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Vertical split learning (SL) enables collaborative model training across parties holding complementary features without sharing raw data, but recent work has shown that it is highly vulnerable to poisoning-based backdoor attacks operating…
The proliferation of Large Language Models (LLMs) in real-world applications poses unprecedented risks of generating harmful, biased, or misleading information to vulnerable populations including LGBTQ+ individuals, single parents, and…
The use of ML in cybersecurity has long been impaired by generalization issues: Models that work well in controlled scenarios fail to maintain performance in production. The root cause often lies in ML algorithms learning superficial…
As cloud computing gains traction, data owners are outsourcing their data to cloud service providers (CSPs) for Database Service (DBaaS), bringing in a deviation of data ownership and usage, and intensifying privacy concerns, especially…
Deep joint source-channel coding (JSCC) has emerged as a promising paradigm for semantic communication, delivering significant performance gains over conventional separate coding schemes. However, existing JSCC frameworks remain vulnerable…
Deploying large language models (LLMs) as autonomous browser agents exposes a significant attack surface in the form of Indirect Prompt Injection (IPI). Cloud-based defenses can provide strong semantic analysis, but they introduce latency…
Recent studies on adversarial images have shown that they tend to leave the underlying low-dimensional data manifold, making them significantly more challenging for current models to make correct predictions. This so-called off-manifold…
As large language models (LLMs) become increasingly integrated into real-world applications such as code generation and chatbot assistance, extensive efforts have been made to align LLM behavior with human values, including safety.…
Contemporary computing employs cache hierarchy to fill the speed gap between processors and main memories. In order to optimise system performance, Last Level Caches(LLC) are shared among all the cores. Cache sharing has made them an…
With the increasing adoption of Continuous Integration and Continuous Deployment pipelines, securing software supply chains has become a critical challenge for modern DevOps teams. This study addresses these challenges by applying a…
Under the emerging network coding paradigm, intermediate nodes in the network are allowed not only to store and forward packets but also to process and mix different data flows. We propose a low-complexity cryptographic scheme that exploits…
Over the last two decades, the danger of sharing resources between programs has been repeatedly highlighted. Multiple side-channel attacks, which seek to exploit shared components for leaking information, have been devised, mostly targeting…
Modern microcontroller software is often written in C/C++ and suffers from control-flow hijacking vulnerabilities. Previous mitigations suffer from high performance and memory overheads and require either the presence of memory protection…
Cyber-physical systems posit a complex number of security challenges due to interconnection of heterogeneous devices having limited processing, communication, and power capabilities. Additionally, the conglomeration of both physical and…
Multimodal Large Language Models (MLLMs) achieve strong reasoning and perception capabilities but are increasingly vulnerable to jailbreak attacks. While existing work focuses on explicit attacks, where malicious content resides in a single…
Side-channel attacks have become a severe threat to the confidentiality of computer applications and systems. One popular type of such attacks is the microarchitectural attack, where the adversary exploits the hardware features to break the…
We systematize software side-channel attacks with a focus on vulnerabilities and countermeasures in the cryptographic implementations. Particularly, we survey past research literature to categorize vulnerable implementations, and identify…
This article provides a tool for analyzing mechanisms that aim to achieve resilience against stealthy, or undetectable, attacks on cyber-physical systems (CPSs). We consider attackers who are able to corrupt all of the inputs and outputs of…
Intel Software Guard Extensions (SGX) provides a trusted execution environment (TEE) to run code and operate sensitive data. SGX provides runtime hardware protection where both code and data are protected even if other code components are…
Attackers can access sensitive information of programs by exploiting the side-effects of speculatively-executed instructions using Spectre attacks. To mitigate theses attacks, popular compilers deployed a wide range of countermeasures. The…