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ORCIDArunesh Sinha
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- affiliation: Rutgers University, NJ, USA
- affiliation (former): Singapore Management University, Singapore
- affiliation (former): University of Southern California, CA, USA
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2020 – today
- 2025
[e7]Arunesh Sinha
, Jie Fu, Quanyan Zhu, Tao Zhang:
Decision and Game Theory for Security - 15th International Conference, GameSec 2024, New York City, NY, USA, October 16-18, 2024, Proceedings. Lecture Notes in Computer Science 14908, Springer 2025, ISBN 978-3-031-74834-9 [contents]- 2024
- [j9]Hai Truong, Dheryta Jaisinghani, Shubham Jain, Arunesh Sinha, JeongGil Ko, Rajesh Balan:
Tracking people across ultra populated indoor spaces by matching unreliable Wi-Fi signals with disconnected video feeds. Pervasive Mob. Comput. 97: 101860 (2024) - [c67]Yuxiao Lu, Arunesh Sinha, Pradeep Varakantham:
Handling Long and Richly Constrained Tasks through Constrained Hierarchical Reinforcement Learning. AAAI 2024: 21368-21377 - [c66]Tien Mai, Avinandan Bose, Arunesh Sinha, Thanh Hong Nguyen, Ayushman Kumar singh:
Tackling Stackelberg Network Interdiction against a Boundedly Rational Adversary. IJCAI 2024: 2913-2921 - [c65]Chen Gong, Zhou Yang, Yunpeng Bai, Junda He, Jieke Shi, Kecen Li, Arunesh Sinha, Bowen Xu, Xinwen Hou, David Lo, Tianhao Wang:
Baffle: Hiding Backdoors in Offline Reinforcement Learning Datasets. SP 2024: 2086-2104 - [e6]Francesco Amigoni, Arunesh Sinha:
Autonomous Agents and Multiagent Systems. Best and Visionary Papers - AAMAS 2023 Workshops, London, UK, May 29 - June 2, 2023, Revised Selected Papers. Lecture Notes in Computer Science 14456, Springer 2024, ISBN 978-3-031-56254-9 [contents] - [i31]Roman Belaire, Arunesh Sinha, Pradeep Varakantham:
Probabilistic Perspectives on Error Minimization in Adversarial Reinforcement Learning. CoRR abs/2406.04724 (2024) - [i30]Changyu Chen, Zichen Liu, Chao Du, Tianyu Pang, Qian Liu, Arunesh Sinha, Pradeep Varakantham, Min Lin:
Bootstrapping Language Models with DPO Implicit Rewards. CoRR abs/2406.09760 (2024) - [i29]Changyu Chen, Shashank Reddy Chirra, Maria José Ferreira, Cleotilde Gonzalez, Arunesh Sinha, Pradeep Varakantham:
Towards Neural Network based Cognitive Models of Dynamic Decision-Making by Humans. CoRR abs/2407.17622 (2024) - [i28]Hritaban Ghosh, Changyu Chen, Arunesh Sinha, Shamik Sural:
Heterogeneous Graph Generation: A Hierarchical Approach using Node Feature Pooling. CoRR abs/2410.11972 (2024) - 2023
- [c64]Tien Mai, Arunesh Sinha:
Securing Lifelines: Safe Delivery of Critical Services in Areas with Volatile Security Situation via a Stackelberg Game Approach. AAAI 2023: 5805-5813 - [c63]Thanh Hong Nguyen, Arunesh Sinha:
Behavioral Learning in Security Games: Threat of Multi-Step Manipulative Attacks. AAAI 2023: 9302-9309 - [c62]Avinandan Bose, Tracey Li, Arunesh Sinha, Tien Mai:
