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Technology that predicts your next security fail

Sandra Gittlen | Sept. 16, 2015
In 2013, the IRS paid out US$5.8 billion in refunds for tax filings it later realized were fraudulent, according to a 2015 report by the Government Accountability Office.

The key, Calatayud says, is to have performed crisis management tabletop exercises with necessary departments -- legal, HR, the privacy/compliance team, communications, external law enforcement and IT -- so that when suspicious activity occurs, there can be a swift response. If a threshold of alarms trip on a Surescripts employee, that person can be removed from the company within four hours, he says.

Without a rapid response, though, predictive analytics can become a liability in an organization's security portfolio. "You can't continue to acquire security technology and not be able to react to it," Calatayud says.

A build-your-own solution

Jason O'Connor, vice president of analysis and mission solutions at defense contractor Lockheed Martin, says the number of data sources that can be culled to detect threats can be overwhelming to many organizations -- especially as social media use grows.

"As the threats become near real-time, countering them needs to be faster than that; it needs to be predictive," he says. "With nearly every major geopolitical event that's happened in the past decade, there has been a tremendous amount of information present on the Internet."

Seven years ago, Lockheed Martin approached this challenge by using its own mathematicians and scientists to develop an analytics engine that now can predict a broad range of events such as social unrest and biological outbreaks. "We not only wanted to see what was going on tactically, but to find characteristics and signals in the data that could infer or assess an outcome," O'Connor says.

After succeeding internally, Lockheed Martin marketed the analytics engine commercially as LM Wisdom to its suppliers and other partners. The company is still using LM Wisdom internally for critical security issues such as supply chain analytics.

Lockheed Martin has thousands of suppliers that help make platforms or products -- all of them channels that introduce risk. The company monitors suppliers for counterfeit parts and materials, including their social media feeds, websites and Internet marketplaces. LM Wisdom's predictive model evaluates the likelihood of a seller being a counterfeit.

"No supplier is going to say 'come buy counterfeit parts,' but LM Wisdom can study the linguistics features of content and marketing materials as well as the types of things a supplier sells," O'Connor says. Employees can then use a system-generated matrix to verify trusted suppliers and avoid counterfeits, reducing the risk associated with delivery of parts, integrity of parts and exposure to bad suppliers.

Early warning to protect people

Predictive analytics also can be used to protect human assets, such as volunteers for international aid organizations or employees of global oil and gas companies. In certain regions, workers are kidnapped and held for millions of dollars in ransom. By monitoring local social media feeds of political groups, news outlets and the like, organizations can detect unrest near outposts and tell workers to stay inside a protected zone, according to Luca Scagliarini, CEO of intelligence software maker Expert System USA.

 

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