Jazz Networks won the U.S. Cyber Command insider threat competition against some of the top insider threat, EDR, UBA, and SIEM vendors. DreamPort DreamPort is a cyber center with state-of-the-art facilities and innovative programs which aims to fuel innovation that leads to “unparalleled capability for U.S. Cyber Command and the warfighters at large”. United States Cyber Command (USCYBERCOM) created DreamPort through a Partner Intermediary Agreement awarded to Maryland Innovation & Security Institute (MISI).
Data is the most important asset of any company, and the uphill battle of protecting it can seem never ending. Traditional data loss prevention (DLP) solutions focus on the data: classifying it, authorizing access, and monitoring usage in accordance with policies. However, data loss is only the symptom. The root of the problem lies with the unpredictable nature of humans, either with malicious or, more commonly, negligent behavior. Attempting to classify thousands – or millions – of changing data records while simultaneously monitoring human users is a tough feat.
Machine learning has never been more prevalent or accessible than it is today. It is a phenomenon that is transforming how we interact with businesses, devices, and each other. From retailers and advertisers recommending appropriate products and email providers detecting spam, to cars that can drive themselves, and phones that recognize their owner’s face. Meanwhile artificial intelligence and machine learning must be the two most misunderstood concepts in tech today.
By the time you finish reading this sentence, the average organization with 1000 employees will have generated more than 65,500 log events from all of the devices connected to their network.* This might be 65,500 login attempts, files deleted, or files that contain personally identifiable information (PII) copied to a USB device by an employee working without VPN on the road. With the EU general data protection regulation (GDPR) going into full effect this week, understanding the difference and interpreting the implications of each scenario quickly and efficiently is necessary in order to be compliant with Article 33.
Most companies recruit employees who they believe can help increase their competitive edge and innovation in their respective industries. But as these employees start adding value in their specific fields, it is imperative that they understand how to protect corporate data. Failing to protect intellectual property (IP) doesn’t just jeopardize the company—the employee’s job security, equity, career direction, and reputation are also at risk. Protecting intellectual property is equally important to the employee as the company they work for.