CaSym: Cache Aware Symbolic Execution for Side Channel Detection and Mitigation
Explores cache-aware symbolic execution for detecting and mitigating side-channel vulnerabilities, offering novel abstract cache models and guidance for effective countermeasures.
Iodine - Fast Dynamic Taint Tracking Using Rollback Free Optimistic Hybrid Analysis
Explores fast dynamic taint tracking using optimistic hybrid analysis, reducing overhead while maintaining soundness. Introduces Iodine tool for efficient security policy enforcement without rollbacks.
SoK: The Challenges, Pitfalls, and Perils of Using Hardware Performance Counters for Security
Explores challenges and pitfalls of using Hardware Performance Counters for security applications, highlighting measurement imprecisions and incorrect assumptions that can undermine protection efforts.
Tracking Browser Fingerprint Evolutions - Antoine Vastel
Explore browser fingerprint tracking techniques, including FP-STALKER's rule-based and hybrid approaches, to understand long-term user identification without cookies.
HeNet- A Deep Learning Approach on Intel Processor Trace for Effective Exploit Detection
Explore a deep learning approach using Intel Processor Trace for effective exploit detection. Learn about HeNet's hierarchical ensemble neural network for classifying hardware-generated control flow traces in malware detection.
Black-Box Generation of Adversarial Text Sequences to Evade Deep Learning Classifiers
Explores techniques for generating adversarial text sequences to deceive deep learning classifiers, focusing on black-box attacks and their effectiveness in real-world scenarios.
Plug & Pray Today - Understanding USB Insecurity in Versions 1 through C
Comprehensive overview of USB security vulnerabilities and defenses across multiple layers, analyzing attacks, countermeasures, and the USB Type-C Authentication protocol's limitations.
Privacy Risks with Facebook's PII-Based Targeting
Explore privacy risks in Facebook's PII-based targeting, uncovering vulnerabilities in custom audience features that allow user data inference and de-anonymization. Learn about potential fixes and implications for advertising platforms.
Understanding Linux Malware
Explore Linux malware analysis challenges, infrastructure design, and insights from a large-scale study of 10,548 samples, addressing the growing threat in embedded devices and IoT.
SoK: Keylogging Side Channels
Comprehensive analysis of keylogging side channel attacks, exploring spatial and temporal vulnerabilities, historical context, and current state-of-the-art techniques in cybersecurity research.
Racing in Hyperspace - Closing Hyper-Threading Side Channels on SGX
Explore techniques to mitigate Hyper-Threading side-channel vulnerabilities in Intel SGX enclaves using HYPERRACE, an LLVM-based tool that creates shadow threads and verifies physical-core co-location.
NTFUZZ: Enabling Type-Aware Kernel Fuzzing on Windows with Static Binary Analysis
Explore type-aware kernel fuzzing on Windows using static binary analysis, enhancing security testing with NTFUZZ's innovative approach and real-world applications.
Revealer- Detecting and Exploiting Regular Expression Denial-of-Service Vulnerabilities
Explore techniques for detecting and exploiting ReDoS vulnerabilities, including static analysis, pattern identification, and automated exploit generation.
CacheOut - Leaking Data on Intel CPUs via Cache Evictions
Explore Intel CPU vulnerabilities, focusing on CacheOut attack, its mechanisms, potential targets, and countermeasures for enhanced system security.
Bookworm Game - Automatic Discovery of LTE Vulnerabilities Through Documentation Analysis
Explore automatic vulnerability detection in LTE networks using documentation analysis, covering network architecture, hazard indicators, and attack models.
Detecting Filter List Evasion With Event-Loop-Turn Granularity JavaScript Signatures
Explore techniques for detecting filter list evasion using JavaScript signatures, focusing on event-loop-turn granularity and privacy-relevant aspects of web tracking.
Adversary Instantiation - Lower Bounds for Differentially Private Machine Learning
Explore lower bounds for differentially private machine learning, focusing on DPSGD, membership inference, and gradient poisoning attacks in this IEEE presentation.
Binary Analysis with Architecture and Code Section Detection Using Supervised Machine Learning
Explore supervised machine learning techniques for binary analysis, focusing on architecture and code section detection to enhance reverse engineering and security analysis.
Meddling Middlemen - Empirical Analysis of the Risks of Data-Saving Mobile Browsers
Empirical analysis of data-saving mobile browsers, exploring their effectiveness, impact on usability, and potential security risks. Examines proxy server configurations, privacy concerns, and proposes improved designs.
KARONTE - Detecting Insecure Multi-Binary Interactions in Embedded Firmware
Explore KARONTE, an innovative tool for detecting security vulnerabilities in embedded firmware through multi-binary interaction analysis, enhancing IoT device protection.
Are We Susceptible to Rowhammer? An End-to-End Methodology for Cloud Providers
Comprehensive methodology for cloud providers to assess DRAM vulnerability to Rowhammer attacks, including near-optimal instruction sequences and row adjacency mapping techniques for modern Intel platforms.