Idiomatic Expressions (IE) based Security and Éclat Learning using Privacy on Content Sharing Social Networks

Abstract

The information society has created various possibilities for remote access to the communication between distributed information resources and users. These aspects of all of the global users have used to create their data and profile. This needed data-protection is provided reliably. In most social networking sites, individuals can create an online profile that other people can see through online interaction, communication, and the basic functions share of interest. Unfortunately, social networks' current trend is to protect their online content from a system or policy administrator. The security and privacy requirements of social networking are not yet fully understood or well defined. This is an important issue that every user should ask themselves. The answer is about the principles of privacy and confidentiality. The main purpose is to discuss social media's challenges for data security as an element of privacy analysis using the Éclat learning method. This method analyses user behaviours. For this reason, the use of identifiable expressions indicates that a brief study of social media is taking place. The Idiomatic Expressions (IE) methods are proposed in the formal interpretation of the global communication security key. The key principles of personal information security are provided based on the organizational structure, life cycle and data protection policy of the Security Information Framework, especially those related to information and communication security policy