| Cyber security in the smart grid: Survey and challenges W Wang, Z Lu Computer networks 57 (5), 1344-1371, 2013 | 1367 | 2013 |
| Review and evaluation of security threats on the communication networks in the smart grid Z Lu, X Lu, W Wang, C Wang 2010-Milcom 2010 Military Communications Conference, 1830-1835, 2010 | 258 | 2010 |
| Adversarial deep learning for cognitive radio security: Jamming attack and defense strategies Y Shi, YE Sagduyu, T Erpek, K Davaslioglu, Z Lu, JH Li 2018 IEEE international conference on communications workshops (ICC …, 2018 | 124 | 2018 |
| Modeling, evaluation and detection of jamming attacks in time-critical wireless applications Z Lu, W Wang, C Wang IEEE Transactions on Mobile Computing 13 (8), 1746-1759, 2013 | 124 | 2013 |
| Cyber deception: Overview and the road ahead C Wang, Z Lu IEEE Security & Privacy 16 (2), 80-85, 2018 | 119 | 2018 |
| Secure edge computing in IoT systems: Review and case studies M Alrowaily, Z Lu 2018 IEEE/ACM symposium on edge computing (SEC), 440-444, 2018 | 118 | 2018 |
| Generalized federated learning via sharpness aware minimization Z Qu, X Li, R Duan, Y Liu, B Tang, Z Lu International conference on machine learning, 18250-18280, 2022 | 109 | 2022 |
| Lomar: A local defense against poisoning attack on federated learning X Li, Z Qu, S Zhao, B Tang, Z Lu, Y Liu IEEE Transactions on Dependable and Secure Computing 20 (1), 437-450, 2021 | 88 | 2021 |
| From jammer to gambler: Modeling and detection of jamming attacks against time-critical traffic Z Lu, W Wang, C Wang 2011 Proceedings IEEE INFOCOM, 1871-1879, 2011 | 79 | 2011 |
| Deep learning-aided cyber-attack detection in power transmission systems D Wilson, Y Tang, J Yan, Z Lu 2018 IEEE Power & Energy Society General Meeting (PESGM), 1-5, 2018 | 72 | 2018 |
| Contextual combinatorial multi-armed bandits with volatile arms and submodular reward L Chen, J Xu, Z Lu Advances in Neural Information Processing Systems 31, 2018 | 70 | 2018 |
| On network performance evaluation toward the smart grid: A case study of DNP3 over TCP/IP X Lu, Z Lu, W Wang, J Ma 2011 IEEE Global Telecommunications Conference-GLOBECOM 2011, 1-6, 2011 | 69 | 2011 |
| When attackers meet AI: Learning-empowered attacks in cooperative spectrum sensing Z Luo, S Zhao, Z Lu, J Xu, YE Sagduyu IEEE Transactions on Mobile Computing 21 (5), 1892-1908, 2020 | 63 | 2020 |
| Context-aware online client selection for hierarchical federated learning Z Qu, R Duan, L Chen, J Xu, Z Lu, Y Liu IEEE Transactions on Parallel and Distributed Systems 33 (12), 4353-4367, 2022 | 59 | 2022 |
| Adversarial machine learning based partial-model attack in IoT Z Luo, S Zhao, Z Lu, YE Sagduyu, J Xu Proceedings of the 2nd ACM workshop on wireless security and machine …, 2020 | 58 | 2020 |
| Effectiveness of machine learning based intrusion detection systems M Alrowaily, F Alenezi, Z Lu Security, Privacy, and Anonymity in Computation, Communication, and Storage …, 2019 | 52 | 2019 |
| No training hurdles: Fast training-agnostic attacks to infer your typing S Fang, I Markwood, Y Liu, S Zhao, Z Lu, H Zhu Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications …, 2018 | 47 | 2018 |
| When wireless security meets machine learning: Motivation, challenges, and research directions YE Sagduyu, Y Shi, T Erpek, W Headley, B Flowers, G Stantchev, Z Lu arXiv preprint arXiv:2001.08883, 2020 | 46 | 2020 |
| Camouflage traffic: Minimizing message delay for smart grid applications under jamming Z Lu, W Wang, C Wang IEEE Transactions on Dependable and Secure Computing 12 (1), 31-44, 2014 | 46 | 2014 |
| Stragglers are not disaster: A hybrid federated learning algorithm with delayed gradients X Li, Z Qu, B Tang, Z Lu arXiv preprint arXiv:2102.06329, 2021 | 40 | 2021 |
