Manipulating Machine Learning: Poisoning Attacks and Countermeasures for Regression Learning
Jagielski, Matthew, Oprea, Alina, Biggio, Battista, Liu, Chang, Nita-Rotaru, Cristina, Li, Bo·2018·2018 IEEE Symposium on Security and Privacy (SP)
Cited by (860)
Items 301–400 of 860
- Turning Federated Learning Systems Into Covert ChannelsGabriele Costa, Fabio Pinelli, Simone Soderi, Gabriele Tolomei · 2022 · IEEE Access
- On the Adversarial Robustness of Subspace LearningFuwei Li, Lifeng Lai, Shuguang Robert Cui · 2020 · IEEE Transactions on Signal Processing
- Towards Class-Oriented Poisoning Attacks Against Neural NetworksBingyin Zhao, Yingjie Lao · 2022 · IEEE Winter Conference on Applications of Computer Vision
- Holistic Adversarial Robustness of Deep Learning ModelsPin‐Yu Chen, Sijia Liu · 2023 · Proceedings of the AAAI Conference on Artificial Intelligence
- PAC-learning in the presence of evasion adversariesDaniel Cullina, A. Bhagoji, Prateek Mittal · 2018 · Neural Information Processing Systems
- Garbage In, Garbage Out: Poisoning Attacks Disguised With Plausible Mobility in Data AggregationPing Zhao, Hongbo Jiang, Jie Li, Zhu Qiang Xiao, Daibo Liu, Ju Ren, Deke Guo · 2021 · IEEE Transactions on Network Science and Engineering
- EV-FL: Efficient Verifiable Federated Learning With Weighted Aggregation for Industrial IoT NetworksHaiyang Yu, Runtong Xu, Zhang Hui, Zhen Yang, Huan Liu · 2023 · IEEE/ACM Transactions on Networking
- Selective Amnesia: On Efficient, High-Fidelity and Blind Suppression of Backdoor Effects in Trojaned Machine Learning ModelsRui Zhu, Di Tang, Siyuan Tang, Xiaofeng Wang, Haixu Tang · 2023 · IEEE Symposium on Security and Privacy (S&P)
- Privacy-Preserving Distributed Learning for Residential Short-Term Load ForecastingYi Dong, Yingjie Wang, Mariana Botelho da Gama, Mustafa Mustafa, Geert Deconinck, Xiaowei Huang · 2024 · IEEE Internet of Things Journal
- Evaluating Efficiency and Effectiveness of Federated Learning Approaches in Knowledge Extraction TasksFiammetta Marulli, Laura Verde, S. Marrone, Roberta Barone, Maria Stella de Biase · 2021 · International Joint Conference on Neural Networks (IJCNN)
- Re-Learning Emotional Intelligence Through Artificial IntelligenceSandeep Singh, Chetan Banbarilal Sharma, Shamneesh Sharma, Neeraj Kumar Verma · 2021 · International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)
- {DRMI}: A Dataset Reduction Technology based on Mutual Information for Black-box AttacksYingzhe He, Guozhu Meng, Kai Chen, Xingbo Hu, Jinwen He · 2021 · USENIX Security Symposium
- Defending Against Data Poisoning Attacks: From Distributed Learning to Federated LearningYuchen Tian, Weizhe Zhang, Andrew C. Simpson, Yang Liu, Zoe L. Jiang · 2021 · The Computer Journal
- An improved real time detection of data poisoning attacks in deep learning vision systemsVijay Raghavan, Thomas A. Mazzuchi, Shahram Sarkani · 2022 · Discover Artificial Intelligence
- Leveraging Artificial Intelligence in Blockchain-Based E-Health for Safer Decision Making FrameworkAbdulatif Alabdulatif, Muneerah Al Asqah, Tarek Moulahi, Salah Zidi · 2023 · Applied Sciences
- Conceptualizing the Secure Machine Learning Operations (SecMLOps) ParadigmXinrui Zhang, Jason Jaskolka · 2022 · IEEE International Conference on Software Quality, Reliability and Security (QRS)
