Sebastian Gierlinger, VP of Engineering at Storyblok - AITech Interview
Sebastian Gierlinger, discusses AI-driven cybersecurity risks, human error, and strategies to safeguard organizations from evolving threats.
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Sebastian, can you start by sharing your background and what led you to your current role as VP of Engineering at Storyblok?
My journey in the tech industry began with a deep interest in software development and a passion for creating innovative solutions. Over the years, I have held various roles in engineering and management, which have provided me with a broad perspective on technology and its applications.
Before joining Storyblok, I worked with several startups and established companies, focusing on building scalable and secure software solutions. My experience in these diverse environments has been instrumental in shaping my approach to engineering and leadership. With Storyblok, I was drawn to the company’s vision of transforming content management and the opportunity to lead a talented team in driving this innovation forward.
In what ways can generative AI be utilized to create malicious content such as phishing emails and social engineering attacks?
Generative AI can produce highly realistic and personalized phishing emails by analyzing vast amounts of publicly available data about potential targets. This allows attackers to craft messages that are more likely to deceive recipients into divulging sensitive information. Similarly, AI can generate fake social media profiles or impersonate trusted contacts, enhancing the effectiveness of social engineering attacks. The ability to produce high-quality, contextually relevant content at scale means that these AI-generated threats can bypass many traditional security filters designed to catch generic phishing attempts.
The current cybersecurity measures seem adequate. What specific measures do you believe are most effective against AI-driven attacks?
While current cybersecurity measures provide a foundation, they need to be enhanced to effectively counter AI-driven attacks. Key measures include advanced threat detection where AI and machine learning are used to detect and respond to threats in real-time, behavioral analytics, which is the monitoring of user behavior to identify deviations that may indicate compromised accounts. Zero Trust Architecture is also important which involves implementing a model where verification is required for every access request, regardless of its origin.
Keeping staff informed about the latest threats and best practices to mitigate human error are also key measures in reducing the threat of AI-driven cyber attacks as is Multi-Factor Authentication (MFA) where an extra layer of security is added to verify user identities.
To Know More, Read Full Interview @ https://ai-techpark.com/aitech-interview-with-sebastian-gierlinger/
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