The cybersecurity landscape is undergoing a dramatic transformation, with artificial intelligence emerging as both a formidable weapon and an indispensable shield. Navigating this new era demands a strategic approach and a deep understanding of the technological and human elements at play.
To gain insights from the front lines, CNBC spoke with Rachel James, Principal AI ML Threat Intelligence Engineer at AbbVie, a global biopharmaceutical powerhouse.
“Beyond the AI augmentation already built into our security tools, we’re leveraging Large Language Models (LLMs) to analyze our detections, observations, correlations, and associated rules,” James explained.
James and her team are harnessing the power of LLMs to sift through a deluge of security alerts, identifying patterns, eliminating redundancies, and proactively uncovering vulnerabilities before malicious actors can exploit them. This involves sophisticated techniques to determine similarity, duplication and expose critical gaps in defenses.
“We use this to determine similarity, duplication and provide gap analysis,” she elaborated, adding that the team is actively working to integrate even richer external threat intelligence data. “We are looking to enhance this with the integration of threat intelligence in our next phase.”
At the heart of AbbVie’s cybersecurity operations lies OpenCTI, a specialized threat intelligence platform designed to distill actionable insights from a vast ocean of digital information. AI provides the engine for this effort, transforming unstructured data into a standardized format known as STIX. James envisions leveraging language models to connect this intelligence with all aspects of their security infrastructure, from vulnerability management to third-party risk assessments.
However, James emphasizes that embracing AI’s capabilities requires caution. As a key contributor to the ‘OWASP Top 10 for GenAI’ initiative, she is keenly aware of the potential pitfalls. “I would be remiss if I didn’t mention the work of a wonderful group of folks I am a part of – the ‘OWASP Top 10 for GenAI’ as a foundational way of understanding vulnerabilities that GenAI can introduce,” she said.
Beyond specific vulnerabilities, James highlights three fundamental trade-offs that business leaders must consider:
- Accepting the inherent risk associated with generative AI’s creative and often unpredictable nature.
- Addressing the challenge of transparency as AI models become increasingly complex and opaque.
- Accurately assessing the return on investment for AI projects, mitigating the risk of overestimating benefits or underestimating the resources required in a rapidly evolving field.
Solid cybersecurity in the AI era demands a deep understanding of the attacker’s mindset. James’ expertise in cyber threat intelligence is crucial in this realm. “This is actually my particular expertise – I have a cyber threat intelligence background and have conducted and documented extensive research into threat actor’s interest, use, and development of AI,” she noted.
James actively monitors adversary communications and tool development through open-source channels and automated dark web collections, sharing her findings on her cybershujin GitHub. Additionally, she actively engages in offensive security tactics. “As the lead for the Prompt Injection entry for OWASP, and co-author of the Guide to Red Teaming GenAI, I also spend time developing adversarial input techniques myself and maintain a network of experts also in this field,” James adds.
What does this mean for the future of the industry? James sees a clear parallel that offers remarkable opportunity: “The cyber threat intelligence lifecycle is almost identical to the data science lifecycle foundational to AI ML systems.”
This close alignment opens doors for unprecedented collaboration. “Without a doubt, in terms of the datasets we can operate with, defenders have a unique chance to capitalise on the power of intelligence data sharing and AI,” she asserts.
James’ final message provides guidance for cybersecurity professionals: “Data science and AI will be a part of every cybersecurity professional’s life moving forward, embrace it.”
Original article, Author: Samuel Thompson. If you wish to reprint this article, please indicate the source:https://aicnbc.com/7879.html
