In the technology world, the latter half of the 2010s was mostly about slight tweaks, not sweeping changes: Smartphones got slightly better, and computer processing somewhat improved. Then OpenAI unveiled its ChatGPT in 2022 to the public, and—seemingly all at once—we were in a qualitatively new era. The predictions have been inescapable in recent months. Futurists warn us that AI will radically overhaul everything from medicine to entertainment to education and beyond. In this instance, the futurists might be closer to the truth. Play with ChatGPT for just a few minutes, and it is impossible not to feel that something massive is on the horizon. With all the excitement surrounding the technology, it is important to identify the ways in which the technology will impact cybersecurity—the good, the bad, and the ugly. It is an inflexible rule of the tech world that any tool that can be put to good use can also be put to nefarious use, but what truly matters is that we understand the risks and how to most responsibly handle them. Large language models (LLMs) and generative artificial intelligence (GenAI) are just the next tools in the shed to understand. The concern at the top of mind for most people, when they consider the consequences of LLMs and AI technologies, is how they might be used for adverse purposes. The reality is more nuanced as these technologies have made tangible positive differences in the world of cybersecurity. For instance, according to an IBM report, AI and automated monitoring tools have made the most significant impact on the speed of breach detection and containment. Organizations that leverage these tools experience a shorter breach life cycle compared to those operating without them.
Full story : How generative AI changes cybersecurity.
