The dissolution of traditional defensive perimeters coupled with attacker's abilities to circumvent traditional security systems requires organizations to adopt an intelligence-driven security model that is more risk-aware, contextual, and agile.

Business Challenges
  • As organizations open and extend their data networks - allowing partners, suppliers and customers to access corporate information, they become more vulnerable to data misuse and theft.
  • Corporate applications and data are also increasingly accessed through cloud services and mobile devices, shattering what's left of enterprise network boundaries and introducing new information risks and threat vectors.
  • Often times, cyber-attacks or fraud schemes perpetrated by advanced adversaries aren't detected until well after damage has been done.

Organizations to move to an intelligence-driven security model, which relies on security-related information from internal and external sources to deliver a comprehensive picture of risk and security vulnerabilities. Organizations need to cultivate security capabilities that will ultimately help them detect the unknown and predict threats in the future.



Big data analytics drives Intelligence-driven security
  • will help organizations encompass both the breadth of sources and the information depth needed for programs to assess risks accurately and to defend against illicit activity and advanced cyber threats.
  • Big data analytics will disrupt the status quo in most information security product segments, including SIEM; network monitoring; user authentication and authorization; identity management; fraud detection; and governance, risk & compliance.
  • builds the data analytics tools that will help organizations enable a range of advanced predictive capabilities and automated real-time controls.
  • In the process of integrating big data analytics into business risk management and security operations, will redesign how information security programs are developed and executed.