There was a time not too long ago when the idea of any kind of artificial intelligence (AI) technologies being involved in cyber security would have been seen as something of a pipe dream. However, with advances in cyber security technologies and those that enable and enhance artificial intelligence such as automation, machine learning and pattern and behavior recognition, this is no longer the case. What we see today are numerous cases in which artificial intelligence technologies are being developed and implemented with cyber security in mind. What has also become clear is the potential AI and its associated technologies have to transform and shape the current cyber security landscape as well as its future.
Given the sophistication of modern cyber threats and the increasing number of attack vectors as Internet of Things device usage grows, security solutions will need to be adaptive, intelligent and increasingly automated. The growing adoption of these technologies across a large number of industries will also mean that new vulnerabilities will need to be dealt with as new applications for AI are developed.
Artificial Intelligence technologies enable cyber security architectures to have all of the above mentioned characteristics. From being able to adapt to new threats and detect anomalous behavior patterns to advanced network traffic monitoring and automated malware detection, artificial intelligence technologies are currently being put to use in order to enhance a vast collection of cyber security systems and functions. Far from the self-aware, unfeeling machines often portrayed in movies, artificial intelligence is now at the cutting edge of cyber security technologies and will likely be a common and well developed in the majority of systems in the not too distant future.
AI technologies also provide much more analytical power than singular human IT security officers and can thus deal with much larger volumes of data in a much shorter space of time than their human counterparts. They are also capable of operating 24 hours a day, seven days a week without the need for food or sleep and are a much cheaper alternative to hiring human analysts and network managers. However, these aren’t the only reasons why artificial intelligence in cyber security has come about and grown so quickly. As previously mentioned, AI and its associated technologies have great potential for further enhancing cyber security applications and functions, and this has not gone unnoticed by those looking to secure their computer networks, accounts and devices from cyber threats.
How Will Artificial Intelligence Transform Cyber Security?
There are a multitude of ways in which artificial intelligence is making an impact on cyber security and, in this section, we’ll be taking a look at four areas of cyber security where AI is currently showing the most potential. These four areas are cyber attacks, device security, identification and authorization, and data handling and they cover the broad range of functions and security operations that artificial intelligence is currently be applied to. As we’ll see, AI and machine learning can remove large parts of a security analyst or operators workload, and even perform the same functions much better in much shorter period of time.
When most people think cyber security, they think of protecting against cyber attacks such as distributed denial of service (DDOS) attacks, malware, phishing, man-in-the-middle (MITM) attacks and so on. These types of cyber threats can cause significant amounts of physical damage and wreak havoc on a computer network or industrial control system (ICS). However, with advanced pattern recognition and predictive capabilities, threats such as malware, for example, can be far more easily identified and dealt with as opposed to older, signature-based methods that would rely on the threats being known beforehand.
DDOS attacks are notoriously hard to predict and defend against and often is the case that security analysts chose to mitigate their effects rather than attempt the almost impossible and try to prevent them all together. This would be a costly waste of security and human resources and is unlikely to provide much assistance in the event of an actual attack. Artificial intelligence enables large scale monitoring of network resources in order to quickly spot abnormal network resource allocation and enact an efficient and automated response. This would also allow for a more efficient allocation of human security resources as well as enhanced threat mitigation when it came to DDOS attacks.
With the Internet of Things (IoT) currently revolutionizing how people and business interact and connect with their devices, device security is one of the top priorities of many security analysts and operators. This down to the increasing number of attack vectors that the current and predicted continued growth of connected devices is also driving. Traditionally, connected devices were protected via security updates that would often come as and when new threats or vulnerabilities where reported. This could often be a long time after their effects have started to be felt and could often be too little too late especially when combined with a poor or no cyber security policy or standard operating procedures.
With artificial intelligence, network level behavior analytics can be combined with user behavior patterns in order to accurately detect when a device may have been compromised and take appropriate action such as blocking that device from accessing the network and making the relevant people aware of the situation in real-time. The advantage here is that AI systems are not only able to provide protection at the network level across large scales, but also their capability of real-time data analytics, something we’ll go into more shortly, to provide accurate and reliable information about a scenario.
One of artificial intelligence’s biggest benefits is the sheer amount of data it is capable of processing, understanding and then interpreting that information in a way that is useful for human cyber security analysts. However, not only could AI process a large amount of data, it can also learn from it without the need for human intervention or programming. This capability would be key in helping to detect and mitigate Zero-Day attacks where the threat being faced is unknown to the system or security analysts. Once a system can learn from the data it takes in, it should start to teach itself new ways in which to protect against threats by running “what if” scenarios and working out the best ways to deal with each type of threat it has faced.
As threats continue to evolve, so will AI systems and their related technologies. This is one of the main advantages of AI’s data handling abilities. Being able to learn from previous experience while also internally testing out new ways in which threats can be dealt with and mitigated will give those organizations a decisive advantage over those who are yet to adopt AI based technology and continue to rely on older generation or lesser advanced security products.
The more one looks into the role of artificial intelligence in cyber security, the more one can’t help but feel this technology will be a game-changer once it is refined and fully developed into cyber security architectures as standard. There is still much debate as to whether general or artificial super intelligence is either physically or ethically possible, however, with advances in wireless communications technologies enabling greater levels of device connectivity and integration, an intelligent, adaptive and automated solution will be needed. Artificial intelligence and its related technologies, when applied to cyber security, seem to fit the bill perfectly.