A Fair Incentive Scheme for Community Health Workers. AAAI 2023: 14127-14135 - [c61]Wai Tuck Wong, Sarah Eve Kinsey, Ramesha Karunasena, Thanh Hong Nguyen, Arunesh Sinha:
Beyond NaN: Resiliency of Optimization Layers in the Face of Infeasibility. AAAI 2023: 15242-15250 - [c60]Sonja Johnson-Yu, Jessie Finocchiaro, Kai Wang, Yevgeniy Vorobeychik, Arunesh Sinha, Aparna Taneja, Milind Tambe:
Characterizing and Improving the Robustness of Predict-Then-Optimize Frameworks. GameSec 2023: 133-152 - [c59]Sarah Eve Kinsey, Jack Wolf, Nalini Saligram, Varun Ramesan, Meeta Walavalkar, Nidhi Jaswal, Sandhya Ramalingam, Arunesh Sinha, Thanh Hong Nguyen:
Building a Personalized Messaging System for Health Intervention in Underprivileged Regions Using Reinforcement Learning. IJCAI 2023: 6022-6030 - [c58]Changyu Chen, Ramesha Karunasena, Thanh Hong Nguyen, Arunesh Sinha, Pradeep Varakantham:
Generative Modelling of Stochastic Actions with Arbitrary Constraints in Reinforcement Learning. NeurIPS 2023 - [i27]Tien Mai, Avinandan Bose, Arunesh Sinha, Thanh Hong Nguyen:
Tackling Stackelberg Network Interdiction against a Boundedly Rational Adversary. CoRR abs/2301.12232 (2023) - [i26]Yuxiao Lu, Pradeep Varakantham, Arunesh Sinha:
Conditioning Hierarchical Reinforcement Learning on Flexible Constraints. CoRR abs/2302.10639 (2023) - [i25]Changyu Chen, Ramesha Karunasena, Thanh Hong Nguyen, Arunesh Sinha, Pradeep Varakantham:
Generative Modelling of Stochastic Actions with Arbitrary Constraints in Reinforcement Learning. CoRR abs/2311.15341 (2023) - 2022
- [c57]Tien Mai, Arunesh Sinha:
Choices Are Not Independent: Stackelberg Security Games with Nested Quantal Response Models. AAAI 2022: 5141-5149 - [c56]Changyu Chen, Avinandan Bose, Shih-Fen Cheng, Arunesh Sinha:
Multiscale Generative Models: Improving Performance of a Generative Model Using Feedback from Other Dependent Generative Models. AAAI 2022: 6193-6201 - [c55]Chen Gong, Zhou Yang, Yunpeng Bai, Jieke Shi, Arunesh Sinha, Bowen Xu, David Lo, Xinwen Hou, Guoliang Fan:
Curiosity-Driven and Victim-Aware Adversarial Policies. ACSAC 2022: 186-200 - [c54]Arunesh Sinha:
AI and Security: A Game Perspective. COMSNETS 2022: 393-396 - [c53]Chaithanya Basrur, Arambam James Singh, Arunesh Sinha, Akshat Kumar, T. K. Satish Kumar:
Trajectory Optimization for Safe Navigation in Maritime Traffic Using Historical Data. CP 2022: 5:1-5:17 - [c52]Sarah Eve Kinsey, Wong Wai Tuck, Arunesh Sinha, Thanh Hong Nguyen:
An Exploration of Poisoning Attacks on Data-Based Decision Making. GameSec 2022: 231-252 - [c51]Avinandan Bose, Arunesh Sinha, Tien Mai:
Scalable Distributional Robustness in a Class of Non-Convex Optimization with Guarantees. NeurIPS 2022 - [i24]Changyu Chen, Avinandan Bose, Shih-Fen Cheng, Arunesh Sinha:
Multiscale Generative Models: Improving Performance of a Generative Model Using Feedback from Other Dependent Generative Models. CoRR abs/2201.09644 (2022) - [i23]Wai Tuck Wong, Andrew Butler, Ramesha Karunasena, Thanh Hong Nguyen, Arunesh Sinha:
