An Indian textile baron has revealed that he was duped out of 70 million rupees ( 833,000) by online scammers impersonating federal investigators and even the Supreme Court chief justice. The fraudsters posing as officers from India's Central Bureau of Investigation (CBI) called SP Oswal, chairman and managing director of the textile manufacturer Vardhman, on August 28 and accused him of money laundering. For the next two days, Oswal was under digital surveillance as he was ordered to keep Skype open on his phone 24/7 during which he was interrogated and threatened with arrest. The fraudsters also conducted a fake virtual court hearing with a digital impersonation of Chief Justice of India DY Chandrachud as the judge. Oswal paid the amount after the court verdict via Skype without realising that he was the latest victim of an online scam using a new modus operandi, called "digital arrest".

Palo Alto Networks has released next-generation firewall (NGFW) software that integrates machine learning to help protect enterprise traffic to and from hybrid clouds, IoT devices and the growing numbers of remote workers. The machine learning is built into the latest version of Palo Alto's firewall operating system – PAN 10.0 – to prevent real-time signatureless attacks and to quickly identify new devices – in particular IoT products – with behavior-based identification. NGFWs include traditional firewall protections like stateful packet inspection but add advanced security judgments based on application, user and content. "Security attacks are continually morphing at rapid pace and traditional signature-based security approaches cannot keep up with the millions of new devices, running a variety of operating systems and software stacks coming on the network," said Anand Oswal senior vice president and GM at Palo Alto. "IoT devices, which are growing exponentially, exacerbated that issue because they have so many of their own different agents, patches and OS's it's impossible to set security policies around them." Oswal said the ML in its new NGFW uses inline machine-learning models to identify variants of known attacks as well as many unknown cyberthreats to prevent up to 95% of zero-day malware in real time.