Interview Questions for Darren Thomson, Cyber Security Strategy Leader at CyberCube
In the ever-evolving world of cybersecurity, artificial intelligence (AI) is proving to be a crucial tool in the fight against social engineering attacks. These attacks, which focus on influencing attitudes and behaviors to gain unauthorised access, pose a significant threat in the digital age.
AI's Key Contributions
AI plays a pivotal role in enhancing detection, prevention, and response capabilities, particularly in sectors like the insurance industry that rely heavily on secure, trusted identity verification.
- Identity-based defenses: AI-driven identity security solutions help prevent attacks that exploit human trust, shifting the focus from perimeter defenses to identity-first controls. This is critical because AI-enabled social engineering often utilizes convincingly faked identities across various channels.
- Detecting and mitigating advanced AI-powered social engineering: AI can identify sophisticated phishing, voice cloning, and impersonation attempts that traditional security measures miss. This is crucial in insurance where interacting with clients and verifying identities remotely is common.
- Automation and scale analysis: AI tools analyze large volumes of communication to detect patterns typical of social engineering — such as phishing campaigns that use generative AI to produce personalized messages—helping security teams respond faster and more accurately.
- Enhancing authentication methods: AI supports the adoption of phishing-resistant, passwordless authentication (e.g., FIDO standards) and live biometric verification with liveness detection to strengthen helpdesk security and reduce vulnerability to social engineering.
- Training and awareness: AI can help prepare frontline personnel by simulating social engineering attacks, enabling employees to better recognize red flags and suspicious behaviors.
- Addressing evolving AI-enabled threats: AI also assists in monitoring and defending against new tactics like agentic AI that autonomously execute complex social engineering steps, including synthetic identity creation and multi-stage interaction strategies.
The Insurance Industry Context
Insurance companies, with their reliance on personal data and complex client interactions, are prime targets for social engineering attacks. AI-enhanced defenses ensure that identity proofing during claims, policy changes, and customer service is robust against increasingly realistic AI-generated deceptions.
Implementing AI-based solutions reduces the risk of unauthorized access to sensitive insurance records and prevents compromise of privileged accounts by detecting AI-generated social engineering content early. AI also supports compliance with evolving legal requirements around AI usage and cybersecurity, which is especially relevant as individual states legislate AI-specific regulations affecting the insurance sector.
A Collaborative Approach
As society grapples with the increasing sophistication of cyber threats, collaboration and the sharing of best practices become essential. The criminal fraternity often leverages such collaboration to amplify their attacks, and it is crucial for society to follow suit to combat these threats effectively.
In the face of emerging threats like deep fake technology, which could potentially destabilize political systems on a global scale and impact the reputation of large corporations, the insurance industry must consider these advancements when developing attack scenarios. The injection of vast scale into socially engineered attacks will increase the likelihood of a return on investment for the attackers and lead to large accumulations of loss for targeted businesses.
The Future of Cybersecurity
The power of data and analytics is not fully understood or appreciated by those seeking to lower their cyber risk posture, which is apparent in both the insurance industry and enterprises. As a result, criminal investment in cyber attacks now focuses on the application of AI and automation, with the ability to build millions of social profiles on demand.
To combat these threats, multi-disciplinary experts across various fields, including data science, cybersecurity, software engineering, actuarial modelling, the military, and commercial insurance, will play an increasing role in understanding the psychology and motivations behind social engineering approaches.
In conclusion, AI serves both as a tool adversaries use to amplify social engineering threats and as an essential defender by enabling more precise identity verification, faster detection of sophisticated attacks, stronger authentication, and improved human training. These capabilities are critical within the insurance industry’s cybersecurity strategy.
[1] CyberCube, "AI and Social Engineering: The New Frontier in Cybersecurity," link
[2] CyberCube, "The Impact of AI on Cybersecurity," link
[3] CyberCube, "The Role of AI in Cyber Risk Management," link
[4] CyberCube, "Navigating the Regulatory Landscape for AI in Insurance," link
[5] CyberCube, "AI and Passwordless Authentication: A New Era for Cybersecurity," link
- The insurance industry, which deals with substantial amounts of personal data and intricate client interactions, is a prime spot for social engineering attacks. AI-boosted defenses fortify identity verification during claims, policy changes, and customer service, shielding sensitive insurance records and privileged accounts from unauthorized access.
- AI-powered analytics and machine learning can detect patterns characteristic of social engineering, such as large phishing campaigns utilizing generative AI for personalized messages. This enables security teams to respond swiftly and accurately.
- AI is also instrumental in shifting the focus from perimeter defenses to identity-first controls, bolstering the prevention of attacks that prey on human trust. AI-driven identity security solutions combat AI-enabled social engineering by guarding against faked identities across various platforms.
- AI-based tools can simulate social engineering attacks, training frontline personnel to identify red flags and suspicious behaviors. This improves the preparedness of employees in recognizing potential threats.
- As criminal entities employ AI and automation to escalate social engineering attacks, multi-disciplinary experts involving data science, cybersecurity, software engineering, actuarial modelling, the military, and commercial insurance fields will be increasingly critical in unraveling the psychology and motives behind these approaches.
- The collaboration and sharing of best practices among various sectors are essential in counteracting the growing sophistication of cyber threats. This mutual exchange of knowledge helps combat threats effectively and stay ahead of emerging threats like deep fake technology, which could potentially jeopardize political systems and large corporations.
