Published By: LogRhythm
Published Date: Aug 08, 2016
IT environments have become much more vulnerable as enterprise mobility, cloud services and “bring-your-own-everything” have broken down the defensible perimeter and added layers of complexity to securing the enterprise. At the same time, the nature of cyber threats has changed dramatically. Threat actors are well organized and well funded, and many of them are known to be supported by nation states. They have sophisticated technical skills which allow these actors to create custom malware for very specific targets, and they are relentless in pursuit of their objectives. Moreover, almost anyone with a malicious intent can purchase malware and rent botnets on the Dark Web, lowering the bar for criminal entities, nation states, and terrorists to use cyber as a weapon of choice towards their intended purpose.
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Imagine getting into your car and saying, “Take me to work,” and then enjoying an automated
drive as you read the morning news. We are getting very close to that kind of
scenario, and companies like Ford expect to have production vehicles in the latter part
Driverless cars are just one popular example of machine learning. It’s also used in
countless applications such as predicting fraud, identifying terrorists, recommending
the right products to customers at the right time, and correctly identifying medical
symptoms to prescribe appropriate treatments.
The concept of machine learning has been around for decades. What’s new is that
it can now be applied to huge quantities of data. Cheaper data storage, distributed
processing, more powerful computers and new analytical opportunities have dramatically
increased interest in machine learning systems. Other reasons for the increased
momentum include: maturing capabilities with methods and algorithms refactored to
run in memory; the
Because terrorists and other criminals are already using technology to carry out their missions, intelligence professionals need to access all available, appropriate information, to extract important elements and process, analyze and disseminate it quickly to keep ahead of potential threats. The scale, complexity and changing nature of intelligence data can make it impossible to stay in front without the aid of technology to collect, process and analyze big data. This paper describes a solution for how this information can be quickly and safely shared with access based on a user's organizational responsibilities and need to know.
Published By: TopLayer
Published Date: Aug 21, 2009
This white paper written by Reymann Group, compliance consultant firm, showcases thought leadership on how intrusion prevention solutions can enable proactive security responses necessary to protect today's corporate enterprise and its customers from real time threats posed by widespread cyber terrorists, hackers, and rogue insiders.
This White Paper discusses how intelligence agency management can apply machine translation as a much-needed support tool that can make linguists and intelligence analysts more effective in producing meaningful and actionable results.
DatacenterDynamics is a brand of DCD Group, a global B2B media and publishing company that develops products to help senior professionals in the world's most ICT dependent organizations make risk-based infrastructure and capacity decisions.
Our portfolio of live events, online and print publishing, business intelligence and professional development brands are centred on the complexities of technology convergence. Operating in 42 different countries, we have developed a unique global knowledge and networking platform, which is trusted by over 30,000 ICT, engineering and technology professionals.
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