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- Gérard MemmiSuggested from co-authorship
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Works166 from public data
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- DeepSweep: An Evaluation Framework for Mitigating DNN Backdoor Attacks using Data Augmentation230
A systematic approach is proposed to discover the optimal policies for defending against different backdoor attacks by comprehensively evaluating 71 state-of-the-art data augmentation functions and envision this framework can be a good benchmark tool to advance future DNN backdoor studies.
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- Selective encryption on ECG data in body sensor network based on supervised machine learning155
This paper re-define the SE schemes in a practical scenario of securely outsourcing the electrocardiogram (ECG) data in the untrusted BSN environment and gives the SE design based on this classification use case to protect the ECG data against illegal classification at the attacker sides which protects the patients’ data privacy.
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- A Dynamic Scalable Blockchain Based Communication Architecture for IoT137
A dynamic Blockchain based trust system is proposed to provide a dynamic and scalable communication architecture for IoT networks and a case study is presented to further discuss the security issues and provide future research directions.
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- System Log Parsing: A Survey85
A comprehensive survey on log parsing is provided as a helpful resource for system administrators and domain experts to choose the most desirable open-source solution or implement new ones based on application-specific requirements.
- CLAP: Learning Transferable Binary Code Representations with Natural Language Supervision79
This work presents CLAP (Contrastive Language-Assembly Pre-training), which employs natural language supervision to learn better representations of binary code and get better transferability and proposes an efficient dataset engine that could automatically generate a large and diverse dataset comprising of binary code and corresponding natural language explanations.
- A Networking Perspective on Starlink's Self-Driving LEO Mega-Constellation75
This paper designs a domain-specific method to characterize key components in Starlink's autonomous driving from various public space situational awareness datasets, including continuous orbit maintenance, collision avoidance, and maneuvers between orbital shells.
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- Privacy-preserving Collaborative Learning with Automatic Transformation Search67
This paper proposes to leverage data augmentation to defeat reconstruction attacks: by preprocessing sensitive images with carefully-selected transformation policies, it becomes infeasible for the adversary to extract any useful information from the corresponding gradients.
- A Data Augmentation-Based Defense Method Against Adversarial Attacks in Neural Networks67
This paper focuses on developing a lightweight defense method that can efficiently invalidate full whitebox adversarial attacks with the compatibility of real-life constraints and demonstrates outstanding robustness and efficiency.
- An efficient key distribution system for data fusion in V2X heterogeneous networks61
This paper proposes an efficient and practical data fusion trust system for the multi-source and multi-formats of data exchange in the V2X heterogeneous networks and presents a location-based PKI system with acceleration brought by General Purpose Graphic Processing Unit for efficient key distribution with a high level of trust achieved.
- All-Or-Nothing data protection for ubiquitous communication: Challenges and perspectives60
This paper collates research works across a number of topics in AON, from historical developments to the recent research proposal, and introduces new definitions and category methods to provide useful reference and perspectives for the state of AON research and development.
- NFV Platforms: Taxonomy, Design Choices and Future Challenges58
This study gives a detailed guideline for network operators or service providers to choose the most appropriate NFV platform based on their respective requirements and also provides guidelines for implementing new NFV platforms.
- Aegis: Mitigating Targeted Bit-flip Attacks against Deep Neural Networks55
A dynamic-exit mechanism to attach extra internal classifiers (ICs) to hidden layers and randomly selects ICs for predictions during each inference to significantly increase the attack cost for the adaptive attacks where all defense mechanisms are transparent to the adversary.
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- Novel denial-of-service attacks against cloud-based multi-robot systems46
By analyzing different attack vectors in cloud-robotic platforms, this paper proposes three new DoS attacks, which manipulate the network resources, micro-architecture resources, and function parameters respectively, and alerts the robotics community to these catastrophic attacks.
- An Engorgio Prompt Makes Large Language Model Babble on44
This paper designs Engorgio, a novel methodology, to efficiently generate adversarial Engorgio prompts to affect the target LLM's service availability, and proposes novel loss functions to stably suppress the appearance of thetoken, whose occurrence will interrupt the LLM's generation process.
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Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-14. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
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