Finding Needles in a Moving Haystack: Prioritizing Alerts with Adversarial Reinforcement Learning
暂无分享,去创建一个
Liang Tong | Yevgeniy Vorobeychik | Chao Yan | Aron Laszka | Ning Zhang | Aron Laszka | Liang Tong | Chao Yan | Yevgeniy Vorobeychik | Ning Zhang
[1] Yi Wu,et al. Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments , 2017, NIPS.
[2] Tom Schaul,et al. Dueling Network Architectures for Deep Reinforcement Learning , 2015, ICML.
[3] Bo An,et al. A Deployed Quantal Response-Based Patrol Planning System for the U.S. Coast Guard , 2013, Interfaces.
[4] Marc G. Bellemare,et al. A Distributional Perspective on Reinforcement Learning , 2017, ICML.
[5] David Silver,et al. A Unified Game-Theoretic Approach to Multiagent Reinforcement Learning , 2017, NIPS.
[6] Shane Legg,et al. Human-level control through deep reinforcement learning , 2015, Nature.
[7] Bo Li,et al. Get Your Workload in Order: Game Theoretic Prioritization of Database Auditing , 2018, 2018 IEEE 34th International Conference on Data Engineering (ICDE).
[8] Nasser M. Nasrabadi,et al. Pattern Recognition and Machine Learning , 2006, Technometrics.
[9] Neminath Hubballi,et al. False alarm minimization techniques in signature-based intrusion detection systems: A survey , 2014, Comput. Commun..
[10] Yuval Tassa,et al. Continuous control with deep reinforcement learning , 2015, ICLR.
[11] Bo An,et al. Stackelberg Security Games: Looking Beyond a Decade of Success , 2018, IJCAI.
[12] Shane Legg,et al. Noisy Networks for Exploration , 2017, ICLR.
[13] Tom Schaul,et al. Prioritized Experience Replay , 2015, ICLR.
[14] Demis Hassabis,et al. A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play , 2018, Science.
[15] Lantao Yu,et al. Deep Reinforcement Learning for Green Security Games with Real-Time Information , 2018, AAAI.
[16] Quanyan Zhu,et al. Game theory meets network security and privacy , 2013, CSUR.
[17] Michael L. Littman,et al. Markov Games as a Framework for Multi-Agent Reinforcement Learning , 1994, ICML.
[18] Michael P. Wellman,et al. Multiagent Reinforcement Learning: Theoretical Framework and an Algorithm , 1998, ICML.
[19] David Silver,et al. Deep Reinforcement Learning with Double Q-Learning , 2015, AAAI.
[20] Lalu Banoth,et al. A Survey of Data Mining and Machine Learning Methods for Cyber Security Intrusion Detection , 2017 .
[21] Yoshua Bengio,et al. Understanding the difficulty of training deep feedforward neural networks , 2010, AISTATS.
[22] Yuan Yu,et al. TensorFlow: A system for large-scale machine learning , 2016, OSDI.
[23] Milind Tambe,et al. Security Games for Controlling Contagion , 2012, AAAI.
[24] Samuel Kounev,et al. Evaluating Computer Intrusion Detection Systems , 2015, ACM Comput. Surv..
[25] Vincent Conitzer,et al. Stackelberg vs. Nash in Security Games: An Extended Investigation of Interchangeability, Equivalence, and Uniqueness , 2011, J. Artif. Intell. Res..
[26] Peter Dayan,et al. Q-learning , 1992, Machine Learning.
[27] Alex Graves,et al. Asynchronous Methods for Deep Reinforcement Learning , 2016, ICML.
[28] Avrim Blum,et al. Planning in the Presence of Cost Functions Controlled by an Adversary , 2003, ICML.
[29] EMMANOUIL VASILOMANOLAKIS,et al. Taxonomy and Survey of Collaborative Intrusion Detection , 2015, ACM Comput. Surv..
[30] Tom Schaul,et al. Rainbow: Combining Improvements in Deep Reinforcement Learning , 2017, AAAI.
[31] Chris Watkins,et al. Learning from delayed rewards , 1989 .
[32] Gerald Tesauro,et al. TD-Gammon, a Self-Teaching Backgammon Program, Achieves Master-Level Play , 1994, Neural Computation.
[33] Raouf Boutaba,et al. FuzMet: a fuzzy‐logic based alert prioritization engine for intrusion detection systems , 2012, Int. J. Netw. Manag..
[34] Vern Paxson,et al. Outside the Closed World: On Using Machine Learning for Network Intrusion Detection , 2010, 2010 IEEE Symposium on Security and Privacy.
[35] Nicolas Christin,et al. Audit Games , 2013, IJCAI.
[36] Michael P. Wellman,et al. Nash Q-Learning for General-Sum Stochastic Games , 2003, J. Mach. Learn. Res..
[37] Alex Graves,et al. Playing Atari with Deep Reinforcement Learning , 2013, ArXiv.
[38] Jian Sun,et al. Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[39] Michael L. Littman,et al. Friend-or-Foe Q-learning in General-Sum Games , 2001, ICML.
[40] Murat Kantarcioglu,et al. Adversarial Machine Learning , 2018, Adversarial Machine Learning.
[41] Demis Hassabis,et al. Mastering the game of Go with deep neural networks and tree search , 2016, Nature.
[42] Yevgeniy Vorobeychik,et al. A Game-Theoretic Approach for Alert Prioritization , 2017, AAAI Workshops.
[43] Mina Guirguis,et al. Don't Bury your Head in Warnings: A Game-Theoretic Approach for Intelligent Allocation of Cyber-security Alerts , 2017, IJCAI.
[44] Gabriel Maciá-Fernández,et al. A model-based survey of alert correlation techniques , 2013, Comput. Networks.
[45] Nicolas Christin,et al. Audit Games with Multiple Defender Resources , 2014, AAAI.
[46] Ali A. Ghorbani,et al. Toward Generating a New Intrusion Detection Dataset and Intrusion Traffic Characterization , 2018, ICISSP.
[47] David A. Wagner,et al. Detecting Credential Spearphishing in Enterprise Settings , 2017, USENIX Security Symposium.