{"id":57434,"date":"2024-10-17T00:00:00","date_gmt":"2024-10-17T00:00:00","guid":{"rendered":"urn:uuid:34ba8dc6-b2be-fed0-0588-a10a084e07a9"},"modified":"2024-10-17T00:00:00","modified_gmt":"2024-10-17T00:00:00","slug":"5-ai-security-takeaways-featuring-forrester","status":"publish","type":"post","link":"https:\/\/www.threatshub.org\/blog\/5-ai-security-takeaways-featuring-forrester\/","title":{"rendered":"5 AI Security Takeaways featuring Forrester"},"content":{"rendered":"

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Depending on who you ask, generative AI could either be the salvation of humankind or the bringer of our doom. For cybersecurity specifically, it\u2019s been positioned both as a kind of panacea and the source of unprecedented new threats.<\/p>\n

David Roth and guest speaker Jeff Pollard recently sat down for a \u201cnot so fast\u201d webinar<\/a> to disentangle the truth about AI from the straw heaps of hype. Roth is Trend Micro Chief Revenue Officer for Enterprise America. Pollard is a Vice-president and Principal Analyst at Forrester.<\/p>\n

The two acknowledged the fact that AI and machine learning are hardly new to security, even if generative AI is, and looked at some of the areas where genAI is practical and useful for cybersecurity teams today. This blog distills key parts of their conversation.<\/p>\n

\u201cI hesitate to say we’ve reached peak AI hype. We have to be close or I think we’re all going to have a terrible time in the industry because there are so many false promises or expectations being laid out that just aren’t being met right now.\u201d<\/i>
Jeff Pollard<\/b><\/p>\n

#1 \u2013 Beware of the AI hype<\/span><\/p>\n

It’s not just fascination with a new \u2018shiny object\u2019 that has fueled the hype about generative AI for cybersecurity. Security teams are desperate for relief. They\u2019re over-pressured and under-resourced, squeezed by a years-long skill shortage, and faced with threats that keep multiplying and changing.<\/p>\n

It\u2019s understandable, then, that when genAI hit the scene, many people latched onto fantasies of fully autonomous security operations centers (SOCs) powered by Terminator-style malware-hunting agents.<\/p>\n

Yet today\u2019s genAI systems aren\u2019t effective enough to operate without human intervention and oversight. Far from magically solving the skills shortage, genAI could exacerbate it in the short term by introducing new training needs. Culture is also a factor. While experienced practitioners may learn new AI tools quickly, it can still take weeks or months for them to change their habits and integrate those tools into their workflows.<\/p>\n

Despite all that, there are compelling security use cases for current genAI systems. By augmenting existing capabilities, AI can help teams do more and get better results with less drudgery, especially in areas such as application development and detection and response.<\/p>\n

\u201cThe faster you\u2019re able to [generate reports], the more time you\u2019re spending working an event.\u201d<\/i>
Jeff Pollard<\/b><\/p>\n

#2 \u2013 Grab the quick wins<\/span><\/p>\n

One task where security teams stand to gain fast from genAI is generating documentation. Action summaries, event write-ups, and other types of reports are tedious and time-consuming to produce. But they need to get done. GenAI can produce them on the fly, freeing up security practitioners to immerse themselves in more events and work more incidents.<\/p>\n

One caveat is that security professionals need good communication skills to perform their roles. AI-generated reports may save time but can\u2019t come at the cost of professional development.<\/p>\n

GenAI can also recommend next best actions and query existing knowledge bases to surface usable information quicker than a human. The key in these cases is to be sure AI outputs align with the organization\u2019s needs and methodologies. If a defined process has seven steps and an AI companion recommends four, a human agent needs to make sure all seven are followed\u2014to achieve the desired outcomes and to ensure the actions being taken are compliant with corporate policies and external regulations. Inadvertent shortcuts could have serious consequences.<\/p>\n

\u201cIt’s not like the \u2018minority report\u2019 on the pre-crime unit, but at least [you] can see enough across a huge volume of data about what the likelihood of an attack path could or would look like.\u201d<\/i>
David Roth<\/b><\/p>\n

#3 \u2013 Be more proactive with AI<\/span><\/p>\n

GenAI has potential to turn the \u2018big data problem\u2019 into a big data opportunity and allow security teams to become much more proactive than they are today by identifying changes in an attack surface and running attack path scenarios. While it might not predict exactly what will happen, it could position security teams to get ahead of threats that would otherwise slip by.<\/p>\n

How effective this turns out to be in practice depends on the extent of an organization\u2019s awareness of its systems, configurations, and current states. If there are gaps, the AI will also have gaps. Today, those gaps are unfortunately common, with data and documentation recorded in multiple spreadsheets on different computers even in large enterprises.<\/p>\n

