The 2017 DefCon conference featured former World Chess Champion Garry Kasparov, who spoke about artificial intelligence, computers, and of course, chess.  After losing a match to a purpose-built computer in 1997, Kasparov realized that the machine, although it had beaten him, was not truly intelligent:  it had simply out-calculated him, by examining over 200 million chess positions per second.  Kasparov soon devised “advanced chess”, in which a strong human player teams up with a computer.   Advanced chess combines the best human qualities of imagination, judgment,

It will come as no surprise to anyone that 2016 saw an alarming increase in targeted attacks aimed at politically motivated sabotage and subversion. This new level of ambition by cyber criminals is corroborated by the annual Internet Security Threat Report from DLT partner, Symantec. The perceived success of several campaigns – particularly the U.S.

Data breach statistics are staggering. Through the end of March 2017, there have already been over 300 major breaches and over nine million records stolen. It’s a challenging problem and one that doesn’t come with a lot of solutions. Part of the problem is understanding what the patterns are. Today’s attacks have several stages from initial reconnaissance to object completion, as depicted in the Cyber Kill Chain which describes the phases of a targeted attack.

The history of hacking shows that bad actors use good technologies for bad purposes.  Machine learning is no different: it has never been easier for white hats and black hats to obtain and learn the tools of the machine learning trade. Software is readily available at little or no cost, and machine learning tutorials are just as easy to obtain.