- Secure water quality prediction system using machine learning and blockchain technologiesM. Geetha Jenifel · 2023 · Journal of Environmental Management
- FlexibleFL: Mitigating poisoning attacks with contributions in cloud-edge federated learning systemsYaru Zhao, Yihao Cao, Jianbiao Zhang, Haoxiang Huang, Yanhui Liu · 2024 · Information Sciences
- A survey on machine unlearning: Techniques and new emerged privacy risksHengzhu Liu, Ping Xiong, Tianqing Zhu, Philip S. Yu · 2025 · Journal of Information Security and Applications
- A Cause-Based Classification Approach for Malicious DNS Queries Detected Through BlacklistsAkihiro Satoh, Yutaka Nakamura, Yutaka Fukuda, Kazuto Sasai, Gen Kitagata · 2019 · IEEE Access
- Review and Critical Analysis of Privacy-Preserving Infection Tracking and Contact TracingWilliam Johnston Buchanan, Muhammad Ali Imran, Masood Ur Rehman, Lei Zhang, Qammer H. Abbasi, Christos Chrysoulas, David Haynes, Nikolaos Pitropakis, Pavlos Papadopoulos · 2020 · Frontiers in Communications and Networks
- Quarantine: Sparsity Can Uncover the Trojan Attack Trigger for FreeTianlong Chen, Zhenyu Zhang, Yihua Zhang, Shiyu Chang, Sijia Liu, Zhangyang Wang · 2022 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
- Min-Max Optimization without Gradients: Convergence and Applications to Adversarial MLSijia Liu, Songtao Lu, Xiangyi Chen, Yao Feng, Kaidi Xu, Abdullah Al-Dujaili, Hong, Minyi, Una-May O’Reilly · 2019 · arXiv (Cornell University)
- Financial Crime & Fraud Detection Using Graph Computing: Application Considerations & OutlookEren Kurshan, Hongda Shen, Haiyang Yu · 2021 · arXiv (Cornell University)
- Understanding the Limits of Unsupervised Domain Adaptation via Data PoisoningAkshay Mehra, Bhavya Kailkhura, Pin‐Yu Chen, Jihun Hamm · 2021 · arXiv (Cornell University)
- Blockchain-Based Attack Detection on Machine Learning Algorithms for IoT-Based e-Health ApplicationsThippa Reddy Gadekallu, M. K. Manoj, Sivarama Krishnan S, Neeraj Kumar, Saqib Hakak, Sweta Bhattacharya · 2021 · IEEE Internet of Things Magazine
- Sensitivity of Machine Learning Approaches to Fake and Untrusted Data in Healthcare DomainFiammetta Marulli, S. Marrone, Laura Verde · 2022 · Journal of Sensor and Actuator Networks
- Efficient Defenses Against Output Poisoning Attacks on Local Differential PrivacyShaorui Song, Lei Xu, Liehuang Zhu · 2023 · IEEE Transactions on Information Forensics and Security
- Ethical Marketing AI?A Structured Literature Review of the Ethical Challenges Posed by Artificial Intelligence in the Domains of Marketing and Consumer BehaviorYiran Su, Emma Junhong Wang, Pierre R. Berthon · 2023 · Hawaii International Conference on System Sciences (HICSS)
- Poison-Resilient Anomaly Detection: Mitigating Poisoning Attacks in Semi-Supervised Encrypted Traffic Anomaly DetectionZhangfa Wu, Huifang Li, Yekui Qian, Yi Hua, Hongping Gan · 2024 · IEEE Transactions on Network Science and Engineering
- Exploiting Gaussian Noise Variance for Dynamic Differential Poisoning in Federated LearningMd Tamjid Hossain, Shahriar Badsha, Hung Manh La, Shafkat Islam, Ibrahim Khalil · 2025 · IEEE Transactions on Artificial Intelligence
