Artificial intelligence is already shaping the world around us — and that trend is only set to grow.
The new technology — which has recently undergone vast, expectation-beating improvements — has seeped into virtually every industry, one way or another. It is transforming processes and propelling innovations.
But like most technological advancements, AI brings with it an array of complex challenges, particularly in the domain of cybersecurity.
As the sophistication of AI increases, so does the complexity of cyber threats. Consider a scenario where a skilled cybercriminal uses an AI tool to draft a highly personalized spear-phishing message. This message, blending seamlessly with the organization's internal communication style, can deceive even the most vigilant employees. Traditional security systems often prove ineffective against such sophisticated attacks, leaving businesses vulnerable to significant disruption.
Similarly, cyber-attackers can use AI to create deepfake voices and impersonate high-ranking executives. A well-executed deepfake could deceive employees into authorizing large unauthorized fund transfers, exploiting human trust to circumvent security measures.
Artificial intelligence (AI) enables machines to perform tasks that typically require human intelligence, including making decisions, recognizing human speech, perceiving visual elements, and translating languages. AI uses training data to comprehend context and determine how to respond or react in different situations.
Artificial intelligence in cybersecurity is increasingly critical to protecting online systems from attacks by cyber criminals and unauthorized access attempts. If used correctly, AI systems can be trained to enable automatic cyber threat detection, generate alerts, identify new strands of malware, and protect businesses’ sensitive data.
Benefits of artificial intelligence in cybersecurity include leveraging AI techniques — such as deep learning, machine learning (ML), knowledge representation and reasoning, and natural language processing — for a more automated and intelligent cyber defense. In this way, organizations can discover and mitigate the thousands of cyber events that they can come across daily.
AI for cybersecurity works by evaluating massive amounts of data across multiple sources to identify patterns of activity across an organization, such as when and where people sign in, traffic volumes, and the devices and cloud apps that employees use. Once it understands what’s typical, it can identify anomalous behavior that may need to be investigated. To maintain privacy, an organization’s data isn’t used for the AI output at other organizations. Instead, AI uses global threat intelligence synthesized from multiple organizations.
AI uses machine learning algorithms to continuously learn based on the data the system evaluates. When generative AI identifies certain known cyberthreats, such as malware, it can help contextualize threat analysis and make it easier to understand by generating new text or pictures to describe what’s happening.
People are still vitally important to cybersecurity, but AI helps them increase their skills and identify and resolve threats faster.
AI in cybersecurity reinforces cyber threat intelligence, enabling security professionals to:
With AI in cybersecurity, organizations can better protect passwords and secure user accounts through authentication. Most websites include features that allow users to log in to purchase products or contact forms for people to input sensitive data. Extra security layers are necessary to keep their information secure and prevent it from getting into the hands of malicious actors.
AI tools, such as CAPTCHA, facial recognition, and fingerprint scanners enable organizations to automatically detect whether an attempt to log in to a service is genuine. These solutions help prevent cybercrime tactics like brute-force attacks and credential stuffing, which could put an organization’s entire network at risk.
Phishing remains one of the biggest cybersecurity threats facing businesses across all industries. AI within email security solutions enables companies to discover anomalies and indicators of malicious messages. It can analyze the content and context of emails to quickly find whether they are spam messages, part of phishing campaigns, or legitimate. For example, AI can quickly and easily identify signs of phishing, such as email spoofing, forged senders, and misspelled domain names.
ML algorithm techniques allow AI to learn from data to make analysis more accurate and evolve to address new threats. It also helps AI better understand how users communicate, their typical behavior, and textual patterns. This is crucial to preventing more advanced threats like spear phishing, which involves attackers attempting to impersonate high-profile individuals like company CEOs. AI can intercept suspicious activity to prevent a spear-phishing attack before it causes damage to corporate networks and systems.
As cyber criminals deploy more sophisticated methods and techniques, thousands of new vulnerabilities are discovered and reported every year. As a result, businesses struggle to manage the vast volume of new vulnerabilities they encounter every day, and their traditional systems cannot prevent these high-risk threats in real time.
AI-powered security solutions such as user and entity behavior analytics (UEBA) enable businesses to analyze the activity of devices, servers, and users, helping them identify anomalous or unusual behavior that could indicate a zero-day attack. AI in cybersecurity can protect businesses against vulnerabilities they are unaware of before they are officially reported and patched.
Network security involves the time-intensive processes of creating policies and understanding the network’s topography. When policies are in place, organizations can enact processes for identifying legitimate connections versus those that may require inspection for potentially malicious behavior. These policies can also help organizations implement and enforce a zero-trust approach to security .
However, creating and maintaining policies across multiple networks requires a significant amount of time and manual effort. Organizations often do not deploy the correct naming conventions for their applications and workloads. This means security teams may have to spend more time determining which workloads belong to specific applications. AI learns organizations’ network traffic patterns over time, allowing it to recommend the right policies and workloads.
With behavioral analytics, organizations can identify evolving threats and known vulnerabilities. Traditional security defenses rely on attack signatures and indicators of compromise (IOCs) to discover threats. However, with the thousands of new attacks that cyber criminals launch every year, this approach is not practical.
Organizations can implement behavioral analytics to enhance their threat-hunting processes. It uses AI models to develop profiles of the applications deployed on their networks and process vast volumes of device and user data. Incoming data can then be analyzed against those profiles to prevent potentially malicious activity.
Implementing AI in cybersecurity offers a wide range of benefits for organizations looking to manage their risk. Typical benefits are:
As AI continues evolving and integrating into our daily lives, we must ensure our cybersecurity strategies evolve. The threats are significant — but so too are the opportunities.
AI can be a powerful ally in combating cyber threats, but its potential must be harnessed responsibly and securely. Collaborative efforts from all stakeholders are essential in navigating the challenges and seizing this new digital frontier's opportunities.
