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AI in Cybersecurity: How to Cut Through the Overhype and Maximize the Potential

CyberSecurity Insiders

–( BUSINESS WIRE )–Artificial intelligence (AI), machine learning (ML), and deep learning (DL) are often applied in cybersecurity, but their applications may not always work as intended. The paper explores those areas as well as malicious uses of ML and DL, specifically in social engineering and phishing.

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Can a 60-year-old framework still improve cyber efficiency?

SC Magazine

While being “classic” and “timeless” might work in other industries, information security (Infosec) must constantly guard against resting on laurels when it comes to strategies and solutions. Cybercrime also has elements where automated remediation is unavailable, such as social engineering attacks.

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From a tech explosion to accidental cyberattacks, researchers offer a glimpse into 2030

SC Magazine

But what might they offer the front-facing information security officer – someone with a ten-year plan, wondering what to prepare for down the line? With advances in artificial intelligence, disinformation become full conversations, and information could become a pervasive threat requiring training or even evaluation tools to evade.

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Top Cybersecurity Accounts to Follow on Twitter

eSecurity Planet

Fifteen years after the launch of the microblogging social media platform, Twitter remains a dominant public forum for instant communication with individuals and organizations worldwide on a universe of topics, including #cybersecurity. How to screen for natural infosec talent: Ask for a worst case scenario for any common situation.

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Embracing Automation in Cyber Threat Intelligence: The Key to Timely Protection

SecureWorld News

Threat Intelligence (TI) representation across different levels There is a lot of information on cyberattacks on the internet, and, as a rule, the most helpful information is contained in cyber threat reports ( Threat Intelligence Reports ). Highlighting the AI advantages in ITSM and InfoSec, you can use ChatGPT.