- DTA-PUF: Dynamic Timing-aware Physical Unclonable Function for Resource-constrained DevicesIoannis Tsiokanos, Jack Miskelly, Chongyan Gu, Maire P. O'Neill, Georgios Karakonstantis · 2021 · ACM Journal on Emerging Technologies in Computing Systems
- Trembling triggers: exploring the sensitivity of backdoors in DNN-based face recognitionCecilia Pasquini, Rainer Böhme · 2020 · EURASIP Journal on Information Security
- zkMLaaS: a Verifiable Scheme for Machine Learning as a ServiceChenyu Huang, Jianzong Wang, Huangxun Chen, Shijing Si, Zhangcheng Huang, Jing Zhong Xiao · 2022 · Globecom
- Challenges and Countermeasures of Federated Learning Data Poisoning Attack Situation PredictionJianping Wu, Jiahe Jin, Chunming Wu · 2024 · Mathematics
- Cybersecurity of AI medical devices: risks, legislation, and challengesElisabetta Biasin, Erik Kamenjašević, Kaspar Rosager Ludvigsen · 2024 · Edward Elgar Publishing eBooks
- FedRoLA: Robust Federated Learning Against Model Poisoning via Layer-based AggregationGang Yan, Hao Wang, Xu Yuan, Jian Li · 2024 · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)
- Security threats to agricultural artificial intelligence: Position and perspectiveYansong Gao, Seyit Ahmet Camtepe, Nazatul Haque Sultan, Hang Thanh Bui, Arash Mahboubi, Hamed Aboutorab, Michael Bewong, Rafiqul Islam, Md Zahidul Islam, Aufeef Chauhan et al. · 2024 · Computers and Electronics in Agriculture
- AI-Powered Cyber Threats: A Systematic ReviewMafaz Mohsin Khalil Alanezi, Ruah Mouad Alyas AL-Azzawi · 2024 · Mesopotamian Journal of CyberSecurity
- An Adversarial Training Based Machine Learning Approach to Malware Classification under Adversarial ConditionsSean M. Devine, Nathaniel D. Bastian · 2021 · Hawaii International Conference on System Sciences (HICSS)
- Dynamic Federated Learning Model for Identifying Adversarial Clients.Nuria Rodríguez-Barroso, Eugenio Martínez‐Cámara, M. Victoria Luzón, Gerardo González-Seco, Miguel A. Veganzones, Francisco Herrera · 2020 · arXiv (Cornell University)
- Privacy Issues, Attacks, Countermeasures and Open Problems in Federated Learning: A SurveyBlessing Guembe, Sanjay Misra, Ambrose Agbon Azeta · 2024 · Applied Artificial Intelligence
- Robust Nonparametric Regression under Poisoning AttackPuning Zhao, Zhiguo Wan · 2024 · Proceedings of the AAAI Conference on Artificial Intelligence
- Robust and privacy-preserving federated learning with distributed additive encryption against poisoning attacksFan Zhang, Hui Huang, Zhixiong Chen, Zhenjie Huang · 2024 · Computer Networks
- Impacting Robustness in Deep Learning-Based NIDS through Poisoning AttacksShahad Alahmed, Qutaiba Alasad, Jiann Shiun Yuan, Mohammed Alawad · 2024 · Algorithms
- M-to-N Backdoor Paradigm: A Multi-Trigger and Multi-Target Attack to Deep Learning ModelsLinshan Hou, Zhongyun Hua, Yuhong Li, Yifeng Zheng, Leo Yu Zhang · 2024 · IEEE Transactions on Circuits and Systems for Video Technology
- Adopting AI in EducationMehdi Kaddouri, Khalid Mhamdi, Ilham Chniete, Meriem Marhraoui, Mohamed Khaldi, Sabrine Jmad · 2024 · Advances in educational technologies and instructional design book series
- The Price of Tailoring the Index to Your Data: Poisoning Attacks on Learned Index StructuresEvgenios M. Kornaropoulos, Silei Ren, Roberto Tamassia · 2022 · ACM SIGMOD International Conference on Management of Data (SIGMOD)
