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Mechanics of Materials I: Fundamentals of Stress & Strain and Axial Loading
Fractals and Scaling
Bacterial Genomes II: Accessing and Analysing Microbial Genome Data Using Artemis
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Innovative system for compact storage using homomorphic encryption, addressing high storage overhead while maintaining data confidentiality. Demonstrates practical performance in multi-cloud environments.
Explore DScope, a scalable cloud-based Internet telescope for monitoring malicious behavior. Learn about its design, implementation, and advantages over traditional methods in capturing cloud-targeting traffic.
Explore VulChecker, a tool for precise vulnerability detection in source code using graph-based neural networks. Learn about its innovative approach to locating and classifying security flaws.
Explore side-channel vulnerabilities in Chrome's password leak detection, revealing potential risks to user privacy and security through microarchitectural attacks on cryptographic implementations.
Scalable framework for secure two-party GBDT training on vertically split datasets, featuring novel cryptographic techniques for privacy-preserving machine learning in distributed environments.
Explore robust asynchronous Dynamic-committee Proactive Secret Sharing (DPSS) protocols that handle network churn and faults efficiently, with insights on high-threshold DPSS and batch-amortized schemes.
Innovative defense strategy against bit-flip attacks in neural networks using "honey neurons" to lure attackers, enabling efficient detection and model recovery in safety-critical AI applications.
Privacy-preserving inventory matching system for financial stock trading, enabling efficient order matching while maintaining client confidentiality. Introduces innovative secure linear comparison protocol for computing minimums with malicious security.
Explores security risks of over-privileged cloud credentials in mobile apps, revealing potential data attacks and new threat vectors through analysis of 1.3 million apps across major cloud platforms.
Explores vulnerabilities in federated learning, demonstrating how gradient obfuscation techniques may not provide adequate privacy protection. Proposes a new attack framework and challenges existing evaluation methods.
Análisis de seguridad del protocolo de voto electrónico utilizado en las elecciones legislativas francesas de 2022, revelando vulnerabilidades, proponiendo soluciones y extrayendo lecciones para futuras implementaciones.
Explore a novel system for transparent, privacy-preserving data services. Learn about TAP's tree structure, zero-knowledge proofs, and verifiable operations, addressing limitations in existing approaches.
Explores vulnerabilities in microVM-based containers, demonstrating operation forwarding attacks that can break isolation, exploit host kernel vulnerabilities, and exhaust resources on public cloud platforms.
Explores user perceptions of social media verification, focusing on Twitter's changes. Combines survey data and account analysis to reveal misunderstandings and shifts in verified user demographics.
Real-time method for identifying attack sources on vehicle networks, enhancing cybersecurity through error handling and sequential ECU inspection. Robust against environmental changes and attacker evasion.
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