Data security demands robust protection methods in our digital age. Format-preserving encryption and tokenization stand out as robust solutions for safeguarding sensitive information. Understanding the difference between data tokenization and encryption helps organizations protect data while maintaining usability. Modern businesses must choose between encryption vs tokenization for their needs. The choice between these methods impacts system performance and security levels.

Data masking is essential for protecting sensitive information in today’s data-driven world. It ensures that critical data, such as personal and financial information, remains secure from unauthorized access by replacing real data with fictitious or obfuscated values. By replacing real data with fictitious or obfuscated values, data masking safeguards privacy while enabling necessary operations like testing and analytics.

The threat group FIN7 is using the lure of generating nude images of favorite celebrities to get victims to download their NetSupport RAT. In any social engineering scam, there’s always the need to create some sense of urgency to act in order to make the potential victim take an action that enables the attack. In the case of a new attack by threat group FIN7, the urgency appears to be the desire to see deepfake nude images.

As organizations deploy more AI-enabled systems across their networks, adversaries are taking note and using sophisticated new tactics, techniques and procedures (TTPs) against them. The need for continued innovation to fight these threats is paramount.

In this episode of Trust Issues, host David Puner interviews James Imanian, Senior Director of the U.S. Federal Technology Office at CyberArk. They discuss the critical topic of election security, focusing on the recent 2024 U.S. presidential election. Drawing from his extensive background in cybersecurity including a career in the Navy and a stint at the U.S.

Highlights include Tanium platform announcements, launch of the Tanium Titans Community Program, and a customer panel of industry leaders.

Gal Peretz is Head of AI & Data at Torq. Gal accelerates Torq’s AI and data initiatives, applying his deep learning and natural language processing expertise to advance AI-powered security automation. He also co-hosts the LangTalks podcast, which discusses the latest AI and LLM technologies. To stay ahead of today’s threats, you must do more than keep pace — you need to equip your team with tools that enable smarter, faster responses.

In artificial intelligence (AI), especially within natural language processing (NLP), tokenization is a fundamental process that breaks down text into smaller, manageable units known as tokens. Depending on the specific task and model, these tokens can be individual words, subwords, characters, or even symbols.

As a modern CTO, it should probably come as no big surprise that I’m an optimist on the innovative prospects of artificial intelligence (AI). But I’ve been in this career for a long time, and that optimism is tempered with experience. I’ve seen enough emerging technology patterns to know that it always takes a lot more time and resources than people think to evolve innovative technologies beyond their final barriers.

In today’s rapidly evolving threat landscape, where cyberattacks grow more sophisticated by the day, staying ahead requires more than vigilance—it demands a platform built to operate at scale. Enter the Arctic Wolf Aurora Platform, the new name for our industry-leading security operations platform. With the ability to process over seven trillion events weekly, The Aurora Platform stands as one of the largest and most advanced cybersecurity platforms in our industry.