Artificial Intelligence Will Transform Cybersecurity

artificial intelligence in cybersecurity

The expanding possibilities of artificial intelligence in cybersecurity are revolutionizing the way organizations detect, prevent, and respond to cyber threats. Using advanced machine learning programs and data analytics techniques, AI systems can analyze large amounts of data in real-time to identify patterns, anomalies, and potential security breaches that may evade traditional security measures. From malware detection and threat intelligence analysis to user behavior monitoring and network security, AI-powered cybersecurity solutions offer proactive defense mechanisms that adapt and evolve alongside emerging threats. Moreover, AI enables automation of repetitive tasks such as patch management, vulnerability scanning, and incident response, allowing human resources to focus on more strategic aspects of cybersecurity. However, while AI holds great promise in enhancing cyber defenses, its adoption also presents challenges such as potential vulnerabilities to adversarial attacks and the ethical implications of autonomous decision-making in security contexts. As AI continues to mature, its integration into cybersecurity frameworks will be critical in staying ahead of increasingly sophisticated cyber threats in today’s digital landscape.

Managing user identities and permissions is an essential component of cybersecurity, particularly at the enterprise level. Increasing numbers of devices and a greater diversity of device types call for a smarter, more detailed approach to network security, and businesses are turning to artificial intelligence (AI) for help.

Breaches, Cybercrime and AI

The threat of a breach is significant for today’s companies. More than 80% of businesses say they have been hacked, and the global cost of cybercrime is estimated to surpass 20 trillion U.S. dollars by 2026. Exposure of personal information is of particular concern. 2023 smashed all previous records with an astonishing 133 million records exposed, stolen, or otherwise impermissibly disclosed.

Although better identity and access management (IAM) practices can lower the risk of system breaches thereby protecting user and consumer data, the vast majority of organizations lack a “mature approach” to IAM. According to Gartner, Thirty-four percent of organizations are either already using or implementing artificial intelligence (AI) application security tools to mitigate the accompanying risks of generative AI (GenAI). Over half (56%) of respondents said they are also exploring such solutions.

Smarter Workflows through Intelligent Access

Role-based access is a common approach to IAM, but it can fall short in workflows in which employees need short-term or one-time access to network assets. Even with a single sign-on model, users may be required to sign into multiple different applications to complete a single task or project, which can significantly slow down day-to-day business activities.

Granting special access has its own challenges. There’s always the chance access won’t be properly revoked when permissions are no longer needed, and accounts with more privileges are attractive to hackers looking for easy ways to infiltrate networks.

Using AI can minimize the risk of both workflow bottlenecks and increased account vulnerability. With AI-powered security, businesses can implement continuous authentication protocols in which user activities are monitored on an ongoing basis during sessions using a robust set of identifiers, including visual and audio cues.

Fine-Grained Access at All Permission Levels

Continuous authentication is a must when privileged accounts are required. AI provides the means by which businesses can monitor all user activities and behaviors within their networks on a moment-by-moment basis. With the security system always checking for anomalies and unusual patterns, it’s possible to fine-tune access privileges and revoke access when a user doesn’t behave as expected. Such security measures can be implemented to cover every device connecting to a business network, regardless of platform or location.

Some organizations are relying completely on AI for cyber threat detection, which indicates the technology is paying off. To get the greatest benefit, however, security systems must be provided with as many identifying factors as possible. A more robust identity profile for each user creates smarter access control across the network.

Learning and Intervening Without Humans

AI is often combined with machine learning (ML) to create powerful tools for breach detection and prevention. As users interact with a network, ML algorithms “learn” their normal behaviors and can adapt in response to this information. This technology is making it increasingly possible to automate security and reduce the number of alerts requiring human attention.

Growing businesses and enterprises need automation to handle an otherwise overwhelming amount of user data. Adding even a few users to a network introduces new behavior patterns with variations and nuances unique to each user. Monitoring these behaviors and identifying discrepancies becomes almost impossible in large networks, but AI and ML can keep up where human efforts fall short.

Better Responses to Incidents

So far, AI is showing the most promise when it comes to incident response. The number of days it takes organizations to detect a breach is 977 days or roughly 9 months, a significant gap considering the amount of damage hackers can do in this time period.

Using predictive analytics, security systems with AI components are better equipped to estimate the potential extent of a breach and the level of risk at the time of detection. This sets interventions in motion sooner, whether from a human cybersecurity team or the AI tool itself. With the help of ML algorithms, AI can determine when user behaviors require a lockdown of certain parts of the system and minimize data loss by preventing hackers from getting any deeper into the network.

For IT professionals, AI represents the next frontier in security and access management. The demand for trained security professionals is likely to keep growing as AI and ML become more powerful and give rise to new options for breach prevention. Certification in identity and access management provides the necessary knowledge to help businesses keep up with the changing IAM landscape.

Identity and access management certifications