Generative AI, which combines Machine Learning (ML) and Artificial Intelligence (AI), is an emerging technology with immense potential. However, the risks associated with generative AI cybersecurity cannot be ignored. It is important to explore and understand how to prevent cybersecurity challenges that arise from the use and misuse of Generative

In today’s rapidly evolving digital landscape, cybersecurity has become a critical concern for businesses and individuals alike. With the increasing complexity of systems and networks, traditional methods of fault detection and prevention are no longer sufficient to keep up with the ever-growing number of threats. As a result, artificial intelligence

Today, companies that house secure data and information are encountering an accessibility dilemma: On the one hand, they face an increased need for security and privacy of data, particularly as cyber threats become self-generating and more sophisticated. On the other hand, the value in securing assets lies in being able

A recent article in Forbes discusses the shifting mindset in cybersecurity from the traditional “detect and respond” approach to a prevention-first philosophy. With the continuous evolution of cybersecurity threats, organizations are investing in various tools like EDR (endpoint detection and response), MDR (managed detection and response), and XDR (extended detection and response).

The digital world is rapidly evolving. Thanks to real-time security news on digital transformations, it is now evident that cyberattacks, data leaks and vulnerability risks have had a fair share in “staining” the entire digital landscape as our reliance on technology increases. This begs the question: Are we really adapting