AI in Cyber Security: Benefits Explained

Considering that 95% of all workplace data breaches are caused by human error, few people are as happy about the continued advancements in artificial intelligence (AI) as security professionals. AI has shown great promise in protecting precious corporate data and businesses have taken notice. By 2030, the artificial intelligence cybersecurity market is projected to reach nearly $134 billion - more than four times what it is today. 

It’s an exciting time as IT security professionals look to turn the tables on increasingly sophisticated phishing and social engineering attacks. Companies need to adapt as quickly as cybercriminals do to protect their assets and critical data. Although it has a long way to go, AI has already proven its ability to improve cyber threat response and risk management. Here are five reasons artificial intelligence will be hugely valuable in the evolving cybersecurity landscape.

 

Enhanced Threat Detection

Threat detection involves analyzing data (e.g. system and network logs). Most modern networks capture more data than humans can really process, but AI can consume big data stores and produce reports and predictions way more efficiently than we can. Human error is inevitable. We get tired, or some things just slip past us, but AI can constantly monitor and analyze network traffic without the need for downtime.

AI can process vast data sets lightning and identify anomalies and patterns indicative of potential threats in real-time. Not only that, AI-power systems have adaptive learning capabilities, meaning they can actually use historical data to learn and even recognize attacks that went unnoticed. By pairing human intelligence with AI, threat detection methodologies can help companies prevent attacks through new vectors, such as IoT and mobile devices.

Automated Incident Response

Any business would like to reduce the likelihood of security incidents to 0%, but that is impossible.  What you can do, however, is reduce the risk of a breach and the impact one may have. Think about a cybersecurity threat like a house fire; the sooner you respond to a fire, the less damage is done. In the medical field, the sooner you detect and respond to an illness, the better chance you have of making a full recovery.

Incident response in cybersecurity is much the same. AI can automate and streamline incident response processes to increase the speed of identification, analysis, and containment. For example, AI can automatically block malicious traffic, isolate compromised devices, and notify security teams of threats. AI can also automate patch management and update vulnerable software to prevent future incidents.  A fast, automated response means less downtime, less exposure, and fewer losses.

Reduced False Positives

A false positive is an alert that incorrectly indicates the presence of a vulnerability or threat. Human error is one the main drivers of false positives, usually because someone does configure rules correctly or they make a mistake whitelisting or blacklisting an entity. False positives can be a huge drain on IT teams, wasting time and resources investigating non-issues when they could be spent addressing actual vulnerabilities.

To stop new and unknown threats, organizations can make a list of known safe items and block everything that is not on that list. Let’s look at a real-world scenario to explain how this works. Most schools maintain a list of websites that they know are kid-friendly and have their system block any site that isn’t on the list. But the internet isn’t static, it changes every day. With millions of sites that may be appropriate for kids, it’s impossible to manually keep a full and accurate list. In this case, many “false positives” would block totally appropriate sites. However, AI can moderate content on the fly, determine what is and is not appropriate for kids, and do away with the need for a list altogether.

Predictive Analytics

AI is trained on data. The more data you feed it, the more intelligent its solutions and the more accurate its predictions will be. Most people may not realize it, but we see this in action with the amount of spam emails in our inboxes. Not too long ago it was common to get email messages with a bunch of meaningless gibberish that was designed to bypass spam filters. As AI has gotten involved, it can better predict a message as being spam, making sure we don’t see those messages anymore.

One of the most valuable things about AI in cybersecurity is its self-learning capacities. Thanks to its ability to rapidly comb through vast datasets,  AI can run simulations of potential attack scenarios to understand how they might unfold. Iy can generate informed predictions, such as how often an anomaly may occur without a solution in place, and assess how much damage it may do.

Security teams can also use the advanced analytics and recommendations from AI to make more informed decisions about the next steps in their cybersecurity strategy. This frees up critical resources to focus on more complex, integrated aspects of cybersecurity management.

Integration Strategies for AI in Cybersecurity

At one time, the biggest obstacle to implementing AI in cybersecurity might have been getting your team to buy in. Those days are long gone, with 48% of cybersecurity pros feeling confident their organization can execute a strategy for leveraging AI in security. But there are still some common challenges you need to consider when building out your AI strategy. Let’s look at what they are and how you can overcome them to integrate AI into your existing cybersecurity frameworks.

Assessments and goal-setting: Identify specific cybersecurity needs and challenges that AI can address. This could include threat detection, incident response, and anomaly detection. Run an assessment of your current cybersecurity infrastructure to identify gaps that AI can fill. Once you do that, you define the specific things you hope to accomplish by adding an AI system to your security stack.

Vendor evaluation: AI tools are not all created equal. Just like any other solution, they have their strengths and weaknesses that need to align with the goals you’ve set organization's cybersecurity needs. Evaluate AI vendors based on their technology, expertise, support services, and track record. Consider open-source solutions as well for flexibility and customization.

Data access and integrity: Breaking down data silos so AI applications can actually access, monitor, and analyze data. Also, accurate data is essential for AI systems to be helpful, so security teams need to ensure data is clean, complete, and accurate.

Skill shortages: There is already a global shortage of skilled AI professionals, including data scientists, machine learning engineers, and AI specialists. Your organization has to prioritize upskilling its existing workforce or attracting new talent to drive a successful AI integration strategy. Partner with a training and development specialist like New Horizons which offers a robust catalog of Artificial Intelligence (AI) and Machine Learning training so your security team has the knowledge and expertise to understand, create, and implement AI and Machine Learning solutions

Tempering expectations: With everyone from entry-level employees to the C-suite excited about the hype surrounding AI, there is often a misunderstanding of its real-world capabilities. AI is not magic, it’s just a tool. Teams that are rolling out AI as part of their security poster need to manage expectations so everyone understands the limitations of this technology.

Deploy gradually: Deploy the AI system gradually across the organization, beginning with critical areas or high-risk segments and expand deployment in phases. The system should be scalable so it can handle increasing data volumes and complexity; cloud-based solutions are a great option for flexible scaling.

Future Trends in AI and Cybersecurity

As AI becomes more reliable and accurate, it will be an active collaborator in all your human-driven efforts. As it exceeds human performance and trustworthiness, it will drive more value than ever before. Just like the invention of the automobile made jobs like blacksmith and farrier obsolete and made way to new jobs like factory worker and auto mechanic, the advance of AI will give way to a whole new generation of jobs that didn’t exist before. But AI remains a tool, not a catch-all solution to your cybersecurity woes. Humans will have to play a role in wielding this tech and getting results for the foreseeable future. 

Conclusion

The age of AI is upon us, and it is a welcome development for security professionals who are often overlooked heroes in a taxing profession. From improved threat detection to eradicating false positives and offering proactive defense strategies, AI is poised to help businesses overcome an era of increasingly sophisticated cyber attacks. There’s no reason to ignore the opportunity that’s before you and avoid discussions about artificial intelligence in cybersecurity. New Horizons is ready to help you gain the skills needed to thrive in this new era. With the proper expertise, you will soon make AI an indispensable tool in your organization’s fight against cybercrime.