Beyond NaN: Resiliency of Optimization Layers in The Face of Infeasibility. CoRR abs/2202.06242 (2022) - [i22]Thanh Hong Nguyen, Arunesh Sinha:
The Art of Manipulation: Threat of Multi-Step Manipulative Attacks in Security Games. CoRR abs/2202.13424 (2022) - [i21]James Holt, Edward Raff, Ahmad Ridley, Dennis Ross, Arunesh Sinha, Diane Staheli, William Streilen, Milind Tambe, Yevgeniy Vorobeychik, Allan B. Wollaber:
Artificial Intelligence for Cyber Security (AICS). CoRR abs/2202.14010 (2022) - [i20]Tien Mai, Arunesh Sinha:
Safe Delivery of Critical Services in Areas with Volatile Security Situation via a Stackelberg Game Approach. CoRR abs/2204.11451 (2022) - [i19]Avinandan Bose, Arunesh Sinha, Tien Mai:
Scalable Distributional Robustness in a Class of Non Convex Optimization with Guarantees. CoRR abs/2205.15624 (2022) - [i18]Chen Gong, Zhou Yang, Yunpeng Bai, Junda He, Jieke Shi, Arunesh Sinha, Bowen Xu, Xinwen Hou, Guoliang Fan, David Lo:
Mind Your Data! Hiding Backdoors in Offline Reinforcement Learning Datasets. CoRR abs/2210.04688 (2022) - 2021
- [c50]Chaithanya Basrur, Arambam James Singh, Arunesh Sinha, Akshat Kumar:
Ship-GAN: Generative Modeling Based Maritime Traffic Simulator. AAMAS 2021: 1755-1757 - [c49]Ramesha Karunasena, Mohammad Sarparajul Ambiya, Arunesh Sinha, Ruchit Nagar, Saachi Dalal, Hamid Abdullah, Divy Thakkar, Dhyanesh Narayanan, Milind Tambe:
Measuring Data Collection Diligence for Community Healthcare. EAAMO 2021: 10:1-10:12 - [c48]Andrew R. Butler, Thanh Hong Nguyen, Arunesh Sinha:
Countering Attacker Data Manipulation in Security Games. GameSec 2021: 59-79 - [c47]Yongzhao Wang, Arunesh Sinha, Sky CH-Wang, Michael P. Wellman:
Building Action Sets in a Deep Reinforcement Learner. ICMLA 2021: 484-489 - [e5]Branislav Bosanský, Cleotilde Gonzalez, Stefan Rass, Arunesh Sinha:
Decision and Game Theory for Security - 12th International Conference, GameSec 2021, Virtual Event, October 25-27, 2021, Proceedings. Lecture Notes in Computer Science 13061, Springer 2021, ISBN 978-3-030-90369-5 [contents] - 2020
- [j8]Andrew Perrault, Fei Fang, Arunesh Sinha, Milind Tambe:
Artificial Intelligence for Social Impact: Learning and Planning in the Data-to-Deployment Pipeline. AI Mag. 41(4): 3-16 (2020) - [j7]Ankit Shah, Arunesh Sinha, Rajesh Ganesan, Sushil Jajodia, Hasan Cam:
Two Can Play That Game: An Adversarial Evaluation of a Cyber-Alert Inspection System. ACM Trans. Intell. Syst. Technol. 11(3): 32:1-32:20 (2020) - [c46]Junyi Li, Xintong Wang, Yaoyang Lin, Arunesh Sinha, Michael P. Wellman:
Generating Realistic Stock Market Order Streams. AAAI 2020: 727-734 - [c45]Sanket Shah, Arunesh Sinha, Pradeep Varakantham, Andrew Perrault, Milind Tambe:
Solving Online Threat Screening Games using Constrained Action Space Reinforcement Learning. AAAI 2020: 2226-2235 - [c44]Steven Jecmen, Arunesh Sinha, Zun Li, Long Tran-Thanh:
Bounding Regret in Empirical Games. AAAI 2020: 4280-4287 - [c43]Han-Ching Ou, Arunesh Sinha, Sze-Chuan Suen, Andrew Perrault, Alpan Raval, Milind Tambe:
