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Critical infrastructure defense is fundamentally bottlenecked by the operational reality that preventive controls are frequently bypassed by sophisticated supply-chain compromises and stolen administrative credentials. When prevention…
This paper introduces ObfusQate, a novel tool that conducts obfuscations using quantum primitives to enhance the security of both classical and quantum programs. We have designed and implemented two primary categories of obfuscations:…
One single error can result in a total compromise of all security in today's large, monolithic software. Partitioning of software can help simplify code-review and verification, whereas isolated execution of software-components limits the…
In this paper we study a cybersecurity problem of protecting system's secrets with multiple protections and a required security level, while minimizing the associated cost due to implementation/maintenance of these protections as well as…
Large Language Models (LLMs) are increasingly used for automated software development, making their ability to preserve secure coding practices critical. In practice, however, many security requirements are implicit or underspecified,…
Enterprise environment often screens large-scale (millions of lines of code) codebases with static analysis tools to find bugs and vulnerabilities. Parfait is a static code analysis tool used in Oracle to find security vulnerabilities in…
Recently proliferated semantic communications (SC) aim at effectively transmitting the semantics conveyed by the source and accurately interpreting the meaning at the destination. While such a paradigm holds the promise of making wireless…
Virtualization-based binary obfuscation is widely adopted to protect software intellectual property, yet existing approaches leave exception-handling (EH) metadata unprotected to preserve ABI compatibility. This exposed metadata leaks rich…
The recent breakthrough in large language models (LLMs) such as ChatGPT has revolutionized production processes at an unprecedented pace. Alongside this progress also comes mounting concerns about LLMs' susceptibility to jailbreaking…
As large language models increasingly memorize web-scraped training content, they risk exposing copyrighted or private information. Existing protections require compliance from crawlers or model developers, fundamentally limiting their…
Microarchitectural side channel attacks have been very prominent in security research over the last few years. Caches have been an outstanding covert channel, as they provide high resolution and generic cross-core leakage even with simple…
Auto-regressive decoding in Large Language Models (LLMs) is inherently memory-bound: every generation step requires loading the model weights and intermediate results from memory (e.g., High-Bandwidth Memory (HBM) for GPU servers), making…
Face recognition technology has demonstrated tremendous progress over the past few years, primarily due to advances in representation learning. As we witness the widespread adoption of these systems, it is imperative to consider the…
Edge caching (EC) decreases the average access delay of the end-users through caching popular content at the edge network, however, it increases the leakage probability of valuable information such as users preferences. Most of the existing…
Watermarking acts as a critical safeguard in text generated by Large Language Models (LLMs). By embedding identifiable signals into model outputs, watermarking enables reliable attribution and enhances the security of machine-generated…
The advent of MiniApps, operating within larger SuperApps, has revolutionized user experiences by offering a wide range of services without the need for individual app downloads. However, this convenience has raised significant privacy…
Numerous companies have started offering services based on large language models (LLM), such as ChatGPT, which inevitably raises privacy concerns as users' prompts are exposed to the model provider. Previous research on secure reasoning…
Large language models (LLMs) have achieved remarkable progress in code generation, yet their potential for software protection remains largely untapped. Reverse engineering continues to threaten software security, while traditional virtual…
Benefiting from the superior capabilities of large language models in natural language understanding and generation, Embeddings-as-a-Service (EaaS) has emerged as a successful commercial paradigm on the web platform. However, prior studies…
Cross-app collaboration via inter-component communication is a fundamental mechanism on Android. Although it brings the benefits such as functionality reuse and data sharing, a threat called component hijacking is also introduced. By…