Cybersecurity has been in the spotlight the past few years. There’ve been many public reports of hackers infiltrating large companies and stealing sensitive customer and insider information. These attacks will only continue to rise in 2021, including Ransomware that can lock a computer until you pay the hacker.
AI is well-suited to solving some of the world’s most complex issues, and cybersecurity is undoubtedly one of them. Machine learning and AI may be used to “keep up with the bad guys” in today’s ever-evolving cyber-attacks and proliferation of gadgets, automating threat detection and responding more effectively than traditional software-driven techniques.
 
At the same time, cybersecurity presents some unique challenges:
  • A vast attack surface
  • 10s or 100s of thousands of devices per organization
  • Hundreds of attack vectors
  • Big shortfalls in the number of skilled security professionals
  • Masses of data that have moved beyond a human-scale problem
Many of these issues should be solved by a self-learning, AI-based cybersecurity posture management system. There are technologies available to correctly train a self-learning system to acquire data from across your corporate information systems in a continual and autonomous manner. Following that, the data is processed and used to conduct pattern correlation across millions to billions of signals relevant to the enterprise attack surface.

The result is new levels of intelligence feeding human teams across diverse categories of cybersecurity, including:
IT Asset Inventory: obtaining a comprehensive and accurate list of all devices, users, and apps having access to information systems In inventory, categorization and assessment of business criticality are also important.
Threat Exposure – hackers follow trends just like everyone else, so what’s fashionable with hackers changes regularly. AI-based cybersecurity systems can provide up to date knowledge of global and industry specific threats to help make critical prioritization decisions based not only on what could be used to attack your enterprise, but based on what is likely to be used to attack your enterprise.

Controls Effectiveness: To maintain a strong security posture, it’s critical to understand the impact of the various security tools and processes you’ve implemented. AI can help understand where your infosec program has strengths, and where it has gaps.

Breach Risk Prediction: AI-based solutions can anticipate how and where you are most likely to be hacked by taking into account IT asset inventory, threat exposure, and controls efficacy, allowing you to allocate resources and tools to areas of vulnerability. Prescriptive insights obtained from AI analysis may assist you in configuring and improving policies and procedures to increase your organization’s cyber resilience in the most efficient way possible.

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