Who and When to Screen: Multi-Round Active Screening for Network Recurrent Infectious Diseases Under Uncertainty. AAMAS 2020: 992-1000 - [c42]Thanh Hong Nguyen, Arunesh Sinha, He He:
Partial Adversarial Behavior Deception in Security Games. IJCAI 2020: 283-289 - [i17]Andrew Perrault, Fei Fang, Arunesh Sinha, Milind Tambe:
AI for Social Impact: Learning and Planning in the Data-to-Deployment Pipeline. CoRR abs/2001.00088 (2020) - [i16]Dennis Ross, Arunesh Sinha, Diane Staheli, Bill Streilein:
Proceedings of the Artificial Intelligence for Cyber Security (AICS) Workshop 2020. CoRR abs/2002.08320 (2020) - [i15]Junyi Li, Xintong Wang, Yaoyang Lin, Arunesh Sinha, Michael P. Wellman:
Generating Realistic Stock Market Order Streams. CoRR abs/2006.04212 (2020) - [i14]Ramesha Karunasena, Mohammad Sarparajul Ambiya, Arunesh Sinha, Ruchit Nagar, Saachi Dalal, Divy Thakkar, Milind Tambe:
Measuring Data Collection Quality for Community Healthcare. CoRR abs/2011.02962 (2020)
2010 – 2019
- 2019
- [c41]Thanh Hong Nguyen, Yongzhao Wang, Arunesh Sinha, Michael P. Wellman:
Deception in Finitely Repeated Security Games. AAAI 2019: 2133-2140 - [c40]Arunesh Sinha, Michael P. Wellman:
Incentivizing Collaboration in a Competition. AAMAS 2019: 556-564 - [c39]Parinaz Naghizadeh, Arunesh Sinha:
Adversarial Contract Design for Private Data Commercialization. EC 2019: 681-699 - [i13]Han-Ching Ou, Arunesh Sinha, Sze-Chuan Suen, Andrew Perrault, Milind Tambe:
Who and When to Screen: Multi-Round Active Screening for Recurrent Infectious Diseases Under Uncertainty. CoRR abs/1903.06113 (2019) - [i12]Sanket Shah, Arunesh Sinha, Pradeep Varakantham, Andrew Perrault, Milind Tambe:
Solving Online Threat Screening Games using Constrained Action Space Reinforcement Learning. CoRR abs/1911.08799 (2019) - 2018
- [j6]Bruno Bouchard, Kevin Bouchard, Noam Brown, Niyati Chhaya, Eitan Farchi, Sébastien Gaboury, Christopher W. Geib, Amelie Gyrard, Kokil Jaidka, Sarah Keren, Roni Khardon, Parisa Kordjamshidi, David R. Martinez, Nicholas Mattei, Martin Michalowski, Reuth Mirsky, Joseph C. Osborn, Cem Sahin, Onn Shehory, Arash Shaban-Nejad, Amit P. Sheth, Ilan Shimshoni, Howard E. Shrobe, Arunesh Sinha, Atanu R. Sinha, Biplav Srivastava, William W. Streilein, Georgios Theocharous, Kristen Brent Venable, Neal Wagner, Anna Zamansky:
Reports of the Workshops of the 32nd AAAI Conference on Artificial Intelligence. AI Mag. 39(4): 45-56 (2018) - [c38]Thanh Hong Nguyen, Michael P. Wellman, Arunesh Sinha:
Deceitful Attacks in Security Games. AAAI Workshops 2018: 260-267 - [c37]Nicolas Papernot, Patrick D. McDaniel, Arunesh Sinha, Michael P. Wellman:
SoK: Security and Privacy in Machine Learning. EuroS&P 2018: 399-414 - [c36]Arunesh Sinha, Aaron Schlenker, Donnabell Dmello, Milind Tambe:
Scaling-Up Stackelberg Security Games Applications Using Approximations. GameSec 2018: 432-452 - [c35]Linh Nguyen, Sky Wang, Arunesh Sinha:
