Tag Archives: conference

POMABuster: Detecting Price Oracle Manipulation Attacks in Decentralized Finance

Posted on March 9, 2024 by | Comments Off on POMABuster: Detecting Price Oracle Manipulation Attacks in Decentralized Finance

Rui Xi, Zehua Wang, and Karthik Pattabiraman, To appear in the Proceedings of the IEEE Symposium on Security and Privacy (S&P), 2024. (Acceptance Rate: 17.8%) [ PDF | Talk] (Code)
Continue reading →

Comments Off on POMABuster: Detecting Price Oracle Manipulation Attacks in Decentralized Finance

Posted in papers

Tagged , , , ,

Systematically Assessing the Security Risks of AI/ML-enabled Connected Healthcare Systems

Posted on February 16, 2024 by | Comments Off on Systematically Assessing the Security Risks of AI/ML-enabled Connected Healthcare Systems

Mohammad ElNawawy, Mohammadreza Hallajiyan, Gargi Mitra, Shahrear Iqbal, and Karthik Pattabiraman, To appear in the IEEE/ACM international conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE) (CHASE 2024). (Acceptance Rate: TBD) [ PDF | Talk ] (arXIV version)
Continue reading →

Comments Off on Systematically Assessing the Security Risks of AI/ML-enabled Connected Healthcare Systems

Posted in papers

Tagged , , , , , , ,

ImmunoPlane: Middleware for Providing Adaptivity to Distributed Internet-of-Things Applications

Posted on January 19, 2024 by | Comments Off on ImmunoPlane: Middleware for Providing Adaptivity to Distributed Internet-of-Things Applications

Kumseok Jung, Gargi Mitra, Sathish Gopalakrishnan and Karthik Pattabiraman, To appear in the Proceedings of the ACM/IEEE Conference on Internet of Things Design and Implementation (IoTDI), 2024. (Acceptance Rate: TBD) [ PDF | Talk] (code)
Continue reading →

Comments Off on ImmunoPlane: Middleware for Providing Adaptivity to Distributed Internet-of-Things Applications

Posted in papers

Tagged , , , , , ,

Diagnosis-guided Attack Recovery for Securing Robotic Vehicles from Sensor Deception Attacks

Posted on December 19, 2023 by | Comments Off on Diagnosis-guided Attack Recovery for Securing Robotic Vehicles from Sensor Deception Attacks

Pritam Dash, Guanpeng Li, Mehdi Karimibiuki, and Karthik Pattabiraman, To appear in the ACM Asia Conference on Computer and Communications Security (AsiaCCS), 2024. (Acceptance Rate: TBD) [PDF | Talk] (Code) (arXIV version)
Continue reading →

Comments Off on Diagnosis-guided Attack Recovery for Securing Robotic Vehicles from Sensor Deception Attacks

Posted in papers

Tagged , , , , , ,

Overconfidence is a Dangerous Thing: Mitigating Membership Inference Attacks by Enforcing Less Confident Prediction

Posted on December 2, 2023 by | Comments Off on Overconfidence is a Dangerous Thing: Mitigating Membership Inference Attacks by Enforcing Less Confident Prediction

Zitao Chen and Karthik Pattabiraman, Proceedings of the Network and Distributed Systems Security Conference (NDSS), 2024. (Acceptance Rate: 15%). [ PDF | Talk ] (ArXIV, Code). Artifacts Available, Functional and Reproduced
Continue reading →

Comments Off on Overconfidence is a Dangerous Thing: Mitigating Membership Inference Attacks by Enforcing Less Confident Prediction

Posted in papers

Tagged , , , ,

EdgeEngine: A Thermal-Aware Optimization Framework for Edge Inference

Posted on September 20, 2023 by | Comments Off on EdgeEngine: A Thermal-Aware Optimization Framework for Edge Inference

Amirhossein Ahmadi, Hazem Abdelhafez, Karthik Pattabiraman and Matei Ripeanu, Proceedings of the ACM/IEEE International Symposium on Edge Computing (SEC), 2023. (Acceptance Rate: 25%) [ PDF | Talk ] (Code)
Continue reading →

Comments Off on EdgeEngine: A Thermal-Aware Optimization Framework for Edge Inference

Posted in papers

Tagged , , , ,

Evaluating the Effect of Common Annotation Faults on Object Detection Techniques

Posted on August 7, 2023 by | Comments Off on Evaluating the Effect of Common Annotation Faults on Object Detection Techniques

Abraham Chan, Arpan Gujarati, Karthik Pattabiraman and Sathish Gopalakrishnan, Proceedings of the IEEE International Symposium on Software Reliability Engineering (ISSRE), 2023. (Acceptance Rate: 28.5%) [ PDF | Talk ] (Code). Artifacts Available and Reviewed.

Continue reading →

Comments Off on Evaluating the Effect of Common Annotation Faults on Object Detection Techniques

Posted in papers

Tagged , , , , ,

Resilience Assessment of Large Language Models under Transient Hardware Faults

Posted on August 7, 2023 by | Comments Off on Resilience Assessment of Large Language Models under Transient Hardware Faults

Udit Agarwal, Abraham Chan, and Karthik Pattabiraman, Proceedings of the IEEE International Symposium on Software Reliability Engineering (ISSRE), 2023. (Acceptance Rate: 28.5%) [ PDF | Talk ] (Code). Artifacts Available and Reviewed.
Continue reading →

Comments Off on Resilience Assessment of Large Language Models under Transient Hardware Faults

Posted in papers

Tagged , , , , , ,

Structural Coding: A Low-Cost Scheme to Protect CNNs from Large-Granularity Memory Faults

Posted on June 16, 2023 by | Comments Off on Structural Coding: A Low-Cost Scheme to Protect CNNs from Large-Granularity Memory Faults

Ali Asgari, Florian Geissler, Syed Qutub, Michael Paulitsch, Prashant Nair, and Karthik Pattabiraman, Proceedings of the International Conference for High Performance Computing, Networking, Storage, and Analysis (SC), 2023. (Acceptance Rate: 23.9%) [ PDF | Talk ] (code). Artifacts Available and Functional
Continue reading →

Comments Off on Structural Coding: A Low-Cost Scheme to Protect CNNs from Large-Granularity Memory Faults

Posted in papers

Tagged , , , , ,

A Low-cost Strategic Monitoring Approach for Scalable and Interpretable Error Detection in Deep Neural Networks

Posted on April 22, 2023 by | Comments Off on A Low-cost Strategic Monitoring Approach for Scalable and Interpretable Error Detection in Deep Neural Networks

Florian Geissler, Syed Qutub, Michael Paulitsch and Karthik Pattabiraman, Proceedings of the International Conference on Computer Safety, Reliability and Security (SafeComp), 2023. (Acceptance Rate: 20%) [PDF | Talk]
Continue reading →

Comments Off on A Low-cost Strategic Monitoring Approach for Scalable and Interpretable Error Detection in Deep Neural Networks

Posted in papers

Tagged , , , ,