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AI – The Future Of Cybersecurity?

Today’s advanced technologies, including AI and machine learning, are bringing about a cybersecurity landscape in which organizations are far more protected than was possible before.

Detection and elimination of traditional threats and zero-day exploits must rely on advanced data collection and analysis, machine learning, and predictive and behavioral analytics.

AI can automatically detect anomalous events without the need for new upfront rules. On the incident management, customers are drowning in false alerts – the rules triggered, but the incident turned out to be benign – an opportunity to automate this process using AI

AI and intelligent technologies do perform some lower-level remediation, such as blocking malware, they’re not mature enough to launch full-scale defenses against potential attacks. You still need humans for that.

Cybersecurity technologies – specifically AI and machine learning applications – are making headway by providing basic protections that organizations lack. Expect an arms race as hackers power up their own AI toolkits.

Due to its dynamic nature, security best practices are harder to achieve in cloud computing environments. A cloud-native approach is needed for a holistic view of security and compliance risk.

As we’ve seen in the headlines, reacting to what has already been seen or experienced is proving ineffective. With artificial intelligence, the future of predictive and preventative cybersecurity has arrived.

It’s no surprise breaches go undiscovered for 146 days on average. Companies are over-reliant on AI, machine learning, and SIEMs. The future of cybersecurity technology is the right balance between automation and intelligence.

More breaches, increasingly advanced threat actors, and higher stakes are going to require more advanced defenses and practices. AI and ML are a natural response to these ever increasing challenges.

In the very near future, both cyber attacker and cyber defenders will have AI-algorithms that adapt in near-real time, resulting into a cyber warfare with very little human intervention.

Current state – Very basic AI capabilities and cyber prevention mechanisms. Future state – we’ll start seeing more advanced techniques especially with threat protection and the increase in encryption algorithms.

AI shouldn’t start from scratch. The right framework can amplify human experience and leverage existing knowledge to automate cybersecurity threat detection and generate results that make sense.

Orchestration and automation are key, where thousands of sensors will be embedded within the corporate network, feeding data into systems determining the real threats using machine learning and anomaly detection.

Organizations must adopt a holistic view of their cyber-threat environment, and technology must evolve to minimize false positives. Security teams need these advances to properly focus on their highest-priority threats.

As companies increasingly emphasize employees as a defense layer, and with advances in ML, we’ll see more attacks detected by the combination of human and machine, rather than one alone.