To quantify trade-offs between increasing demand for open data sharing and concerns about sensitive information disclosure, statistical privacy (SDP) methodology analyzes release mechanisms that sanitize outputs based on confidential data. Two dominant frameworks exist: disclosure control (SDC) the more recent differential (DP). Despite framing differences, both SDC DP share same problems at th...

The issue of online privacy and security is a challenging subject, as it concerns the privacy of data that are increasingly more accessible via the internet. In other words, people who intend to access the private information of other users can do so more efficiently over the internet. This study is an attempt to address the privacy issue of distributed big data in the context of cloud computin...

There are some critical privacy concerns in the current online social networks (OSNs). Users' information is disclosed to different entities that they were not supposed to access. Furthermore, the notion of friendship is inadequate in OSNs since the degree of social relationships between users dynamically changes over the time. Additionally, users may define similar privacy settings for their f...

The emerging public awareness and government regulations of data privacy motivate new paradigms collecting analyzing that are transparent acceptable to owners. We present a concept corresponding formats, mechanisms, theories for privatizing during collection. privacy, named Interval Privacy, enforces the raw conditional distribution on privatized be same as its unconditional over nontrivial sup...