- An Approach for Poisoning Attacks Against RNN-Based Cyber Anomaly DetectionJinghui Xu, Yu Wen, Chun Hung Yang, Dan Meng · 2020 · IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)
- Poisoning Attacks against Data-Driven Control MethodsAlessio Russo, Alexandre Proutière · 2021 · Proceedings of the ... American Control Conference/Proceedings of the American Control Conference
- Efficient and Secure Deep Learning Inference in Trusted Processor Enabled Edge CloudsYuepeng Li, Deze Zeng, Lin Gu, Quan Chen, Song Guo, Albert Y. Zomaya, Minyi Guo · 2022 · IEEE Transactions on Parallel and Distributed Systems
- PELTA - Shielding Multiparty-FHE against Malicious AdversariesSylvain Chatel, Christian Mouchet, Ali Utkan Şahin, Apostolos Pyrgelis, Carmela Troncoso, Jean‐Pierre Hubaux · 2023 · ACM SIGSAC Conference on Computer and Communications Security (CCS)
- Poisoning Attacks on Algorithmic FairnessDavid Solans, Battista Biggio, Carlos Castillo · 2021 · Lecture notes in computer science
- Better Safe Than Sorry: Constructing Byzantine-Robust Federated Learning with Synthesized TrustGangchao Geng, Tianyang Cai, Zheng Yang · 2023 · Electronics
- Towards an Adversarial Machine Learning Framework in Cyber-Physical SystemsJohn Mulo, Tian Pu, Adamu Hussaini, Hengshuo Liang, Wei Yu · 2023 · IEEE/ACIS International Conference on Software Engineering Research, Management and Applications (SERA)
- Fraud Detection under Siege: Practical Poisoning Attacks and Defense StrategiesTommaso Paladini, Francesco Monti, Mario Polino, Michele Carminati, Stefano Zanero · 2023 · ACM Transactions on Privacy and Security
- Hijack Vertical Federated Learning Models as One PartyPengyu Qiu, Xuhong Zhang, Shouling Ji, Changjiang Li, Yuwen Pu, Xing Yang, Ting Wang · 2024 · IEEE Transactions on Dependable and Secure Computing
- Nullius in Explanans: an ethical risk assessment for explainable AILuca Nannini, Diletta Huyskes, Enrico Panai, Giada Pistilli, Alessio Tartaro · 2024 · Ethics and Information Technology
- A Proactive Defense Against Model Poisoning Attacks in Federated LearningHaonan Yan, Chengbo Zheng, Qian Chen, Xiaoguang Li, Bin Wang, Hui Li, Xiaodong Lin · 2025 · IEEE Transactions on Dependable and Secure Computing
- Decentralized Min-Max Optimization: Formulations, Algorithms and Applications in Network Poisoning AttackIoannis Tsaknakis, Mingyi Hong, Sijia Liu · 2020 · IEEE International Conference on Acoustics Speech and Signal Processing
- Backdoor Attack of Graph Neural Networks Based on Subgraph TriggerYu Sheng, Rong Chen, Guanyu Cai, Li Kuang · 2021 · Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
- Manipulating Supply Chain Demand Forecasting With Targeted Poisoning AttacksJian Chen, Yuan Gao, Jinyong Shan, Kai Peng, Chen Wang, Hongbo Jiang · 2022 · IEEE Transactions on Industrial Informatics
- A review of generative and non-generative adversarial attack on context-rich imagesHamil Stanly, S. Mercy Shalinie, Riji Paul · 2023 · Engineering Applications of Artificial Intelligence
- Demystifying Data Poisoning Attacks in Distributed Learning as a ServiceWenqi Wei, Ka-Ho Chow, Yanzhao Wu, Ling Liu · 2023 · IEEE Transactions on Services Computing
- Property Inference Attacks on Convolutional Neural Networks: Influence and Implications of Target Model’s ComplexityMathias Parisot, Balázs Pejó, Dayana Spagnuelo · 2021 · International Conference on Security and Cryptography