A Learning and Masking Approach to Secure Learning. GameSec 2018: 453-464 - [c34]Sara Marie McCarthy, Corine M. Laan, Kai Wang, Phebe Vayanos, Arunesh Sinha, Milind Tambe:
The Price of Usability: Designing Operationalizable Strategies for Security Games. IJCAI 2018: 454-460 - [c33]Arunesh Sinha, Fei Fang, Bo An, Christopher Kiekintveld, Milind Tambe:
Stackelberg Security Games: Looking Beyond a Decade of Success. IJCAI 2018: 5494-5501 - [i11]Ankit Shah, Arunesh Sinha, Rajesh Ganesan, Sushil Jajodia, Hasan Cam:
Two Can Play That Game: An Adversarial Evaluation of a Cyber-alert Inspection System. CoRR abs/1810.05921 (2018) - [i10]Parinaz Naghizadeh, Arunesh Sinha:
Adversarial Contract Design for Private Data Commercialization. CoRR abs/1810.07608 (2018) - 2017
- [j5]Monica Anderson, Roman Barták, John S. Brownstein, David L. Buckeridge, Hoda Eldardiry, Christopher W. Geib, Maria L. Gini, Aaron Isaksen, Sarah Keren, Robert Laddaga, Viliam Lisý, Rodney Martin, David R. Martinez, Martin Michalowski, Loizos Michael, Reuth Mirsky, Thanh Hai Nguyen, Michael J. Paul, Enrico Pontelli, Scott Sanner, Arash Shaban-Nejad, Arunesh Sinha, Shirin Sohrabi, Kumar Sricharan, Biplav Srivastava, Mark Stefik, William W. Streilein, Nathan R. Sturtevant, Kartik Talamadupula, Michael Thielscher, Julian Togelius, Tran Cao Son, Long Tran-Thanh, Neal Wagner, Byron C. Wallace, Szymon Wilk, Jichen Zhu:
Reports of the Workshops of the Thirty-First AAAI Conference on Artificial Intelligence. AI Mag. 38(3): 72-82 (2017) - [j4]Fei Fang, Thanh Hong Nguyen, Arunesh Sinha, Shahrzad Gholami, Andrew J. Plumptre, Lucas Joppa, Milind Tambe, Margaret Driciru, Fred Wanyama, Aggrey Rwetsiba, Rob Critchlow, Colin M. Beale:
Predicting poaching for wildlife Protection. IBM J. Res. Dev. 61(6): 3:1-3:12 (2017) - [c32]Battista Biggio, David Freeman, Brad Miller, Arunesh Sinha:
10th International Workshop on Artificial Intelligence and Security (AISec 2017). CCS 2017: 2621-2622 - [c31]Aaron Schlenker, Haifeng Xu, Mina Guirguis, Christopher Kiekintveld, Arunesh Sinha, Milind Tambe, Solomon Y. Sonya, Darryl Balderas, Noah Dunstatter:
Don't Bury your Head in Warnings: A Game-Theoretic Approach for Intelligent Allocation of Cyber-security Alerts. IJCAI 2017: 381-387 - [e4]Bhavani Thuraisingham, Battista Biggio, David Mandell Freeman, Brad Miller, Arunesh Sinha:
Proceedings of the 10th ACM Workshop on Artificial Intelligence and Security, AISec@CCS 2017, Dallas, TX, USA, November 3, 2017. ACM 2017, ISBN 978-1-4503-5202-4 [contents] - [i9]Linh Nguyen, Arunesh Sinha:
A Learning Approach to Secure Learning. CoRR abs/1709.04447 (2017) - [i8]Arunesh Sinha, Aaron Schlenker, Donnabell Dmello, Milind Tambe:
Practical Scalability for Stackelberg Security Games. CoRR abs/1711.04208 (2017) - 2016
