Fight "Blacklist" criminals using real-time actionable intelligence
If you are familiar with the hit NBC TV-series The Blacklist, you may remember the opening scenes in a recent episode showing FBI Agent Elizabeth Keen's hotel room wall covered with a complicated web of information related to her ex-husband, Tom. By way of a visual metaphor, this is what intelligence looks like: connecting events to identities and then more entities, all in an effort to build a comprehensive understanding of a threatscape.
Unfortunately, today’s threatscape contains so much data that Agent Keen's wall would never be able to hold it. That’s where advanced big data intelligence analysis solutions come in. These solutions help agencies and analysts collect, compile, organize and simplify massive and disparate data sets so they can uncover hidden connections and patterns that can be used to disrupt and prevent criminal and terrorist acts. As threats continue to grow in number and gravity, these kinds of solutions are more critical than ever.
Just as technology continues to simplify and shrink our world as consumers, it does the same for nefarious individuals and networks. Online transactions, social media, mobile technology and the Internet of Things all provide the real “blacklist” criminals with more access to critical infrastructure, sensitive data and additional bad actors. Essentially, all the technology advances we enjoy as consumers are providing more opportunities to nefarious individuals and networks. But are we willing to forgo the conveniences and gadgets we’ve come to rely on in order to stop these potential crimes?
This discussion is not new, and the public policy debate will likely play out for the foreseeable future. The good news is, we have solutions that will help us turn Lizzie’s wall into actionable intelligence now and put the criminal world at the intelligence community’s fingertips.
Learn more about how IBM i2 Enterprise Insight Analysis can help your organization generate actionable intelligence in near real-time.