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Rowhammer is a hardware security vulnerability at the heart of every system with modern DRAM-based memory. Despite its discovery a decade ago, comprehensive defenses remain elusive, while the probability of successful attacks grows with…

Machine learning models are increasingly being adopted across various fields, such as medicine, business, autonomous vehicles, and cybersecurity, to analyze vast amounts of data, detect patterns, and make predictions or recommendations. In…

Deep learning-based malware detectors have been shown to be susceptible to adversarial malware examples, i.e. malware examples that have been deliberately manipulated in order to avoid detection. In light of the vulnerability of deep…

Rank-metric code-based cryptography relies on the hardness of decoding a random linear code in the rank metric. The Rank Support Learning problem (RSL) is a variant where an attacker has access to N decoding instances whose errors have the…

Return-Oriented Programming (ROP) is a software exploit for system compromise. By chaining short instruction sequences from existing code pieces, ROP can bypass static code-integrity checking approaches and non-executable page protections.…

Research has proven that end-to-end malware detectors are vulnerable to adversarial attacks. In response, the research community has proposed defenses based on randomized and (de)randomized smoothing. However, these techniques remain…

Adversarial examples have been shown to be the severe threat to deep neural networks (DNNs). One of the most effective adversarial defense methods is adversarial training (AT) through minimizing the adversarial risk $R_{adv}$, which…

The Precision Time Protocol (PTP), standardized as IEEE 1588, provides sub-microsecond synchronization across distributed systems and underpins critical infrastructure in telecommunications, finance, power systems, and industrial…

With the improvements in computing technologies, edge devices in the Internet-of-Things have become more complex. The enabler technology for these complex systems are powerful application core processors with operating system support, such…

The endless stream of vulnerabilities urgently calls for principled mitigation to confine the effect of exploitation. However, the monolithic architecture of commodity OS kernels, like the Linux kernel, allows an attacker to compromise the…

Recent Microsoft security bulletins show that kernel vulnerabilities are becoming more and more important security threats. Despite the pretty extensive security mitigations many of the kernel vulnerabilities are still exploitable.…

Linux Containers, such as those managed by Docker, are an increasingly popular way to package and deploy complex applications. However, the fundamental security primitive of network access control for a distributed microservice deployment…

With the advancement in robotics, it is becoming increasingly common for large factories and warehouses to incorporate visual SLAM (vSLAM) enabled automated robots that operate closely next to humans. This makes any adversarial attacks on…

AI control protocols serve as a defense mechanism to stop untrusted LLM agents from causing harm in autonomous settings. Prior work treats this as a security problem, stress testing with exploits that use the deployment context to subtly…

Large language models are exposed to risks of extraction, distillation, and unauthorized fine-tuning. Existing defenses use watermarking or monitoring, but these act after leakage. We design AlignDP, a hybrid privacy lock that blocks…

Denial-of-Service (DoS) conditions in enterprise networks are commonly attributed to malicious actors. However, availability can also be compromised by benign non-malicious insider behavior. This paper presents an empirical study of a…

Deep learning-based automatic modulation classification (AMC) models are susceptible to adversarial attacks. Such attacks inject specifically crafted wireless interference into transmitted signals to induce erroneous classification…

Jailbreak attacks pose persistent threats to large language models (LLMs). Current safety alignment methods have attempted to address these issues, but they experience two significant limitations: insufficient safety alignment depth and…

Linux kernel vulnerability reproduction is a critical task in system security. To reproduce a kernel vulnerability, the vulnerable environment and the Proof of Concept (PoC) program are needed. Most existing research focuses on the…

Adversarial training (AT) is a robust learning algorithm that can defend against adversarial attacks in the inference phase and mitigate the side effects of corrupted data in the training phase. As such, it has become an indispensable…