Artificial intelligence (AI) is coupling with cybersecurity in order to create a new genre of tools known as threat analytics. Machine learning is allowing threat analytics to deliver greater precision in the areas of risk context, explicitly involving the behavior of privileged users, states a recent account in Forbes. This approach can be leveraged to develop notifications in real-time and respond actively to the incidents by cutting off sessions. FREMONT, CA: The general notion is that hackers have gone to the dark side to plan a massive attack on vulnerable businesses. Still, the truth is that the companies are not protecting their access credentials from easy hacks.

Bottom line: Machine learning is enabling threat analytics to deliver greater precision regarding the risk context of privileged users' behavior, creating notifications of risky activity in real time, while also being able to actively respond to incidents by cutting off sessions, adding additional monitoring, or flagging for forensic follow-up. A commonly-held misconception or fiction is that millions of hackers have gone to the dark side and are orchestrating massive attacks on any and every business that is vulnerable. The facts are far different and reflect a much more brutal truth, which is that businesses make themselves easy to hack into by not protecting their privileged access credentials. Cybercriminals aren't expending the time and effort to hack into systems; they're looking for ingenious ways to steal privileged access credentials and walk in the front door. According to Verizon's 2019 Data Breach Investigations Report, 'Phishing' (as a pre-cursor to credential misuse), 'Stolen Credentials', and'Privilege Abuse' account for the majority of threat actions in breaches (see page 9 of the report).

Our patent pending AI platform and threat hunters continuously scour your entire IT stack for threats. We combine Endpoint Detection and Response (EDR), User Behavior Analytics (UEBA), Network Threat Analytics (NTA and NFT) and Application Threat Analytics (ATA) on a single platform. Analytics done in silos isn't capable of uncovering blended threats – only a unified application of AI on all data protects you from modern threats.

From car hacks to connected homes, every aspect of our lives is vulnerable to cyber crime. But AI research and deep learning is working to keep us safe. It's now over 18 months since Charlie Miller and Chris Valasek carried out the infamous remote Jeep hack that led to the recall of 1.4 million vehicles. They remotely killed the power of a Jeep on the highway and disabled the brakes at low speed. Things have since gone quiet, so is it safe to assume that the cars we drive and the homes we increasingly connect are safe?

Trying to discern drug smugglers passing through customs presents exactly the same problem as trying to discern security threats passing through our networks. Machine learning has been applied to both with varying degrees of success, but ultimately the technology reaches the same limitations. Machine learning has two basic elements: feature vectors and classification exemplars -- the data that is gathered and the corresponding classification examples. In the case of drug smugglers, we might observe number of travelers, point of origin, point of destination, number of bags, length of stay and weight of the bags. We might also flag any traveler or pair of travelers with two or more bags whose combined weight is greater than 150 pounds, whose stay is less than a week and who originated from a climate conducive to poppies.

Trying to discern drug smugglers passing through customs presents exactly the same problem as trying to discern security threats passing through our networks. Machine learning has been applied to both with varying degrees of success, but ultimately the technology reaches the same limitations. Machine learning has two basic elements: feature vectors and classification exemplars -- the data that is gathered and the corresponding classification examples. In the case of drug smugglers, we might observe number of travelers, point of origin, point of destination, number of bags, length of stay and weight of the bags. We might also flag any traveler or pair of travelers with two or more bags whose combined weight is greater than 150 pounds, whose stay is less than a week and who originated from a climate conducive to poppies.