Related papers: Secure and Privacy-Preserving Authentication for D…
Local Differential Privacy (LDP) provides provable privacy protection for data collection without the assumption of the trusted data server. In the real-world scenario, different data have different privacy requirements due to the distinct…
Industrial control systems are a fundamental component of critical infrastructure networks (CIN) such as gas, water and power. With the growing risk of cyberattacks, regulatory compliance requirements are also increasing for large scale…
Privacy directly concerns the user as the data owner (data- subject) and hence privacy in systems should be implemented in a manner which concerns the user (user-centered). There are many concepts and guidelines that support development of…
Security monitoring via ubiquitous cameras and their more extended in intelligent buildings stand to gain from advances in signal processing and machine learning. While these innovative and ground-breaking applications can be considered as…
Public access to digital data can turn out to be a cause of undesirable information disclosure. That's why it is vital to somehow protect the data before publishing. There exist two main subclasses of such a task, namely, providing…
Nowadays, a large amount of user privacy-sensitive data is outsourced to the cloud server in ciphertext, which is provided by the data owners and can be accessed by authorized data users. When accessing data, the user should be assigned…
On the Internet large service providers tend to control the digital identities of users. These defacto identity authorities wield significant power over users, compelling them to comply with non-negotiable terms, before access to services…
Data anonymization is an approach to privacy-preserving data release aimed at preventing participants reidentification, and it is an important alternative to differential privacy in applications that cannot tolerate noisy data. Existing…
Recently, with the support of mobile cloud computing, a large number of health related data collected from various body sensor networks can be managed efficiently. However, to ensure data security and data privacy in cloud-integrated body…
Privacy-preserving computer vision is an important emerging problem in machine learning and artificial intelligence. Prevalent methods tackling this problem use differential privacy (DP) or obfuscation techniques to protect the privacy of…
In the international development community, the term "digital public goods" is used to describe open-source digital products (e.g., software, datasets) that aim to address the United Nations (UN) Sustainable Development Goals. DPGs are…
In password-based authentication systems, the username fields are essentially unprotected, while the password fields are susceptible to attacks. In this article, we shift our research focus from traditional authentication paradigm to the…
The protection of personal data has become a central topic in software development, especially with the implementation of the General Data Protection Law (LGPD) in Brazil and the General Data Protection Regulation (GDPR) in the European…
Data privacy is critical in instilling trust and empowering the societal pacts of modern technology-driven democracies. Unfortunately, it is under continuous attack by overreaching or outright oppressive governments, including some of the…
Privacy-preservation policies are guidelines formulated to protect data providers private data. Previous privacy-preservation methodologies have addressed privacy in which data are permanently stored in repositories and disconnected from…
Modern cyber physical systems (CPSs) has widely being used in our daily lives because of development of information and communication technologies (ICT).With the provision of CPSs, the security and privacy threats associated to these…
The General Data Protection Regulation (GDPR) provides new rights and protections to European people concerning their personal data. We analyze GDPR from a systems perspective, translating its legal articles into a set of capabilities and…
Outsourcing databases, i.e., resorting to Database-as-a-Service (DBaaS), is nowadays a popular choice due to the elasticity, availability, scalability and pay-as-you-go features of cloud computing. However, most data are sensitive to some…
Context: Consistent requirements and system specifications are essential for the compliance of software systems towards the General Data Protection Regulation (GDPR). Both artefacts need to be grounded in the original text and conjointly…
Differential privacy is an information theoretic constraint on algorithms and code. It provides quantification of privacy leakage and formal privacy guarantees that are currently considered the gold standard in privacy protections. In this…