CUPERTINO, Calif., Dec. 10, 2012 /PRNewswire/ -- Advanced malware detection experts TaaSERA, Inc., today announced that Tom Ridge, former U.S. Secretary of Homeland Security, has joined the company's advisory board. In this role, Ridge will help guide the security software maker through its upcoming launch and further align the startup's attack behavior discovery methodology with techniques used by DHS and other law enforcement agencies to identify potential criminals and suspected terrorists. Prior to serving as the first ever Secretary of Homeland Security in 2001, Ridge served as a longtime member of the U.S. House of Representatives and was the 43rd Governor of Pennsylvania, lending further depth to his perspective on local, national and global security issues. According to Ridge, today's intelligence and law enforcement agencies continue to adopt more comprehensive electronic data analysis to identify potential suspects before they can commit crimes, and locate individuals working with known terrorist groups. Organizations throughout both the government and private sectors should embrace a similar approach to defending themselves against today's highly advanced and targeted malware attacks, adopting IT security systems that leverage behavioral analysis and data correlation in a similar fashion, he said. "Just as it's no longer sufficient to check for passports at a border crossing, or wait until someone attempts to carry out an attack to identify threats to our nation, organizations must move past traditional perimeter security models and analysis of historical data to prevent data breaches and other incidents," said Ridge. "TaaSERA will bring to market a compelling array of solutions that empower IT security professionals to understand when malicious programs are first attempting to carry out their commands, and take action before it's too late." Available in various solutions offered by TaaSERA and its partners early 2013, the company's Attack Warning and Response Engine (AWARE) leverages detailed analysis of known malware behavior characteristics to identify threats as they take shape, notably previously unseen attacks that cannot be prevented with existing signature-based AV, heuristics analysis or virtual sandbox testing solutions.