相关论文: Understanding Software Developers' Approach toward…
Differential Privacy (DP) is the current gold-standard for ensuring privacy for statistical queries. Estimation problems under DP constraints appearing in the literature have largely focused on providing equal privacy to all users. We…
In recent years, technology has advanced considerably with the introduction of many systems including advanced robotics, big data analytics, cloud computing, machine learning and many more. The opportunities to exploit the yet to come…
Software logs, generated during the runtime of software systems, are essential for various development and analysis activities, such as anomaly detection and failure diagnosis. However, the presence of sensitive information in these logs…
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…
Ensuring privacy of sensitive data is essential in many contexts, such as healthcare data, banks, e-commerce, wireless sensor networks, and social networks. It is common that different entities coordinate or want to rely on a third party to…
Software security requirements have been traditionally considered as a non-functional attribute of the software. However, as more software started to provide services online, existing mechanisms of using firewalls and other hardware to…
To investigate the level of support and awareness developers possess for dealing with sensitive data in the metaverse, we surveyed developers, consulted legal frameworks, and analyzed API documentation in the metaverse. Our preliminary…
Decision-making is a key software engineering skill. Developers constantly make choices throughout the software development process, from requirements to implementation. While prior work has studied developer decision-making, the choices…
Differential Privacy (DP) is a well-established framework to quantify privacy loss incurred by any algorithm. Traditional DP formulations impose a uniform privacy requirement for all users, which is often inconsistent with real-world…
Digital and physical footprints are a trail of user activities collected over the use of software applications and systems. As software becomes ubiquitous, protecting user privacy has become challenging. With the increase of user privacy…
In this research project, we investigate an alternative to the standard cloud-centralized data architecture. Specifically, we aim to leave part of the application data under the control of the individual data owners in decentralized…
Secure development process is a procedure taken by developers to ensure the programs developed are following the general security standards and will always be up to date so that the outcomes are well secured and obedient. As a software…
Context: Domain-Driven Design (DDD) has gained significant attention in software development for its potential to address complex software challenges, particularly in the areas of system refactoring, reimplementation, and adoption. Using…
Mini-app is an emerging form of mobile application that combines web technology with native capabilities. Its features, e.g., no need to download and no installation, have made it popular rapidly. However, privacy issues that violate the…
In this paper we define the notion of a privacy design strategy. These strategies help IT architects to support privacy by design early in the software development life cycle, during concept development and analysis. Using current data…
Nowadays, intelligent systems and services are getting increasingly popular as they provide data-driven solutions to diverse real-world problems, thanks to recent breakthroughs in Artificial Intelligence (AI) and Machine Learning (ML).…
Most modern software products incorporate open-source components, requiring development teams to maintain compliance with each component's licenses. Noncompliance can have significant financial, legal, and reputational repercussions.…
Deep-Learning(DL) applications have been widely employed to assist in various tasks. They are constructed based on a data-driven programming paradigm that is different from conventional software applications. Given the increasing popularity…
Nowadays, privacy has become a very serious issue with smart and mobile platforms. Users tend to allow intrusive apps access much sensible information without really knowing the potential threats. To solve this issue several solutions (e.g.…
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…