- LEGO: A hybrid toolkit for efficient 2PC-based privacy-preserving machine learningZhipeng Zhou, Qiang Fu, Qianjun Wei, Qiang Li · 2022 · Computers & Security
- Covert Channel Attack to Federated Learning Systems.Gabriele Costa, Fabio Pinelli, Simone Soderi, Gabriele Tolomei · 2021 · arXiv (Cornell University)
- ComAvg: Robust decentralized federated learning with random committeesSicong Zhou, Huawei Huang, Ruixin Li, Jialiang Liu, Zibin Zheng · 2023 · Computer Communications
- Poison-Tolerant Collaborative Filtering Against Poisoning Attacks on Recommender SystemsThar Baker, Tong Li, Jingyu Jia, Baolei Zhang, Chang Tan, Albert Y. Zomaya · 2024 · IEEE Transactions on Dependable and Secure Computing
- RVFL: Rational Verifiable Federated Learning Secure Aggregation ProtocolXianyu Mu, Youliang Tian, Zhou Zhou, Shuai Wang, Jinbo Xiong · 2024 · IEEE Internet of Things Journal
- Social bot detection using variational generative adversarial networks with hidden Markov models in Twitter networkGreeshma Lingam, Sajal Kumar Das · 2025 · Knowledge-Based Systems
- Bi-Level Poisoning Attack Model and Countermeasure for Appliance Consumption Data of Smart HomesMustain Billah, Adnan Anwar, Ziaur Rahman, Syed Md. Galib · 2021 · Energies
- Poisoning attack detection using client historical similarity in non-iid environmentsXintong You, Zhengqi Liu, Yang Xu, Xuyang Ding · 2022 · International Conference on Cloud Computing, Data Science & Engineering (Confluence)
- Multi-Attack Detection: General Defense Strategy Based on Neural Networks for CV-QKDHongwei Du, Duan Huang · 2022 · Photonics
- FLMJR: Improving Robustness of Federated Learning via Model StabilityQi Guo, Di Wu, Yong Qi, Saiyu Qi, Qian Li · 2022 · Lecture notes in computer science
- Detection of Electricity Theft False Data Injection Attacks in Smart GridsAbdulrahman Takiddin, Muhammad Ismail, Erchin Serpedin · 2022 · European Signal Processing Conference (EUSIPCO)
- Clean-label poisoning attack with perturbation causing dominant featuresChen Zhang, Zhuo Tang, Kenli Li · 2023 · Information Sciences
- ACROSS: Automated zero-touch cross-layer provisioning framework for 5G and beyond vertical servicesDimitris Giannopoulos, Georgios P. Katsikas, Kostis Trantzas, Dimitrios Klonidis, Christos Tranoris, Spyros Denazis, Lluís Gifre, Ricard Vilalta, Pol Alemany, Raül Muñoz et al. · 2023 · Joint European Conference on Networks and Communications & 6G Summit (EuCNC/6G Summit)
- Online data poisoning attack against edge AI paradigm for IoT-enabled smart cityYanxu Zhu, Hong Wen, Jinsong Wu, Runhui Zhao · 2023 · Mathematical Biosciences & Engineering
- Resilience of Pruned Neural Network Against Poisoning AttackBingyin Zhao, Yingjie Lao · 2018 · International Conference on Malicious and Unwanted Software
- A Robust Malware Detection Approach for Android System Against Adversarial Example AttacksWenjia Li, Neha Bala, Aemun Ahmar, Fernanda Tovar, Arpit Battu, Prachi Bambarkar · 2019 · IEEE International Conference on Collaboration and Internet Computing (CIC)
- PAC-Learning for Strategic ClassificationRavi Sundaram, Anil Kumar S. Vullikanti, Haifeng Xu, Yao, Fan · 2020 · arXiv (Cornell University)
