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action or later. Please see Debugging in WordPress for more information. (This message was added in version 6.7.0.) in /home4/scienrds/scienceandnerds/wp-includes/functions.php on line 6114Source:https:\/\/techcrunch.com\/2023\/04\/24\/google-brings-generative-ai-to-cybersecurity\/<\/a><\/br> There\u2019s a new trend emerging in the generative AI space \u2014 generative AI for cybersecurity \u2014 and Google is among those looking to get in on the ground floor.<\/p>\n At the RSA Conference 2023 today, Google announced<\/a> Cloud Security AI Workbench, a cybersecurity suite powered by a specialized \u201csecurity\u201d AI language model called Sec-PaLM. An offshoot of Google\u2019s PaLM<\/a> model, Sec-PaLM is \u201cfine-tuned for security use cases,\u201d Google says \u2014 incorporating security intelligence such as research on software vulnerabilities, malware, threat indicators and behavioral threat actor profiles.<\/p>\n Cloud Security AI Workbench spans a range of new AI-powered tools, like Mandiant\u2019s Threat Intelligence AI, which will leverage Sec-PaLM to find, summarize and act on security threats. (Recall that Google purchased<\/a> Mandiant in 2022 for $5.4 billion.) VirusTotal, another Google property, will use Sec-PaLM to help subscribers analyze and explain the behavior of malicious scripts.<\/p>\n Elsewhere, Sec-PaLM will assist customers of Chronicle, Google\u2019s cloud cybersecurity service, in searching security events and interacting \u201cconservationally\u201d with the results. Users of Google\u2019s Security Command Center AI, meanwhile, will get \u201chuman-readable\u201d explanations of attack exposure courtesy of Sec-PaLM, including impacted assets, recommended mitigations and risk summaries for security, compliance and privacy findings.<\/p>\n \u201cWhile 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,\u201d Google wrote in a blog post this morning. \u201cWe 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.\u201d<\/p>\n Those are pretty bold ambitions, particularly considering that VirusTotal Code Insight, the first tool in the Cloud Security AI Workbench, is only available in a limited preview at the moment. (Google says that it plans to roll out the rest of the offerings to \u201ctrusted testers\u201d in the coming months.) It\u2019s frankly not clear how well Sec-PaLM works \u2014 or doesn\u2019t work \u2014 in practice. Sure, \u201crecommended mitigations and risk summaries\u201d sound useful, but are the suggestions that much better or more precise because an AI model produced them?<\/p>\n After all, AI language models \u2014 no matter how cutting-edge \u2014 make mistakes. And they\u2019re susceptible to attacks like prompt injection<\/a>, which can cause them to behave in ways their creators didn\u2019t intend.<\/p>\n That\u2019s not stopping the tech giants, of course. In March, Microsoft launched<\/a> Security Copilot, a new tool that aims to \u201csummarize\u201d and \u201cmake sense\u201d of threat intelligence using generative AI models from OpenAI including GPT-4<\/a>. In the press materials, Microsoft \u2014 similar to Google \u2014 claimed that generative AI would better equip security professionals to combat new threats.<\/p>\n The jury\u2019s very much out on that. In truth, generative AI for cybersecurity might turn out to be more hype than anything \u2014 there\u2019s a dearth of studies on its effectiveness. We\u2019ll see the results soon enough with any luck, but in the meantime, take Google\u2019s and Microsoft\u2019s claims with a healthy grain of salt.<\/p>\n<\/p><\/div>\n <\/br><\/br><\/br><\/p>\n
\nGoogle brings generative AI to cybersecurity<\/br>
\n2023-04-24 21:44:31<\/br><\/p>\n