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Emerging Technology

GenAI Can Make Cybersecurity Easier But Also Poses Threats!

By TechDogs Bureau

TD NewsDesk

Updated on Tue, May 16, 2023

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It’s no surprise that industries are looking to incorporate generative artificial intelligence (AI) and machine learning (ML) technologies into their functions, operations and software bundles, especially given its ability to produce results quickly. #TheFlash

One industry that surely needs quick response is cybersecurity, which is already finding benefits from Gen AI and ML, with the most common use cases being for Endpoint Detection and Response (EDR), which helps in detecting anomalous activities by analyzing behavior analytics.

OpenAI’s ChatGPT has been touted as an effective tool in this regard. By learning from ‘good behavior’, ChatGPT can flag accounts, terminate processes, create instant alerts and more. Along with automating routine but vital processes, it can make manual tasks easier by converting simple prompts into queries as well as offer explanations for the logic behind the query.

Even Google is getting on the act, having recently announced Cloud Security AI Workbench, a tool dedicated to cybersecurity, powered by their specialized “security” AI language model called Sec-PaLM (Pathways Language Model). Essentially, the tool will offer customers of Google’s security platforms enhanced security event searches, explanations, reporting, insights and more.

An excerpt from a blog post by Google regarding the same read as, “While generative AI has recently captured the imagination, Sec-PaLM is based on years of foundational AI research by Google and DeepMind, and the deep expertise of our security teams. … We have only just begun to realize the power of applying generative AI to security, and we look forward to continuing to leverage this expertise for our customers and drive advancements across the security community.”

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However, even though Gen AI and ML have found usefulness in cybersecurity, there are a few factors that cause hindrances to its usefulness.

AI tools can only be built to carry out certain tasks and produce results based on information and data fed in by humans. It can’t actually replicate a human’s real-life experiences, expertise and decision-making abilities.

Another issue observed with AI-produced results is the possibility of reporting fake positives – something that needs to be then checked by humans.

Furthermore, Gen AI tools can also be used by cybercriminals, which, reportedly, have already been used to create convincing and effective phishing emails. Alternatively, corrupted or malicious data sets can create security lapses.

According to Shishir Singh, Executive VP, Product and CTO, BlackBerry Cyber Security, “It’s been well documented that people with malicious intent are testing the waters, but over this year, we expect to see hackers get a much better handle on how to use ChatGPT successfully for nefarious purposes; whether as a tool to write better mutable malware or as an enabler to bolster their ‘skillset.’ Both cyber pros and hackers will continue to look into how they can utilize it best. Time will tell who’s more effective.”

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Of course, there are other issues that vary from company to company, one of which is the investment cost for acquiring and maintaining such technology. Generative AI and ML though have made certain aspects of cybersecurity easier and will continue to better operations as the technology develops.

How do you think organizations can address the shortcomings observed currently? What other industries do you think Generative AI and ML tools can revolutionize? Let us know in the comments below!

First published on Tue, May 16, 2023

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