IBM Debuts AI-Powered Threat Detection Tools

IBM has added generative artificial intelligence (AI) capabilities to its managed threat detection and response services. Built on the company’s watsonx data and AI platform, the new IBM Consulting Cybersecurity Assistant is designed to speed and improve the identification, investigation and response to critical security threats, IBM announced Monday (Aug. 5). “As cyber incidents evolve […]

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IBM has added generative artificial intelligence (AI) capabilities to its managed threat detection and response services.

Built on the company’s watsonx data and AI platform, the new IBM Consulting Cybersecurity Assistant is designed to speed and improve the identification, investigation and response to critical security threats, IBM announced Monday (Aug. 5).

“As cyber incidents evolve from immediate crises to multi-dimensional and months-long events, security teams are facing the enduring challenge of too many attacks and not enough time or people to defend against them,” said Mark Hughes, global managing partner of cybersecurity services, IBM Consulting.

“By enhancing our Threat Detection and Response services with generative AI, we can reduce manual investigations and operational tasks for security analysts, empowering them to respond more proactively and precisely to critical threats, and helping to improve overall security posture for clients,” Hughes added.

According to the release, the tool analyzes “patterns of historical, client-specific threat activity,” helping security analysts comprehend threats via “a timeline view of attack sequences.”

The assistant will also auto-recommend actions based on the patterns of analyzed activity and pre-set confidence levels, speeding response times for clients and helping to lower attackers’ dwell time.

“With the ability to continuously learn from investigations, the Cybersecurity Assistant’s speed and accuracy is expected to improve over time,” IBM said.

As PYMNTS wrote earlier this year, AI is transforming how cybersecurity teams deal with threats, automating the initial stages of incident investigation to allow security professionals to begin their work with a clear understanding of the situation, speeding up response times.

“Tools like machine learning-based anomaly detection systems can flag unusual behavior, while AI-driven security platforms offer comprehensive threat intelligence and predictive analytics,” Timothy E. Bates, chief technology officer at Lenovo, told PYMNTS in an interview.

“Then there’s deep learning, which can analyze malware to understand its structure and potentially reverse-engineer attacks. These AI operatives work in the shadows, continuously learning from each attack to not just defend but also to disarm future threats,” he added.

These efforts are happening amid a wave of cybersecurity challenges in the U.S., where 82% of large merchants reported data and cyber breaches over the past year, according to the PYMNTS Intelligence report “Fraud Management in Online Transactions.”

“The report found that there is a need for stronger anti-fraud strategies and enhanced cybersecurity measures to safeguard cross-border transactions,” PYMNTS wrote last week. “Outsourcing fraud prevention to specialized providers has proven effective, achieving a 32% reduction in failed payment rates compared to in-house efforts. Although only 53% of merchants implement two-factor authentication at the transaction level, its use is crucial for minimizing payment failures.”

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