"Sysdig Incorporates Machine Learning to Detect Cryptojacking Attempts"

One of the most important capabilities a security team can have is the ability to detect and respond to threats in the shortest amount of time possible. The faster they can respond to a data breach, the less disruption and operational impact there will be. The issue is that this is much easier said than done, as relying on manual administrative approaches can make it difficult to detect malicious activity in the environment and initiate a response. However, Artificial intelligence (AI) and Machine Learning (ML) technologies have the potential to accelerate an enterprise's detection and response efforts. Sysdig, a unified container and cloud security provider, has announced the release of a new ML-driven Cloud Detection and Response (CDR) solution to combat cryptojacking attempts. According to Sysdig's announcement at the Black Hat Conference, ML is a critical technology that enterprises and decision-makers can use to accelerate their efforts to detect and mitigate vulnerabilities. While the cryptocurrency market has taken a beating in recent months, malicious cryptomining remains a serious threat, with the volume of cryptojacking attacks increasing by 30 percent to 66.7 million between January and June 2022. Cryptojacking poses unique challenges for enterprise security teams because cybercriminals will use malware to hijack a target's computing resources in order to mine for cryptocurrency while remaining undetected for as long as possible. The longer they go undetected, the greater the financial benefit of the attack. Despite these efforts to avoid detection, technologies such as ML could detect and respond to cryptojacking attempts in decentralized cloud environments in real-time. Sysdig provides real-time visibility at scale to address risk across containers and multiple clouds, thus removing security blind spots. Sysdig's ML-powered solution employs a focused ML model that has been specifically trained to recognize cryptominer behavior in containers, providing deep container visibility as well as the ability to analyze process activity and other system behaviors. This article continues to discuss Sysdig's ML-powered CDR solution aimed at defending against cryptojacking attempts.

VentureBeat "Sysdig Incorporates Machine Learning to Detect Cryptojacking Attempts"