📄 6. Artificial Intelligence and Security Features

The combination between artificial intelligence and security frameworks is revolutionizing the way systems, transactions, and activities are monitored and protected. More precisely, AI-powered anomaly detection is an innovative milestone in the field of cybersecurity. Making use of the immense capabilities of AI, this type of technology establishes more durable and adaptive means of protection. The paper will explain the technology in more detail and cover its multifaceted applications.

6.1 Continuous Monitoring

Continuous and uninterrupted monitoring of activities and transactions in a system is one of the most significant contributions of AI to cybersecurity. Usually, traditional security is only present through spot checks, or activity monitoring would occur under specific rules. However, AI can conduct its real-time monitoring constantly. Loading a system with a real-time system of data analysis and comparison would not be feasible or productive with a human workforce. AI can notice even the smallest discrepancies between the incoming data and its massive dataset of its entirety of previously analyzed activity. When a new transaction, command, or user action enters the system, the AI solution can immediately draw from its dataset and verify whether this action was performed, or any similar action has occurred in the past.

If the AI determines that there are no similar transactions or commands in its memory, the activity will be marked as unique. While it does not necessarily indicate that the activity is malicious, it can be noted that the unlikelihood of it being recurring makes it suspicious. In any case, the suspicious activity will be flagged by the program, at which point the system administrator will have to decide whether to investigate further. By far, the most valuable feature of AI is its ability to compare a new activity with its large dataset.

6.2 Suspicious Activities Identification

AI is not limited to monitoring. It contains complex algorithms and machine learning that allow AI to notice any patterns or behaviors that might as well be recognized as dangerous. This is a significant departure from traditional practices. Often, when guarded by human security, the AI or software lacks the immediate intervention that might be necessary to mitigate the risks. However, AI dynamically adapts to new forms of threats. Thus a high trade for which the previous ones were a small fraction of might get immediately flagged by the AI. This capacity is crucial in mitigating the threats. Because the AI can intercept the threats while they are still in the form of small transactions before they escalate into potentially devastating breaches. The AI also learns constantly. Whenever it makes a mistake, humans can rectify the mistakes, and the AI system is adjusted to recognize similar forms of attacks. As such, the AI learns from mistakes and adapts to the constantly evolving forms of cybersecurity threats.

6.3 Mitigation

An AI-driven system is intended to resist a possible threat as quickly and efficiently as possible. In this sense, it might turn to the type of response depending on the peculiarities of an anomaly detected. The mildest form of response is sending an alert – the system signals that something unusual has been detected, and it is a time for human operators to act. While sending an alert, the supporting system can make assumptions at best, while in most cases, it should limit itself to reporting a fact. At the same time, the decision regarding the actual status of a threat is performed by human operators – in this way, the system gets a safety net. Additionally, in the case of an alert, operators have more time to decide, so they can spend some of the time double-checking assumptions made by an AI system. At the same time, in the case of a clear and imminent threat, the AI can perform actions of a different scale – for instance, block a suspicious transaction or cut off a suspicious part of a network. All the responses, in this case, are predefined: they are implemented through a kind of conditional programming by the developers, so their emergency response still does not imply panicking and deciding on the spot as confusion is the last thing one might expect from an AI system. On the other hand, in such cases, it is vital for such execution to happen in real-time – an incident should be stopped at the smallest possible scale to prevent it to grow and act before doing damage.

6.4 Real-Time Operation

It is important to note that a profound characteristic of AI-based anomaly detection is that it is a tool with a real-time function. Therefore, the fact that AI systems can detect the problem, analyze it, and do everything to avoid it, has far-reaching implications in the field of cybersecurity. The traditional means of security, as one can readily observe, are deficient in that they often involve delays between the discovery of a problem and the implementation of its solution. With the modern state of cybercrime, this can be fatal. Therefore, AI shows a compelling advantage of continuous feedback and action. It is vitally important to have such a function in the field of security, especially in such applications as, for instance, surgery. Obviously, in such high-stress conditions, there can be no delays because the problems solved are too urgent.