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The use of unsafe programming languages still remains one of the major root causes of software vulnerabilities. Although well-known defenses that detect and mitigate memory-safety related issues exist, they don't address the challenge of…

In Ontology Based Data Access (OBDA) users pose SPARQL queries over an ontology that lies on top of relational datasources. These queries are translated on-the-fly into SQL queries by OBDA systems. Standard SPARQL-to-SQL translation…

Secure applications implement software protections against side-channel and physical attacks. Such protections are meaningful at machine code or micro-architectural level, but they typically do not carry observable semantics at source…

Simply restricting the computation to non-sensitive part of the data may lead to inferences on sensitive data through data dependencies. Inference control from data dependencies has been studied in the prior work. However, existing…

The General Data Protection Regulation (GDPR) requires an organisation that suffers a data breach to notify the competent Data Protection Authority. The organisation must also inform the relevant individuals, when a data breach threatens…

The promise of Large Language Model (LLM) agents is to perform complex, stateful tasks. This promise is stunted by significant risks - policy violations, process corruption, and security flaws - that stem from the lack of visibility and…

As Large Language Models (LLMs) become integral to scientific workflows, concerns over the confidentiality and ethical handling of confidential data have emerged. This paper explores data exposure risks through LLM-powered scientific tools,…

Irregular codes are bottlenecked by memory and communication latency. Decoupled access/execute (DAE) is a common technique to tackle this problem. It relies on the compiler to separate memory address generation from the rest of the program,…

Databases play a pivotal role in the contemporary World Wide Web and the world of cloud computing. Unfortunately, numerous privacy violations have recently garnered attention in the news. To enhance database privacy, we consider Oblivious…

The evolving landscape of Decentralized Finance (DeFi) has raised critical security concerns, especially pertaining to Protocols for Loanable Funds (PLFs) and their dependency on price oracles, which are susceptible to manipulation. The…

Sharing and working on sensitive data in distributed settings from healthcare to finance is a major challenge due to security and privacy concerns. Secure multiparty computation (SMC) is a viable panacea for this, allowing distributed…

We present an approach for dynamic information flow control across the application and database. Our approach reduces the amount of policy code required, yields formal guarantees across the application and database, works with existing…

The increasing adoption of Cloud storage poses a number of privacy issues. Users wish to preserve full control over their sensitive data and cannot accept that it to be accessible by the remote storage provider. Previous research was made…

Specifying legal requirements for software systems to ensure their compliance with the applicable regulations is a major concern to requirements engineering (RE). Personal data which is collected by an organization is often shared with…

The utilisation of Deep Learning (DL) raises new challenges regarding its dependability in critical applications. Sound verification and validation methods are needed to assure the safe and reliable use of DL. However, state-of-the-art…

Processing personal data is regulated in Europe by the General Data Protection Regulation (GDPR) through data processing agreements (DPAs). Checking the compliance of DPAs contributes to the compliance verification of software systems as…

ML models are ubiquitous in real world applications and are a constant focus of research. At the same time, the community has started to realize the importance of protecting the privacy of ML training data. Differential Privacy (DP) has…

An increasing number of companies have begun providing services that leverage cloud-based large language models (LLMs), such as ChatGPT. However, this development raises substantial privacy concerns, as users' prompts are transmitted to and…

Domain-specific languages (DSLs) are routinely created to simplify difficult or specialized programming tasks. They expose useful abstractions and design patterns in the form of language constructs, provide static semantics to eagerly…

The increasing adoption of Cloud-based data processing and storage poses a number of privacy issues. Users wish to preserve full control over their sensitive data and cannot accept it to be fully accessible to an external storage provider.…