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Adversarial Update-Based Federated Unlearning for Poisoned Model Recovery
Published in ArXiv cs.CR Recent Papers (2026)Subjects: “…ArXiv cs.CR Recent Papers…”
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Detecting Adversarial Data via Provable Adversarial Noise Amplification
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Redefining AI Red Teaming in the Agentic Era: From Weeks to Hours
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LIPPEN: A Lightweight In-Place Pointer Encryption Architecture for Pointer Integrity
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Generating Proof-of-Vulnerability Tests to Help Enhance the Security of Complex Software
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MOSAIC-Bench: Measuring Compositional Vulnerability Induction in Coding Agents
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HELO Cryptography: A Lightweight Cryptographic System for Enhancing IoT Security in P2P Data Transmission
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KVerus: Scalable and Resilient Formal Verification Proof Generation for Rust Code
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GPUBreach: Privilege Escalation Attacks on GPUs using Rowhammer
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Firmware Distribution as Attack Surface: A Security Study of ASIC Cryptocurrency Miners
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Internet of Things Security: A Survey on Common Attacks
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Tailored Prompts, Targeted Protection: Vulnerability-Specific LLM Analysis for Smart Contracts
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The Infinite Mutation Engine? Measuring Polymorphism in LLM-Generated Offensive Code
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ZK-Value: A Practical Zero-Knowledge System for Verifiable Data Valuation
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From TinyGo to gc Compiler: Extending Zorya's Concolic Framework to Real-World Go Binaries
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MEMSAD: Gradient-Coupled Anomaly Detection for Memory Poisoning in Retrieval-Augmented Agents
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Exposing LLM Safety Gaps Through Mathematical Encoding:New Attacks and Systematic Analysis
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Graph Reconstruction from Differentially Private GNN Explanations
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DECKER: Domain-invariant Embedding for Cross-Keyboard Extraction and Recognition
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ARGUS: Defending LLM Agents Against Context-Aware Prompt Injection
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