MIT Golub Center for Finance and Policy
Public Policy
Dr. Jeremy Kepner’s Seminar “Percolation Model of Insider Threats to Assess the Optimum Number of Rules”
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Percolation Model of Insider Threats to Assess the Optimum Number of Rules
In a special seminar co-hosted by the MIT Center for Finance and Policy (CFP) and the MIT Laboratory for Financial Engineering (LFE), Dr. Jeremy Kepner, senior scientist at the MIT Lincoln Laboratory, will present “Percolation Model of Insider Threats to Assess the Optimum Number of Rules.” The seminar will take place on Wednesday, April 22 from 12:00-1:00pm in E62.450. Lunch will be served.
- DATE: Wednesday, April 22nd, 2015
- TIME: 12 pm- 1 pm
- LOCATION: E62-450
Open to the MIT community. Lunch will be served. Co-hosted by the MIT Center for Finance and Policy (CFP) and the MIT Laboratory for Financial Engineering (LFE)
Paper available at http://arxiv.org/abs/1412.8699.
Abstract
Rules, regulations, and policies are the basis of civilized society and are used to coordinate the activities of individuals who have a variety of goals and purposes. History has taught that over-regulation (too many rules) makes it difficult to compete and under-regulation (too few rules) can lead to crisis. This implies an optimal number of rules that avoids these two extremes. Rules create boundaries that define the latitude an individual has to perform their activities. This paper creates a Toy Model of a work environment and examines it with respect to the latitude provided to a normal individual and the latitude provided to an insider threat. Simulations with the Toy Model illustrate four regimes with respect to an insider threat: under-regulated, possibly optimal, tipping-point, and over-regulated. These regimes depend up the number of rules (N) and the minimum latitude (Lmin) required by a normal individual to carry out their activities. The Toy Model is then mapped onto the standard 1D Percolation Model from theoretical physics and the same behavior is observed. This allows the Toy Model to be generalized to a wide array of more complex models that have been well studied by the theoretical physics community and also show the same behavior. Finally, by estimating N and Lmin it should be possible to determine the regime of any particular environment.
Bio
Dr. Kepner leads large scale computing research across MIT’s largest laboratory. Dr. Kepner is the most published author in the 60+ year history of Lincoln Laboratory. His published works span signal processing, data mining, databases, high performance computing, graph algorithms, cyber security, visualization, cloud computing, random matrix theory, abstract algebra, bioinformatics, astronomy, physics, and astrophysics. In addition he has authored two books on parallel computing and graph algorithms. He recently received Lincoln’s highest honor for technical excellence “For his leadership and vision in bringing supercomputing to Lincoln Laboratory through the establishment of LLGrid; his pivotal role in open systems for embedded computing; his creativity in developing a novel database management language and schema; and his contributions to the field of graph analytics.” More recently, Dr. Kepner has been at the forefront of developing new signal processing technique for genetic sequence analysis and operating on data while it is stored in encrypted form. Dr. Kepner is the Chair of the largest computing conference in New England (IEEE High Performance Extreme Computing) and Vice-Chair of SIAM Data Mining. Dr. Kepner received his Ph.D. in Astrophysics from Princeton University in 1998.
