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Code review is a critical step in the software development life cycle, which assesses and boosts the code's effectiveness and correctness, pinpoints security issues, and raises its quality by adhering to best practices. Due to the increased…
Nowadays, machine learning models and applications have become increasingly pervasive. With this rapid increase in the development and employment of machine learning models, a concern regarding privacy has risen. Thus, there is a legitimate…
Users care greatly about preserving the privacy of their personal data gathered during their use of information systems. This extends to both the data they actively provide in exchange for services as well as the metadata passively…
This work aims to show the applicability, and how, of privacy by design approach to biometric systems and the benefit of using formal methods to this end. Starting from a general framework that has been introduced at STM in 2014, that…
In recent years, the number of cyber attacks has grown rapidly. An effective way to reduce the attack surface and protect software is adoption of methodologies that apply security at each step of the software development lifecycle. While…
Research shows that analysts and developers consider privacy as a security concept or as an afterthought, which may lead to non-compliance and violation of users' privacy. Most current approaches, however, focus on extracting legal…
Due to the prevalence of online services in modern society, such as internet banking and social media, it is important for users to have an understanding of basic security measures in order to keep themselves safe online. However, users…
There currently exists a wide range of techniques to model and evolve artificial players for games. Existing techniques range from black box neural networks to entirely hand-designed solutions. In this paper, we demonstrate the feasibility…
End-users seldom read verbose privacy policies, leading app stores like Google Play to mandate simplified data safety declarations as a user-friendly alternative. However, these self-declared disclosures often contradict the full privacy…
This paper aims to improve privacy-preserving visual recognition, an increasingly demanded feature in smart camera applications, by formulating a unique adversarial training framework. The proposed framework explicitly learns a degradation…
Gamification frameworks can aid in gamification planning for education. Most frameworks, however, do not provide ways to select, relate or recommend how to use game elements, to gamify a certain educational task. Instead, most provide a…
Ensuring equitable privacy experiences remains a challenge, especially for marginalised and vulnerable populations (MVPs) who often hesitate to participate or use digital services due to concerns about the privacy of their sensitive…
As software becomes more complex and assumes an even greater role in our lives, formal verification is set to become the gold standard in securing software systems into the future, since it can guarantee the absence of errors and entire…
Federated learning (FL) enhances privacy by keeping user data on local devices. However, emerging attacks have demonstrated that the updates shared by users during training can reveal significant information about their data. This has…
Background: Governments worldwide are considering data privacy regulations. These laws, e.g. the European Union's General Data Protection Regulation (GDPR), require software developers to meet privacy-related requirements when interacting…
The use of machine learning (ML) has become increasingly prevalent in various domains, highlighting the importance of understanding and ensuring its safety. One pressing concern is the vulnerability of ML applications to model stealing…
Although Large Language Models (LLMs) have become increasingly integral to diverse applications, their capabilities raise significant privacy concerns. This survey offers a comprehensive overview of privacy risks associated with LLMs and…
Organizations struggle to comply with legal requirements as well as customers calls for better data protection. On the implementation level, incorporation of privacy protections in products and services depends on the commitment of the…
In recent years, large language models (LLMs) have made significant progress in the field of code generation. However, as more and more users rely on these models for software development, the security risks associated with code generation…
Differential Privacy (DP) has emerged as a pivotal approach for safeguarding individual privacy in data analysis, yet its practical adoption is often hindered by challenges in the implementation and communication of DP. This paper presents…