A Dose of AI Could Be the Cure for Hospital Data Center Cyberattacks in 2017

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I know how terrible healthcare records theft can be. I myself have been the victim of a data theft by hackers who stole my deceased father's medical files, running up more than $300,000 in false charges. I am still disputing on-going bills that have been accruing for the last 15 years. This event led me on the path to finding a solution so others would not suffer the consequences that I continue to be impacted by, but hospitals and other healthcare providers must be willing to make the change. The writing is on the wall.


Security looks to machine learning technology for a cognitive leg up

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Keen Footwear sells its iconic boots, shoes and sandals through thousands of retailers worldwide. But the Oregon manufacturer, which is working hard to honor its commitment to become "American Built," does not have the manpower to support a dedicated information security staff. With a team of six information technology professionals -- all but two focused on handling the day-to-day client issues of its 450 employees -- the IT staff would fall behind in triaging incidents the company's security software flagged. "We fit squarely in the realm that we have the problems of all the big players, but we don't have the resources of a large enterprise," said Clark Flannery, Keen's director of IT in Portland. To solve the problem, Flannery augmented his IT staff with machines.


Artificial Intelligence in Cybersecurity – Current Use-Cases and Capabilities Emerj

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Raghav serves as Content Lead at Emerj, covering our major industry areas and conducting research. Raghav has a personal interest in robotics, and previously worked for research firms like Frost & Sullivan and Infiniti Research. AI has made some inroads in the cybersecurity sector and several AI vendors claim to have launched products that use AI to help safeguard against cyber threats. At Emerj, we've seen many cybersecurity vendors offering AI and machine learning-based products to help identify and deal with cyber threats. Even the Pentagon created the Joint Artificial Intelligence Center (JAIC) to upgrade to AI-enabled capabilities in their cybersecurity efforts.


Anomaly Detection with Unsupervised AI in MixMode: Why Threat Intel Alone is Not Enough - MixMode

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Historically, the MixMode platform has provided its users with a forensic hunting platform with intel-based Indicators and Security Events from public & proprietary sources. While these detections still have their place in the security ecosystem, the increase in state-sponsored attacks, insider threats and adversarial artificial intelligence means there are simply too many threats to your network to rely on solely intelligence-based detections or proactive hunting. Many of these threats are sophisticated enough to evade traditional threat detection or, in the case of zero-day threats, signature-based detection may not even be possible. In the face of this growing threat, the best defense is to supplement these traditional methods with anomaly detection, a term that is quickly becoming genericized as it is rapidly bandied about within the industry. Here we will discuss some of the opportunities and challenges that can arise with anomaly detection as well as MixMode's unique approach to the solution.


How advanced analytics can shore up defenses against data theft

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Since cyberattacks on hospital EHR systems have become a topic of nightly newscasts, no longer is anyone shocked by their scope and veracity. What is shocking is the financial damage the attacks are predicted to cause. During this past June, more than 11 million patient EHRs were breached, making it the year's worst incident according to a study by DataBreaches.net For comparison, May had less than 700,000 records breached, and records breached in March topped out at slightly more than 2.5 million. While traditional security filters like firewalls and reputation lists are good practice, they are no longer enough.