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 calls 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. Two-thirds of organizations experienced a breach in 2016, and the global cost of cybercrime in general is expected to reach $6 trillion by 2021. Exposure of personal information is of particular concern. While breach numbers fell 23 percent between 2017 and 2018, 126 percent more records were compromised.
Although better identity and access management (IAM) practices can lower the risk of cloud breaches by 63 percent and server and application breaches by 46 percent, thereby protecting user and consumer data, the vast majority of organizations lack a “mature approach” to IAM. Enterprises are attempting to remedy the situation by introducing artificial intelligence (AI) into their security protocols. About 15 percent of enterprises currently use AI, which has the potential to both minimize breach risk and improve business operations.
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.
As of 2018, 32 percent of organizations were 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. Between 2015 and 2016, the number of days it took organizations to detect a breach dropped from 146 to 99, a significant change considering the amount of damage hackers can do in a short time.
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 as an identity and access management specialist or technologist provides both the knowledge and experience to help businesses keep up with the changing IAM landscape.