This points to the importance of good, AI-ready data hygiene and applying standardized approaches to data management. The better the raw material, the more AI can do with it.<\/p>\n

\u201cIf you have enterprise software in your business, it has AI now. Whether it’s SAP Joule, Salesforce with Einstein GPT, Microsoft with Copilot, and the dozens of other names out there. That\u2019s another area you need to worry about because this changes the ways users interact with company data. \u201d<\/i>
Jeff Pollard<\/b><\/p>\n

#4 \u2013 Watch out for shadow AI<\/span><\/p>\n

Enterprises have legitimate concerns about AI leaking sensitive company or customer information. This can happen through employee use of unauthorized tools or via sanctioned enterprise software, which is increasingly being augmented with AI capabilities. In the past, a bad actor would need to understand how to hack into an ERP system to access unauthorized data inside it; with AI, the right prompt could too easily make the same information available.<\/p>\n

Enterprises need to secure themselves against employee shadow AI and illegitimate use of approved AI tools. They also need to take care when using large language models (LLMs) to build applications for themselves. The underlying data needs to be secured along with the application being built, the LLM itself, and the prompt system.<\/p>\n

These risks basically boil down to a new set of problems: bring-your-own-AI problems, enterprise app problems, and product security or innovation problems. Each type requires its own protective measures and impinges on CISO responsibilities\u2014even though CISOs aren\u2019t in charge of the related projects.<\/p>\n

\u201cIt almost reminds me of the early hyper-growth cloud days…. Being able to enforce through governance and security controls is harder when you\u2019re not keeping up with the speed of the business.\u201d<\/i>
David Roth<\/b><\/p>\n

#5 \u2013 You need an AI strategy<\/span><\/p>\n

There are helpful parallels between the shadow IT app frenzy and early days of cloud and the present state of AI. While security leaders called unsanctioned apps \u2018shadow IT\u2019, business leaders and investors saw their use as \u2018product-led growth\u2019. And security teams learned quickly that they couldn\u2019t ban those innovations: any attempt to clamp down just drove usage underground where things couldn\u2019t be managed at all.<\/p>\n

Security teams need to accept and adapt to the AI reality. Even if it isn\u2019t currently fulfilling all the hopes and dreams of its most fervent champions\u2014and even if it encounters some setbacks\u2014in two to three years AI will be much more mature and powerful than it is today. Organizations can\u2019t afford to try to secure it after it\u2019s adopted.<\/p>\n

That means the opportunity is right now to get ready, develop security-oriented AI strategies, learn about the technology, and be prepared for when it really takes off. Many observers feel security teams got caught flat-footed with cloud even though they had plenty of lead time. Given the potency and complexity of AI, they can\u2019t afford to repeat that mistake.<\/p>\n

Infographic: Survival Guide for AI-Generated Fraud<\/span><\/a><\/p>\n

Take it with a grain of salt, but take it seriously<\/b><\/p>\n

GenAI may not have lived up to the hype of its transformative potential\u2014yet\u2014but it nonetheless has meaningful applications in cybersecurity. It won\u2019t solve the skills shortage in the near term but it can lift some of the burden off security teams, and the better organizations manage and maintain their IT data, the more AI will be able to detect and even prevent over time. By taking lessons from recent past experiences with shadow IT and cloud adoption, security teams can prepare effectively for the day when AI does start to realize its wilder dreams\u2014and keep their enterprises safe.<\/p>\n

Explore more AI perspectives<\/span><\/p>\n

Check out these additional resources:<\/p>\n

Read More HERE<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

Highlights from the recent discussion between Trend Micro\u2019s David Roth, CRO Enterprise America, and guest speaker Jeff Pollard, VP, Principal Analyst, Forrester about AI hype versus reality and how to secure AI in the workplace. Read More HERE…<\/p>\n","protected":false},"author":2,"featured_media":57435,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"colormag_page_layout":"default_layout","footnotes":""},"categories":[61],"tags":[10938,9521,9511,9508,9523,9532,9524,9535],"class_list":["post-57434","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-trendmicro","tag-trend-micro-research-artificial-intelligence-ai","tag-trend-micro-research-cyber-crime","tag-trend-micro-research-cyber-threats","tag-trend-micro-research-endpoints","tag-trend-micro-research-network","tag-trend-micro-research-security-strategies","tag-trend-micro-research-video","tag-trend-micro-research-web"],"yoast_head":"\n5 AI Security Takeaways featuring Forrester 2026 | ThreatsHub Cybersecurity News<\/title>\n<meta name=\"description\" content=\"ThreatsHub Cybersecurity News | ThreatsHub.org | Cloud Security & Cyber Threats Analysis Hub. 100% 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