A framework for semantic extraction of articles and secured storage using a3des algorithm

Abstract

The continuous elevation in the quantity of big data escalates the chances of breaching of the individual s privacy. Big data needs higher computational power as well as huge storage, for which, the distributed systems are utilized. As many parties are engaged in these systems, the threat of privacy violation is elevated. With the appearance of online social networks and the rising fame of digital communication, lots of information concerning individuals is becoming accessible on the Internet. Whilst most of this information is not sensitive, it is not rare for users to publish sensitive information online, particularly on social networking sites. The accessibility of this publicly accessible and also potentially sensitive data can cause abuse and expose users to stalking and also identity theft. An adversary can digitally stalk a victim (a Web user) and find out as much information as possible concerning the victim, either via direct scrutiny of posted information or by inferring knowledge using simple inference logic. Information Retrieval(IR) along with information privacy or security is a two proliferating computer science disciplines. IR gives a set of information seeking, analysis, organization, along with decision-making techniques. Information privacy or security defends information as of unauthorized or else malicious utilization, disclosure, modification, attack, as well as destruction. The 2 disciplines often emerge as 2 areas with opposite objectives: one is to seek information as of large sum of materials; the other is to protect (sensitive) information from being found out. Conversely, there are numerous synergies and connections betwixt these 2 disciplines newline