In today’s global and highly interconnected business environment people and companies collaborate constantly together. From one side, the business becomes more productive and efficient, but from the other side grows probability for the company to become a victim of a data breach or another cyber threat. Determining who should have access to what information is a hard task for many businesses and leaving that problem aside could make their systems vulnerable. That is why the importance of a smart and mature Identity & Access Management (IAM) strategy shouldn’t be underestimated. Researches from analyst companies report that more than 70% of organizations do not have a serious approach to IAM. That means that the risk for these organizations to get suffered from a data breach is twice as high compared to organizations that have their IAM strategy applied. Research reports also show that the smarter an IAM approach is, the smaller is the security risk.

IAM against data breaches

As mentioned above, for many organisations, IAM is a critical weapon in their cyber security arsenal. It is a great solution to mitigate against data breaches as well as manage the additional risks coming with remote working and Bringing Your Own Device (BYOD). Identity and Access Management (IAM) involves tracking the behaviour and actions of each individual and asset in the IT environment, specifically your system administrators and mission-critical assets. IAM enables individuals to access the correct resources at the right times for the proper reasons, which requires significant systems integration so that all platforms have the situational awareness necessary to properly enforce policy. If properly implemented, IAM can drastically increase visibility and security.

As we look ahead to the rest of 2021, securing identity access will once again be everywhere, but we are predicting that with the help of artificial intelligence and machine learning (AIML), there will be a more positive narrative to creating and managing an immutable digital identity. New AIML authentication technologies that continuously protect pre-, during and post-authorization, while leveraging individual behaviours in a secure and private manner will become mainstream, leaving cybercriminals in the dust.

How can AI improve Identity Management and Security

AI and machine learning (ML) technologies can be a major help for effective IAM and can help to avoid a lot of problematic situations. These technologies can assist enterprises to grow from an overly technical approach of access management into a form of access management that is understandable on all levels within a business.

  • Advanced analytics

Analytics in a combination with artificial intelligence can provide more focus and contextual insights so that both technical and non-technical employees can work more time efficient. Modern technologies provide ways to learn new insights and automate processes, which are able to drastically speed up the existing IAM compliance controls. They can detect anomalies and potential threats, without the need of security experts. This gives employees the needed information to make correct decisions. Such progress is crucial, especially in the area of fraud detection and in the area of combating insider threats. In this way the enterprises are continuously in control, continuously secure and compliant.

  • More precise access control

Moving on from biometric passwords, it is not hard to conceive that AI could identify a user with extra security by using sight and sound. Rather than checking against pre-defined credentials, a machine would be able to understand and confirm whether a person was who they claimed to be, by using visual and aural clues. It could also learn when to grant access, and act accordingly. Permitting access on the basis machine learning is the logical next step on from biometric ID.

Working within a user’s access permissions, AI systems could also monitor in a real-time any unusual or irrational behaviour. They could detect whether a user is trying to access a part of the system they wouldn’t normally or downloading more documents than they usually would. The rhythm of a user’s keyboard and mouse movements could be observed to identify irregular or uncommon patterns. These security policies allow the companies to safely conduct their business and to rely on a better breach detection and prevention.

  • Automation and Flexibility

 AI has the capability to monitor subtle details of users’ actions, so it’s possible to automate authentication for low-risk access situations and in this way it offloads some of the burden of IAM administration from the IT department. Considering these details before granting network access makes IAM contextual and granular and can control potential problems caused by improper provisioning or deprovisioning. AI-powered systems are able to apply appropriate IAM policies to any access request based on needs and circumstances, so that the IT department doesn’t have to waste time figuring out the basics of “least privilege” for every use case or resolving problems with privilege creep.

  • Going Beyond Compliance

Many enterprises make the mistake when thinking that complying with security and privacy regulations is sufficient to keep hackers away. Actually these laws are not enough to meet the security needs of every organization. The basics of compliance refers to ensuring information is only accessed by those who need it and ignoring everyone else. The flexible and adaptable nature of AI-powered IAM is very helpful in these situations. Due to the fact that AI and ML constantly monitor traffic, learn behaviors and apply granular access controls, enterprises face less of a challenge when enforcing security protocols, and it becomes difficult for hackers to get any use out of stolen credentials.

AI is no longer some special idea that nobody can realistically implement. It becomes a trend in the cyber security environment. The high degree of interconnectivity, the increasing number of human and device identities and the common practice toward global access will force the enterprises to incorporate smarter technologies into security protocols. And to implement a risk-based approach to Identity and Access Management (IAM), the enterprises will need advanced identity analytics powered by Machine Learning (ML). Best practices across the industry have proven that ML based identity analytics delivers significant improvements to IAM architecture and program management.