ITR: Research on the Profiling Problem in Cybersecurity and Anti-Terrorism

该项目旨在研究用于检测和识别恐怖分子和网络攻击的新的和理论上合理的分析技术。此类攻击的一个共同问题是，我们如何快速从好人中发现“坏人”？各种科学技术，如数据建模和集成，元数据管理，离散数学模型和算法，数据挖掘，机器学习，可视化和统计技术将被调查。例如，将开发和测试用于分析“坏人/交易”的新数学模型和算法。一个研究方向是将问题表述为当前集合覆盖问题的更广义的表述。将开发高效的算法，并研究某些算法的性能界限。将进行仿真以比较新算法与传统算法的性能，并确定这些算法的优缺点。将与路易斯安那州立大学国家安全研究与培训中心（NCSRT）、联邦调查局（FBI）、AFRL等机构合作，使模型更加逼真，并针对更真实的数据集测试算法/技术。项目团队由不同的民族组成，并计划组织一个专门针对妇女和代表性不足的少数民族的研讨会，如果成功，该项目将对科学界和社会产生重大影响。

This project proposes to perform research on new and theoretically sound profiling techniques for detection and identification of terrorists and cyber attacks. A common thread of problems in such attacks is how can we detect "bad guys" from good guys quickly? Various scientific techniques such as data modeling and integration, meta-data management, discrete mathematical models and algorithms, data mining, machine learning, visualization and statistical techniques will be investigated. For example, new mathematical models and algorithms for profiling "bad guys/transactions" will be developed and tested. One research direction is to formulate the problem as a more generalized formulation of the current set covering problem. Efficient algorithms will be developed, and performance bounds of certain algorithms will be studied. Simulations will be done to compare the performance of the new algorithms with conventional algorithms, and the pros and cons of these algorithms will be identified.Making the models more realistic and testing the algorithms/techniques against more realistic data sets will be done by teaming with LSU's National Center for Security Research and Training (NCSRT) , FBI, AFRL, and others. The project team consists of diverse ethnic groups and plans to organize a workshop dedicated to women and under-represented minority..If successful, this project can have significant impact on the scientific community and on the society.