Related papers: Balancing Isolation and Sharing of Data for Third-…
The amount of personal information unwillingly exposed by users on online social networks is staggering, as shown in recent research. Moreover, recent reports indicate that these networks are infested with tens of millions of fake users…
Business Collaboration Platforms like Microsoft Teams and Slack enable teamwork by supporting text chatting and third-party resource integration. A user can access online file storage, make video calls, and manage a code repository, all…
Privacy-preservation for sensitive data has become a challenging issue in cloud computing. Threat modeling as a part of requirements engineering in secure software development provides a structured approach for identifying attacks and…
In many systems privacy of users depends on the number of participants applying collectively some method to protect their security. Indeed, there are numerous already classic results about revealing aggregated data from a set of users. The…
Pushed by market forces, software development has become fast-paced. As a consequence, modern development projects are assembled from 3rd-party components. Security & privacy assurance techniques once designed for large, controlled updates…
In modern information systems different information features, about the same individual, are often collected and managed by autonomous data collection services that may have different privacy policies. Answering many end-users' legitimate…
The greatest advantage that Web3 applications offer over Web 2.0 is the evolution of the data access layer. Opaque, centralized services that compelled trust from users are replaced by trustless, decentralized systems of smart contracts.…
We present the design and implementation of the PeerShare, a system that can be used by applications to securely distribute sensitive data to social contacts of a user. PeerShare incorporates a generic framework that allows different…
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…
Identity Management is becoming more and more important in business systems as they are opened for third parties including trading partners, consumers and suppliers. This paper presents an approach securing a system without any knowledge of…
In the electricity grid, networked sensors which record and transmit increasingly high-granularity data are being deployed. In such a setting, privacy concerns are a natural consideration. We present an attack model for privacy breaches,…
The transparency and privacy behavior of mobile browsers has remained widely unexplored by the research community. In fact, as opposed to regular Android apps, mobile browsers may present contradicting privacy behaviors. On the one end,…
Mobile cloud computing is a new technology that enhances smartphone applications capabilities in terms of performance, energy efficiency, and execution support. These features are achieved via computation offloading technique that is…
Many proximity-based mobile social networks are developed to facilitate connections between any two people, or to help a user to find people with matched profile within a certain distance. A challenging task in these applications is to…
The vigorous development of the Internet has spurred exponential data growth, yet data is predominantly stored in isolated user entities, hampering its full value realization. In large-scale deployment of ``AI+industries'' such as smart…
Personal sensory data is used by context-aware mobile applications to provide utility. However, the same data can also be used by an adversary to make sensitive inferences about a user thereby violating her privacy. We present DEEProtect, a…
Cloud computing as a potential paradigm offers tremendous advantages to enterprises. With the cloud computing, the market's entrance time is reduced, computing capabilities is augmented and computing power is really limitless. Usually, to…
We examine machine learning models in a setup where individuals have the choice to share optional personal information with a decision-making system, as seen in modern insurance pricing models. Some users consent to their data being used…
By regularly querying Web search engines, users (unconsciously) disclose large amounts of their personal data as part of their search queries, among which some might reveal sensitive information (e.g. health issues, sexual, political or…
Application size and complexity are the underlying cause of numerous security vulnerabilities in code. In order to mitigate the risks arising from such vulnerabilities, various techniques have been proposed to isolate the execution of…