- HaS-Nets: A Heal and Select Mechanism to Defend DNNs Against Backdoor Attacks for Data Collection ScenariosHassan Mohamed Ali, Surya Nepal, Salil S. Kanhere, Sanjay Kumar Jha · 2020 · arXiv (Cornell University)
- A Survey of Security Protection Methods for Deep Learning ModelHaipeng Peng, Shuang Bao, Lixiang Li · 2023 · IEEE Transactions on Artificial Intelligence
- Detecting and Mitigating Data Poisoning Attacks in Machine Learning: A Weighted Average ApproachYogi Reddy Maramreddy, Kireet Muppavaram · 2024 · Engineering Technology & Applied Science Research
- Better Together: Attaining the Triad of Byzantine-robust Federated Learning via Local Update AmplificationLiyue Shen, Yanjun Zhang, Jingwei Wang, Guangdong Bai · 2022 · Annual Computer Security Applications Conference
- Ensurance of artificial intelligence systems cyber security: analysis of vulnerabilities, attacks and countermeasuresOleksii Neretin, Vyacheslav Serhiiovych Kharchenko · 2022 · Vìsnik Nacìonalʹnogo unìversitetu Lʹvìvsʹka polìtehnìka Serìâ Ìnformacìjnì sistemi ta merežì
- Energy-Latency Attacks to On-Device Neural Networks via Sponge PoisoningZijian Wang, Shuo Huang, Yujin Huang, Helei Cui · 2023
- The Path to Defence: A Roadmap to Characterising Data Poisoning Attacks on Victim ModelsTarek Chaalan, Shaoning Pang, Joarder Kamruzzaman, Iqbal Gondal, Xuyun Zhang · 2023 · ACM Computing Surveys
- On the Adversarial Robustness of Robust EstimatorsLifeng Lai, Erhan Bayraktar · 2020 · IEEE Transactions on Information Theory
- A Countermeasure Method Using Poisonous Data Against Poisoning Attacks on IoT Machine LearningTomoki Chiba, Yuichi Sei, Yasuyuki Tahara, Akihiko Ohsuga · 2021 · International Journal of Semantic Computing
- Data Sanitization Approach to Mitigate Clean-Label Attacks Against Malware Detection SystemsSamson Ho, Achyut Reddy, Sridhar Venkatesan, Rauf Izmailov, Ritu Chadha, Alina Oprea · 2022 · IEEE Military Communications Conference (MILCOM)
- Attacking Graph-based Classification via Manipulating the Graph StructureBinghui Wang, Neil Zhenqiang Gong · 2019 · arXiv (Cornell University)
- Defending against Label-Flipping Attacks in Federated Learning Systems with UMAPDeepak Upreti, Hyunil Kim, Eunmok Yang, Changho Seo · 2022 · Research Square
- Defending local poisoning attacks in multi-party learning via immune systemXie, Fei, Gao, Yuan, Wang, Jiongqian, Zhao, Wei · 2022 · Knowledge-Based Systems
- FedG2L: a privacy-preserving federated learning scheme base on “G2L” against poisoning attackMengfan Xu, Xinghua Li · 2023 · Connection Science
- The Dataset Multiplicity Problem: How Unreliable Data Impacts PredictionsAnna P. Meyer, Aws Albarghouthi, Loris D’Antoni · 2023 · ACM Conference on Fairness, Accountability, and Transparency (FAccT)
- FedSV: Byzantine-Robust Federated Learning via Shapley ValueKhaoula Otmani, Rachid El-Azouzi, Vincent Labatut · 2024 · International Conference on Communications
- Community-Oriented Duplex Privacy Amplification and Active Poisoning Resistance for Heterogeneous Federated LearningZan Zhou, Jun Zhao, Shujie Yang, Hongjing Li, Tengchao Ma, Changqiao Xu · 2025 · IEEE Transactions on Dependable and Secure Computing
- Artificial Intelligence for Cybersecurity: Offensive Tactics, Mitigation Techniques and Future DirectionsErwin Adi, Zubair Ahmed Baig, Sherali Zeadally · 2022 · Applied Cybersecurity & Internet Governance