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MTD 2015 : 2nd ACM Workshop on Moving Target Defense | |||||||||||||||
Link: http://mtd.mobicloud.asu.edu | |||||||||||||||
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Call For Papers | |||||||||||||||
Background
---------- The static nature of current computing systems has made them easy to attack and harder 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 a great deal of 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 both defenders and attackers - hopefully even tilting it in favor of the defender. Workshop Goals -------------- This 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. Since MTD research is still in its nascent stage, the list should only be used as a reference. We welcome all works that fall under the broad scope of moving target defense, including research that shows negative results. Below are examples of appropriate topics for MTD 2015: + MTD Techniques - System randomization - Artificial diversity and system diversification - Bio-inspired MTDs - Dynamic network configuration - Cloud-based and Large-scale MTDs (using multiple techniques) - Autonomous technologies for MTD - Dynamic compilation - Moving targets in software coding, application APIs and virtualization + MTD Modeling and Analysis - Analytical models for MTDs - Quantitative models and effective measurement of MTDs - Theoretic study on modeling trade-offs of using MTD approaches - Control and game theory aspects of deploying MTDs - Human, social, and psychology aspects of MTD - Other related MTD areas Paper submissions ----------------- Submitted papers must not substantially overlap papers that have been published or that are simultaneously submitted to a journal or a conference with proceedings. Submissions should be at most 10 pages in the ACM double-column format, excluding well-marked appendices, and at most 12 pages in total. Submissions are not required to be anonymized. Submissions are to be made by June 8, 2015 through http://www.easychair.org/conferences/?conf=mtd2015. Only PDF files will be accepted. Submissions not meeting these guidelines risk rejection without consideration of their merits. Authors of accepted papers must guarantee that one of the authors will register and present the paper at the workshop. Proceedings of the workshop will be available on a CD to the workshop attendees and will become part of the ACM Digital Library. TPC Co-Chairs ------------- George Cybenko, Dartmouth College, USA Dijiang Huang, Arizona State University, USA Publicity Chair --------------- Massimiliano Albanese, George Mason University Important dates --------------- Paper submission due: June 8, 2015 Notification to authors: July 19, 2015 Camera ready due: July 29, 2015 Workshop dates: October 12, 2015 Program Committee ----------------- Gail-Joon Ahn, Arizona State University Ehab Al-Shaer, University of North Carolina Charlotte Massimiliano Albanese, George Mason University Hasan Cam, Army Research Lab Marco Carvalho, Florida Institute of Technology Scott DeLoach, Kansas State University Yuval Elovici, Ben-Gurion University of the Negev Rob Erbacher, Army Research Lab Michael Franz, University of California, Irvine Robert Gray, BAE Systems Jason R. Hamlet, Sandia Lab Sushil Jajodia, George Mason University Myong Kang, Naval Research Lab Angelos Keromytis, Columbia University Christopher Charles Lamb, Sandia Lab Jason Li, Intelligent Automation, Inc. (IAI) Peng Liu, Penn State University Tom Longstaff, John Hopkins University Lisa Marvel, Amy Research Lab Patrick McDaniel, Penn State University Prasant Mohapatra, UC Davis Sanjai Narain, Applied Communication Sciences Hamed Okhravi, MIT Lincoln Laboratory Xinming Ou, Kansas State University Radha Poovendran, University of Washington Kui Ren, University at Buffalo Kun Sun, College of William and Mary Vipin Swarup, MITRE Jason Syversen, Siege Technologies Cliff Wang, Army Research Office |
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