers from academia, government, and industry to report on the latest research efforts on moving-target defense, and to have productive discussion and constructive debate on this topic. We solicit submissions on original research in the broad area of MTD, with possible topics such as those listed below. As MTD research is still in its infancy, the list should only be used as a reference. We welcome all contributions that fall under the broad scope of moving target defense, including research that shows negative results.

WORKSHOP TOPICS:
- System randomization
- Artificial diversity
- Cyber maneuver and agility
- Software diversity
- Dynamic network configuration
- Moving target in the cloud
- System diversification techniques
- Dynamic compilation techniques
- Adaptive defenses
- Intelligent countermeasure selection
- MTD strategies and planning
- Deep learning for MTD
- MTD quantification methods and models
- MTD evaluation and assessment frameworks
- Large-scale MTD (using multiple techniques)
- Moving target in software coding, application API virtualization
- Autonomous technologies for MTD
- Theoretic study on modeling trade-offs of using MTD approaches
- Human, social, and usability aspects of MTD
- Other related areas

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