Everyone seemingly is complaining about the spread of ransomware, and now somebody is trying to do something about it using machine learning-based behavioral analytics techniques to track suspicious behavior on company networks. As the scale of the ransomware threat grows, including ransom payments by hospitals and universities and growing fears that it will soon spread to other sectors, a Silicon Valley security intelligence firm has rolled out an approach for detecting ransomware via machine learning. Exabeam, a specialist in user and "entity" behavior analytics based in San Mateo, Calif., unveiled its analytics approach to detecting ransomware attacks during a security conference this week. The early warning system is touted as being able to spot ransomware activity on corporate networks without relying on third-party security controls. The platform also can spot suspicious activity within cloud services, servers and, increasingly, personal devices connected to corporate and other enterprise IT infrastructure.

File-encrypting ransomware programs have become one of the biggest threats to corporate networks worldwide and are constantly evolving by adding increasingly sophisticated detection-evasion and propagation techniques. In a world where any self-respecting malware author makes sure that his creations bypass antivirus detection before releasing them, enterprise security teams are forced to focus on improving their response times to infections rather than trying to prevent them all, which is likely to be a losing game. Exabeam, a provider of user and entity behavior analytics, believes that machine-learning algorithms can significantly improve ransomware detection and reaction time, preventing such programs from spreading inside the network and affecting a larger number of systems. Because the decryption price asked by ransomware authors is calculated per system, isolating affected computers as soon as possible is critical. Only last week the University of Calgary announced that it paid 20,000 Canadian dollars (around US 15,600) to ransomware authors to get the decryption keys for multiple systems.

In a world where any self-respecting malware author makes sure that his creations bypass antivirus detection before releasing them, enterprise security teams are forced to focus on improving their response times to infections rather than trying to prevent them all, which is likely to be a losing game. Exabeam, a provider of user and entity behavior analytics, believes that machine-learning algorithms can significantly improve ransomware detection and reaction time, preventing such programs from spreading inside the network and affecting a larger number of systems. Because the decryption price asked by ransomware authors is calculated per system, isolating affected computers as soon as possible is critical. Only last week the University of Calgary announced that it paid 20,000 Canadian dollars (around US 15,600) to ransomware authors to get the decryption keys for multiple systems. Exabeam's Analytics for Ransomware, a new product that was announced today, uses the company's existing behavior analytics technology to detect ransomware infections shortly after they occur.

File-encrypting ransomware programs have become one of the biggest threats to corporate networks worldwide and are constantly evolving by adding increasingly sophisticated detection-evasion and propagation techniques. In a world where any self-respecting malware author makes sure that his creations bypass antivirus detection before releasing them, enterprise security teams are forced to focus on improving their response times to infections rather than trying to prevent them all, which is likely to be a losing game. Exabeam, a provider of user and entity behavior analytics, believes that machine-learning algorithms can significantly improve ransomware detection and reaction time, preventing such programs from spreading inside the network and affecting a larger number of systems. Because the decryption price asked by ransomware authors is calculated per system, isolating affected computers as soon as possible is critical. Only last week the University of Calgary announced that it paid 20,000 Canadian dollars (around US 15,600) to ransomware authors to get the decryption keys for multiple systems.

File-encrypting ransomware programs have become one of the biggest threats to corporate networks worldwide and are constantly evolving by adding increasingly sophisticated detection-evasion and propagation techniques. In a world where any self-respecting malware author makes sure that his creations bypass antivirus detection before releasing them, enterprise security teams are forced to focus on improving their response times to infections rather than trying to prevent them all, which is likely to be a losing game. Exabeam, a provider of user and entity behavior analytics, believes that machine-learning algorithms can significantly improve ransomware detection and reaction time, preventing such programs from spreading inside the network and affecting a larger number of systems. Because the decryption price asked by ransomware authors is calculated per system, isolating affected computers as soon as possible is critical. Only last week the University of Calgary announced that it paid 20,000 Canadian dollars (around US 15,600) to ransomware authors to get the decryption keys for multiple systems.

Recently a Quebec arts foundation required the Francophone rap group Dead Obies to give back an 18,000 grant they'd been awarded to record their newest album. A word count determined that the group had stirred too much English into their distinctive multilingual lyrics, falling short of the rule that 70 percent of the content be in French. Dough to get I got more shows to rip Dead-O on the road again, c'est mon tour de get Sous le spotlight, viens donc voir le dopest set We just gettin' started et pis t'es captivated Looking at me now, thinking: «How'd he made it?» Dead Obies is used to catching flak for their language mixing. In 2014, they were excoriated by several French-language journalists for their mongrel lyrics. Christian Rioux, writing for Le Devoir, suggested that such language practices were "suicidal" and would likely result in the formation of a "mediocre creole" incomprehensible to speakers of proper French or English.

You may have heard the news lately from Guangzhou, China about the firing of robots as waitstaff. Out of three restaurants that used robots to serve customers, two have closed and the third fired its robot workers. The robots couldn't effectively handle soup dishes, often malfunctioned, and had to follow a fixed route that sometimes resulted in clashes. A customer also claimed that robots were unable to do tasks such as topping up water or placing a dish on the table. "The robots weren't able to carry soup or other food steady and they would frequently break down. The boss has decided never to use them again," said one employee.

Larry Doherty was in good hands, steady hands, like the metal ones you can find on an automaker's assembly line. The 64-year-old bean salesman from Bow Island, Alta., had come to the University of Calgary's Department of Clinical Neurosciences and Hotchkiss Brain Institute to undergo arteriovenous malformation surgery – to untie the tangled blood vessels in his brain. When everyone in the operating room was ready, the operating surgeon began his work sitting in a whole other room surrounded by computer monitors, including one with a 3-D image of Mr. Doherty's brain. Using specially designed hand controls, Dr. Garnette Sutherland manoeuvred the robot to its ready position. For Mr. Doherty, it was the first time in his life he had undergone surgery.

The usually sensible people at MIT's Senseable City Lab are looking at the future of the traffic light in the world of the self-driving car, and predict that its days are numbered. Instead, they propose a "slot-based intersections that could replace traditional traffic lights, significantly reducing delays, make traffic patterns more efficient, and lower fuel consumption." It's based on the principle that if all the self-driving cars are communication with each other and know they all are, they can plan speeds and courses so that they essentially pass through each other. Upon approaching an intersection, a vehicle automatically contacts a traffic management system to request access. Each self-driving vehicle is then assigned an individualized time or "slot" to enter the intersection.

The Lost World: Jurassic Park 1997 AMC Sun. Tomorrow Never Dies 1997 EPIX Wed. 10 p.m., Thur. The X-Files: Fight the Future 1998 IFC Thur. Hard to Kill 1990 Sundance Mon. 8 p.m., Tue. A scientist gives his bodyguard superhuman powers in order to fight racists. A lawyer unwittingly becomes friends with an unstable woman who has a criminal history. A successful businesswoman puts her family, career and life on the line to satisfy her addiction to sex. With his father trapped in the wreckage of their spacecraft, a youth treks across Earth's now-hostile terrain to recover their rescue beacon and signal for help. In the future a cutting-edge android in the form of a boy embarks on a journey to discover his true nature. An 11-year-old boy experiences the worst day of his young life but soon learns that he's not alone when other members of his family encounter their own calamities. A struggling writer falls in love with a stenographer while trying to finish his new novel in 30 days.