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Explore all talks and presentations from USENIX Security. Dive deep into the latest insights, research, and trends from the world's leading experts.
Explores Tor's congestion issues, proposing KIST algorithm to improve network performance by optimizing socket management using real-time kernel information, reducing latency and increasing throughput.
Explore eclipse attacks on Bitcoin's P2P network, their impact on mining and consensus, and proposed countermeasures to enhance network security while maintaining decentralization.
Explores Control-Flow Bending attacks on Control-Flow Integrity defenses, revealing vulnerabilities in fine-grained CFI implementations and demonstrating the necessity of shadow stacks for enhanced security against memory corruption.
Explores BLE device privacy vulnerabilities and introduces BLE-Guardian, a system protecting user privacy by controlling device discovery and access without modifying existing devices or protocols.
Explores k-fingerprinting, a robust website fingerprinting technique using random decision forests, demonstrating high accuracy in identifying visited web pages through encrypted connections.
Automated approach to detect ransomware through dynamic analysis, focusing on file tampering and desktop changes. Improves detection of evasive ransomware unnoticed by traditional antimalware solutions.
Explores model extraction attacks on machine learning systems, demonstrating vulnerabilities in publicly accessible ML interfaces and proposing potential countermeasures to protect confidential models.
Innovative approach to bypass face authentication using 3D models created from social media photos, exploiting virtual reality to simulate liveness and fool security systems.
Explores novel exploitation techniques against Intel SGX, demonstrating vulnerabilities in enclave code without requiring kernel privileges or crashes, even with existing randomization approaches.
Unveils Facebook's exploitation of sensitive user data for advertising, quantifying its prevalence and discussing privacy implications under GDPR. Proposes a browser extension for user awareness.
Uncovers vulnerabilities in OpenPGP and S/MIME email encryption standards, demonstrating how malleability gadgets can be exploited to reveal encrypted content through exfiltration channels in various email clients.
Efficient framework for secure neural network inference combining homomorphic encryption and two-party computation, outperforming existing systems in speed while preserving privacy for cloud-based machine learning.
Optimizing OS fuzzer seed selection through trace distillation, improving code coverage and vulnerability detection in Linux kernel testing.
Explore automated exploit generation for kernel Use-After-Free vulnerabilities using FUZE framework, enhancing security analysis efficiency and exploitability evaluation for complex OS kernels.
Explores QSYM, a fast concolic execution engine for hybrid fuzzing, integrating symbolic emulation with native execution to find bugs in complex software more efficiently than traditional methods.
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