Fatiguing Data to Protect against Cyber Security Extortions: A counter-intelligence methodology

Abstract

"Now and recently, confab is less about preventing and stopping an attack, threat or exposure, and more about how swiftly you can detect that an attack is happening." There's a growing demand for security information and event management (SIEM) technologies and services, which gather and analyse security event big data that is used to manage threats. Big data offers the ability to analyse immense numbers of potential security events and make connections between them to create a prioritized list of threats. With big data, distinct data can be connected, which allows cyber security professionals to take a proactive approach that prevents attacks. Advanced Persistent Threats (APTs) are also used to find and identify where threats are coming from. Integrated security architecture and power of automated information collection and sharing between many security systems, called “Counter-intelligence” to solve the strategic short comings. “Counter intelligence” translates to new security product architecture into a data collection backbone feeding a centralized repository used to correlate security anomalies from, across multiple systems. This paper illustrates the new counter intelligence approach to defend against future cyber security threats by applying modern risk analysis and mitigation methods to protect users’ private data from big data.