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We present a new type of attack in which source code is maliciously encoded so that it appears different to a compiler and to the human eye. This attack exploits subtleties in text-encoding standards such as Unicode to produce source code…
The sustained popularity of the cloud and cloud-related services accelerate the evolution of virtualization-enabling technologies. Modern off-the-shelf computers are already equipped with specialized hardware that enables a hypervisor to…
We investigate the security of Split Learning -- a novel collaborative machine learning framework that enables peak performance by requiring minimal resources consumption. In the present paper, we expose vulnerabilities of the protocol and…
Modern ransomware often generate and manage cryptographic keys on the victim's machine, giving defenders an opportunity to capture exposed keys and recover encrypted data without paying the ransom. However, recent work has raised the…
Internet of Things (IoT) devices sit at the intersection of unwieldy software complexity and unprecedented attacker access. This unique position comes with a daunting security challenge: how can I protect both proprietary code and…
Control Flow Hijacking attacks have posed a serious threat to the security of applications for a long time where an attacker can damage the control Flow Integrity of the program and execute arbitrary code. These attacks can be performed by…
BitLocker is a full-disk encryption feature available in recent Windows versions. It is designed to protect data by providing encryption for entire volumes and it makes use of a number of different authentication methods. In this paper we…
In recent years, edge computing has emerged as a promising technology due to its unique feature of real-time computing and parallel processing. They provide computing and storage capacity closer to the data source and bypass the distant…
Multi-Variant Execution Environments (MVEEs) are a promising technique to protect software against memory corruption attacks. They transparently execute multiple, diversified variants (often referred to as replicae) of the software…
As power consumption from AI training and inference continues to increase, AI accelerators are being integrated directly into the CPU. Intel's Advanced Matrix Extensions (AMX) is one such example, debuting on the 4th generation Intel Xeon…
Machine learning relies on randomness as a fundamental component in various steps such as data sampling, data augmentation, weight initialization, and optimization. Most machine learning frameworks use pseudorandom number generators as the…
Today, permissioned blockchains are being adopted by large organizations for business critical operations. Consequently, they are subject to attacks by malicious actors. Researchers have discovered and enumerated a number of attacks that…
Many emerging cyber-physical systems, such as autonomous vehicles and robots, rely heavily on artificial intelligence and machine learning algorithms to perform important system operations. Since these highly parallel applications are…
Over the past few years, several research groups have introduced innovative hardware designs for Trusted Execution Environments (TEEs), aiming to secure applications against potentially compromised privileged software, including the kernel.…
Vision transformers have contributed greatly to advancements in the computer vision domain, demonstrating state-of-the-art performance in diverse tasks (e.g., image classification, object detection). However, their high computational…
Graphics Processing Units (GPU) offer tremendous computational power by following a throughput oriented computing paradigm where many thousand computational units operate in parallel. Programming this massively parallel hardware is…
Deep Reinforcement Learning (DRL) has numerous applications in the real world thanks to its outstanding ability in quickly adapting to the surrounding environments. Despite its great advantages, DRL is susceptible to adversarial attacks,…
Different types of malicious activities have been flagged in multiple permissionless blockchains such as bitcoin, Ethereum etc. While some malicious activities exploit vulnerabilities in the infrastructure of the blockchain, some target its…
The increasing adoption of large language models (LLMs) in software engineering necessitates rigorous security evaluation of their generated code. However, existing benchmarks often lack relevance to real-world AI-assisted programming…
We give polynomial time attacks on the McEliece public key cryptosystem based either on algebraic geometry (AG) codes or on small codimensional subcodes of AG codes. These attacks consist in the blind reconstruction either of an Error…