- [j3]Stefano V. Albrecht, Bruno Bouchard, John S. Brownstein, David L. Buckeridge, Cornelia Caragea, Kevin M. Carter, Adnan Darwiche, Blaz Fortuna, Yannick Francillette, Sébastien Gaboury, C. Lee Giles, Marko Grobelnik, Estevam R. Hruschka Jr., Jeffrey O. Kephart, Parisa Kordjamshidi, Viliam Lisý, Daniele Magazzeni, João Marques-Silva, Pierre Marquis, David R. Martinez, Marek P. Michalowski, Arash Shaban-Nejad, Zeinab Noorian, Enrico Pontelli, Alex Rogers, Stephanie Rosenthal, Dan Roth, Arunesh Sinha, William W. Streilein, Sylvie Thiébaux, Tran Cao Son, Byron C. Wallace, Toby Walsh, Michael Witbrock, Jie Zhang:
Reports of the 2016 AAAI Workshop Program. AI Mag. 37(3): 99-108 (2016) - [j2]Chao Zhang, Shahrzad Gholami, Debarun Kar, Arunesh Sinha, Manish Jain, Ripple Goyal, Milind Tambe:
Keeping Pace with Criminals: An Extended Study of Designing Patrol Allocation against Adaptive Opportunistic Criminals. Games 7(3): 15 (2016) - [c30]Matthew Brown, Arunesh Sinha, Aaron Schlenker, Milind Tambe:
One Size Does Not Fit All: A Game-Theoretic Approach for Dynamically and Effectively Screening for Threats. AAAI 2016: 425-431 - [c29]Thanh Hong Nguyen, Arunesh Sinha, Shahrzad Gholami, Andrew J. Plumptre, Lucas Joppa, Milind Tambe, Margaret Driciru, Fred Wanyama, Aggrey Rwetsiba, Rob Critchlow, Colin M. Beale:
Protecting Wildlife under Imperfect Observation. AAAI Workshop: Computer Poker and Imperfect Information Games 2016 - [c28]Thanh Hong Nguyen, Arunesh Sinha, Milind Tambe:
Conquering Adversary Behavioral Uncertainty in Security Games: An Efficient Modeling Robust Based Algorithm. AAAI 2016: 4242-4243 - [c27]Chao Zhang, Victor Bucarey, Ayan Mukhopadhyay, Arunesh Sinha, Yundi Qian, Yevgeniy Vorobeychik, Milind Tambe:
Using Abstractions to Solve Opportunistic Crime Security Games at Scale. AAMAS 2016: 196-204 - [c26]Arunesh Sinha, Debarun Kar, Milind Tambe:
Learning Adversary Behavior in Security Games: A PAC Model Perspective. AAMAS 2016: 214-222 - [c25]Thanh Hong Nguyen, Arunesh Sinha, Shahrzad Gholami, Andrew J. Plumptre, Lucas Joppa, Milind Tambe, Margaret Driciru, Fred Wanyama, Aggrey Rwetsiba, Rob Critchlow, Colin M. Beale:
CAPTURE: A New Predictive Anti-Poaching Tool for Wildlife Protection. AAMAS 2016: 767-775 - [c24]Shahrzad Gholami, Bryan Wilder, Matthew Brown, Arunesh Sinha, Nicole D. Sintov, Milind Tambe:
SPECTRE: A Game Theoretic Framework for Preventing Collusion in Security Games (Demonstration). AAMAS 2016: 1498-1500 - [c23]David Mandell Freeman, Katerina Mitrokotsa, Arunesh Sinha:
9th International Workshop on Artificial Intelligence and Security: AISec 2016. CCS 2016: 1881 - [c22]Aaron Schlenker, Matthew Brown, Arunesh Sinha, Milind Tambe, Ruta Mehta:
Get Me to My GATE on Time: Efficiently Solving General-Sum Bayesian Threat Screening Games. ECAI 2016: 1476-1484 - [c21]Sara Marie McCarthy, Arunesh Sinha, Milind Tambe, Pratyusa Manadhata:
Data Exfiltration Detection and Prevention: Virtually Distributed POMDPs for Practically Safer Networks. GameSec 2016: 39-61 - [c20]Nika Haghtalab, Fei Fang, Thanh Hong Nguyen, Arunesh Sinha, Ariel D. Procaccia, Milind Tambe:
Three Strategies to Success: Learning Adversary Models in Security Games. IJCAI 2016: 308-314 - [c19]Thanh Hong Nguyen, Arunesh Sinha, Milind Tambe:
Addressing Behavioral Uncertainty in Security Games: An Efficient Robust Strategic Solution for Defender Patrols. IPDPS Workshops 2016: 1831-1838 - [c18]Benjamin J. Ford, Matthew Brown, Amulya Yadav, Amandeep Singh, Arunesh Sinha, Biplav Srivastava, Christopher Kiekintveld, Milind Tambe:
Protecting the NECTAR of the Ganga River Through Game-Theoretic Factory Inspections. PAAMS 2016: 97-108 - [e3]David R. Martinez, William W. Streilein, Kevin M. Carter, Arunesh Sinha:
Artificial Intelligence for Cyber Security, Papers from the 2016 AAAI Workshop, Phoenix, Arizona, USA, February 12, 2016. AAAI Technical Report WS-16-03, AAAI Press 2016 [contents] - [e2]David Mandell Freeman, Aikaterini Mitrokotsa, Arunesh Sinha:
Proceedings of the 2016 ACM Workshop on Artificial Intelligence and Security, AISec@CCS 2016, Vienna, Austria, October 28, 2016. ACM 2016, ISBN 978-1-4503-4573-6 [contents] - [i7]Nicolas Papernot, Patrick D. McDaniel, Arunesh Sinha, Michael P. Wellman:
Towards the Science of Security and Privacy in Machine Learning. CoRR abs/1611.03814 (2016) - 2015
- [j1]Arunesh Sinha, Thanh Hong Nguyen, Debarun Kar, Matthew Brown, Milind Tambe, Albert Xin Jiang:
From physical security to cybersecurity. J. Cybersecur. 1(1): 19-35 (2015) - [c17]Jeremiah Blocki, Nicolas Christin, Anupam Datta, Ariel D. Procaccia, Arunesh Sinha:
Audit Games with Multiple Defender Resources. AAAI 2015: 791-797 - [c16]Chao Zhang, Arunesh Sinha, Milind Tambe:
Keeping Pace with Criminals: Designing Patrol Allocation Against Adaptive Opportunistic Criminals. AAMAS 2015: 1351-1359 - [c15]Chao Zhang, Manish Jain, Ripple Goyal, Arunesh Sinha, Milind Tambe:
Learning, Predicting and Planning against Crime: Demonstration Based on Real Urban Crime Data (Demonstration). AAMAS 2015: 1911-1912 - [c14]Christos Dimitrakakis, Aikaterini Mitrokotsa, Arunesh Sinha:
Workshop Summary of AISec'15: 2015 Workshop on Artificial Intelligent and Security. CCS 2015: 1702 - [c13]Anupam Datta, Deepak Garg, Dilsun Kirli Kaynar, Divya Sharma, Arunesh Sinha:
Program Actions as Actual Causes: A Building Block for Accountability. CSF 2015: 261-275 - [c12]Alejandro Uriel Carbonara, Anupam Datta, Arunesh Sinha, Yair Zick:
Incentivizing Peer Grading in MOOCS: An Audit Game Approach. IJCAI 2015: 497-503 - [c11]Haifeng Xu, Albert Xin Jiang, Arunesh Sinha, Zinovi Rabinovich, Shaddin Dughmi, Milind Tambe:
Security Games with Information Leakage: Modeling and Computation. IJCAI 2015: 674-680 - [e1]Indrajit Ray, Xiaofeng Wang, Kui Ren, Christos Dimitrakakis, Aikaterini Mitrokotsa, Arunesh Sinha:
Proceedings of the 8th ACM Workshop on Artificial Intelligence and Security, AISec 2015, Denver, Colorado, USA, October 16, 2015. ACM 2015, ISBN 978-1-4503-3826-4 [contents] - [i6]Haifeng Xu, Albert Xin Jiang, Arunesh Sinha, Zinovi Rabinovich, Shaddin Dughmi, Milind Tambe:
Security Games With Information Leakage: Modeling and Computation. CoRR abs/1504.06058 (2015) - [i5]Anupam Datta, Deepak Garg, Dilsun Kirli Kaynar, Divya Sharma, Arunesh Sinha:
Program Actions as Actual Causes: A Building Block for Accountability. CoRR abs/1505.01131 (2015) - [i4]Arunesh Sinha, Debarun Kar, Milind Tambe:
Learning Adversary Behavior in Security Games: A PAC Model Perspective. CoRR abs/1511.00043 (2015) - 2014
- [b1]Arunesh Sinha:
Audit Games. Carnegie Mellon University, USA, 2014 - [c10]Arunesh Sinha, Limin Jia, Paul England, Jacob R. Lorch:
Continuous Tamper-Proof Logging Using TPM 2.0. TRUST 2014: 19-36 - [i3]Jeremiah Blocki, Nicolas Christin, Anupam Datta, Ariel D. Procaccia, Arunesh Sinha:
Audit Games with Multiple Defender Resources. CoRR abs/1409.4503 (2014) - 2013
- [c9]Arunesh Sinha, Yan Li, Lujo Bauer:
What you want is not what you get: predicting sharing policies for text-based content on facebook. AISec 2013: 13-24 - [c8]Jeremiah Blocki, Nicolas Christin, Anupam Datta, Arunesh Sinha:
Adaptive Regret Minimization in Bounded-Memory Games. GameSec 2013: 65-84 - [c7]Jeremiah Blocki, Nicolas Christin, Anupam Datta, Ariel D. Procaccia, Arunesh Sinha:
Audit Games. IJCAI 2013: 41-47 - [i2]Jeremiah Blocki, Nicolas Christin, Anupam Datta, Ariel D. Procaccia, Arunesh Sinha:
Audit Games. CoRR abs/1303.0356 (2013) - 2012
- [c6]Jeremiah Blocki, Nicolas Christin, Anupam Datta, Arunesh Sinha:
Audit Mechanisms for Provable Risk Management and Accountable Data Governance. GameSec 2012: 38-59 - [c5]Anupam Datta, Divya Sharma, Arunesh Sinha:
Provable De-anonymization of Large Datasets with Sparse Dimensions. POST 2012: 229-248 - 2011
- [c4]Jeremiah Blocki, Nicolas Christin, Anupam Datta, Arunesh Sinha:
Regret Minimizing Audits: A Learning-Theoretic Basis for Privacy Protection. CSF 2011: 312-327 - [c3]Anupam Datta, Jeremiah Blocki, Nicolas Christin, Henry DeYoung, Deepak Garg, Limin Jia, Dilsun Kirli Kaynar, Arunesh Sinha:
Understanding and Protecting Privacy: Formal Semantics and Principled Audit Mechanisms. ICISS 2011: 1-27 - [c2]Jeremiah Blocki, Nicolas Christin, Anupam Datta, Arunesh Sinha:
Audit Mechanisms for Privacy Protection in Healthcare Environments. HealthSec 2011 - [i1]Jeremiah Blocki, Nicolas Christin, Anupam Datta, Arunesh Sinha:
Adaptive Regret Minimization in Bounded-Memory Games. CoRR abs/1111.2888 (2011)
2000 – 2009
- 2009
- [c1]Pushparani Bhallamudi, Scott R. Tilley, Arunesh Sinha:
Migrating a Web-based application to a service-based system - an experience report. WSE 2009: 71-74
Coauthor Index
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to record detail pages.
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Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
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OpenAlex data
Load additional information about publications from 
.
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last updated on 2024-11-25 23:38 CET by the dblp team
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