CISOs' time and teams are stretched too thin, keeping remote and hybrid workforces as well as the fast-growing number of machine-based endpoints secure from new, unpredictable attack patterns. Cybersecurity professionals, including CISOs, are doubtful their existing endpoint security systems can thwart an advanced attack. Fifty-five percent of cybersecurity professionals estimate that more than 75% of endpoint attacks can't be stopped with their current systems, based on a survey by Tanium.
Security teams admit they're behind on patches and often don't know if a patch will create a collision at the endpoint, leaving it less secure than before. Only 29% of security teams are very confident that the patches they're installing with stop a breach. The hardest hit by cyberattacks and ransomware last year are also among the slowest to complete endpoint patching. Absolute's 2021 Endpoint Risk Report found that retailers are on average 101 days out of date on patching endpoints, followed by healthcare at 78 days and financial services at 69 days. Self-healing endpoints are a growth catalyst for the endpoint protection platform (EPP) market, which is predicted to grow from $16 billion in 2022 to $26.4 billion in 2025, attaining an 18.1% Compound Annual Growth Rate (CAGR) in just three years. This makes it one of the fastest-growing markets in the cybersecurity industry.
Enterprises that procrastinate about patch management give cybercriminals the time to weaponize new endpoint attack strategies. Most IT and security professionals say patching takes a backseat to other tasks. Ivanti's recent survey found that 71% of IT and security leaders say it's overly complex, cumbersome, and time-consuming. Fifty-seven percent say remote work and decentralized workspaces make a challenging task even more difficult.
6 ways AI brings greater resilience to endpoints
Self-healing endpoints differ by their self-diagnostics, combined with their ability to regenerate their operating system and apps, while using AI and ML to identify suspected or actual breach attempts and thwart them. They're regenerative by design to achieve greater resilience. Self-healing endpoints shut themselves off, re-check all OS and application versioning, and then reset themselves to their specific configuration. All these activities happen autonomously while providing real-time tracking of events.
CISOs tell VentureBeat that building a business case for self-healing endpoints often involves factoring in ITSM cost and time savings, reduced security operation workloads, asset losses, and improved audit and compliance. VentureBeat sees the urgent need for endpoint security vendors to deliver greater visibility and control, more efficient workflows for rolling back malicious changes and more flexibility in re-configuring endpoints automatically back to correct configurations. A core part of CISOs' zero trust security strategies center on endpoint security, which are pivotal to current and planned digital business initiatives.
AI and ML techniques are proving to be effective core technologies for self-healing endpoints due to the following factors:
The future of self-healing endpoints
With IT and security teams stretched thin already, CISOs and CIOs need to add thousands of new endpoints to secure their growing remote and hybrid workforces. According to Forrester, their workloads are compounded with new machine identities growing twice as fast as the human ones. CISOs tell VentureBeat that the most valuable aspect of AI and ML in endpoint security is how reliable and resilient self-healing endpoints are becoming. CISOs want greater visibility and control, more efficient workflows for rolling back malicious changes and more flexibility in re-configuring endpoints automatically back to correct configurations. Add to that the need for more detailed, real-time asset management data and the future of self-healing endpoints is moving in an AI-driven direction.