Artificial intelligence and machine learning (Machine Learning Methods) are actively penetrating all areas related to high technologies, and information security is no exception. The development of digital technologies and digitalization in general entails not only an increase in the number of cybercrimes, but also the improvement of schemes, as well as the emergence of complex tools.
Attacks become more dynamic, versatile, and combined. Not every new tool of the criminal has time to develop protection. This is where artificial intelligence algorithms come into play, which can help identify non-standard attacks that are invisible to existing security tools.
Artificial intelligence in information security is a tool that scans the landscape, recognizes actions and events occurring in it, and can independently make or propose a decision based on the analysis. It is especially good at finding anomalies and patterns.
Also actively used by cybercrime fighters is such a subspecies of artificial intelligence as machine learning. It helps you make forecasts and learns independently based on the data entered by a person.
The signature method involves scanning an object for malicious signatures or indicators of maliciousness that can identify a malicious file, site, ip, or attack. In signature methods, much attention is paid to the process of identifying features and forming a knowledge base, as these are key factors that affect the quality of signature algorithms.
Heuristic methods are very complex and analyze not a sample of data, but a sequence of events, for example, for detecting DDoS, Botnet, or C2C. Heuristic analysis cannot reliably confirm the detection of an attack, since the decision-making criteria are based on evaluating, classifying actions, or linking actions into safe and suspicious ones.
What tasks does artificial intelligence solve in information security?:
Let's talk about the last point in more detail. Market players see a great prospect for AI technology in cybersecurity in the direction of Edtech. New means of attack and protection, sophisticated and high-tech cybercrime schemes, and equally technological security systems are emerging, but one thing remains unchanged – the human factor. No matter how well the company's system is protected, a person can always make a mistake, especially if they do not know/follow the information security rules. This is where artificial intelligence can help, which will not only teach cyber hygiene, test its knowledge, but also monitor employees ' compliance with its rules.
Experts note that today there is no generally accepted standard for presenting threat data, and the variety of formats used slows down information processing.
Some of the data is delivered in machine – readable form, while others are delivered as "human-readable" reports. As a result, before you start analyzing data, you need to bring it to a single view model and normalize it. In order for" human-readable " text to be used, it needs to be analyzed, determine its relevance, and select information about malicious entities from the text. Machine learning technologies can be used to reduce the cost of human and time resources required for manual text processing.
The use of machine learning technologies is not a "magic pill". To a greater extent, these technologies are complementary. They help you save time and effort for a cyber threat analyst, and prepare large volumes of difficult-to-understand data. A person should still interpret the data obtained and make appropriate decisions.
Experts see a huge prospect in such AI technologies and are confident that in the near future a number of tools will be created that will be able not only to analyze, group data and offer solutions, but also to make them. But in order to determine whether the decision made by the machine is adequate, you will still need a person.
We can say that today information security tools based on artificial intelligence technologies are only being formed. It is hard to imagine how widespread their use will be in 10 years, but it is absolutely certain that it will become the basis for a new level of cybersecurity.
Attacks become more dynamic, versatile, and combined. Not every new tool of the criminal has time to develop protection. This is where artificial intelligence algorithms come into play, which can help identify non-standard attacks that are invisible to existing security tools.
Artificial intelligence in information security is a tool that scans the landscape, recognizes actions and events occurring in it, and can independently make or propose a decision based on the analysis. It is especially good at finding anomalies and patterns.
Also actively used by cybercrime fighters is such a subspecies of artificial intelligence as machine learning. It helps you make forecasts and learns independently based on the data entered by a person.
How AI is used in information security
Today, there are several scenarios in which artificial intelligence technologies are used in information security. According to experts, the most popular of them is the processing and analysis of information security reports. And this is not for nothing – people can study such reports for weeks, or even months, and manually select the necessary data. Artificial intelligence will do this in a few hours. It detects repetitions in a matter of seconds and forms vulnerabilities into defects.The signature method involves scanning an object for malicious signatures or indicators of maliciousness that can identify a malicious file, site, ip, or attack. In signature methods, much attention is paid to the process of identifying features and forming a knowledge base, as these are key factors that affect the quality of signature algorithms.
Heuristic methods are very complex and analyze not a sample of data, but a sequence of events, for example, for detecting DDoS, Botnet, or C2C. Heuristic analysis cannot reliably confirm the detection of an attack, since the decision-making criteria are based on evaluating, classifying actions, or linking actions into safe and suspicious ones.
What tasks does artificial intelligence solve in information security?:
- detection of anomalies and duplicates;
- detection of non-standard attacks and threats;
- segmentation of threat types and classes;
- continuous monitoring and analysis of threats;
- monitor and analyze traffic, user behavior, and systems;
- security policy compliance analysis;
- create security reports based on different data;
- search for data leaks;
- testing employees for knowledge and compliance with the rules of cyber hygiene.
Let's talk about the last point in more detail. Market players see a great prospect for AI technology in cybersecurity in the direction of Edtech. New means of attack and protection, sophisticated and high-tech cybercrime schemes, and equally technological security systems are emerging, but one thing remains unchanged – the human factor. No matter how well the company's system is protected, a person can always make a mistake, especially if they do not know/follow the information security rules. This is where artificial intelligence can help, which will not only teach cyber hygiene, test its knowledge, but also monitor employees ' compliance with its rules.
Machine Learning in cybersecurity
Separately, we should focus on such a branch of artificial intelligence as machine learning. It is in information security that machine learning is actively gaining momentum as a way to analyze, segment and reduce information to one type, as well as identify patterns.Experts note that today there is no generally accepted standard for presenting threat data, and the variety of formats used slows down information processing.
Some of the data is delivered in machine – readable form, while others are delivered as "human-readable" reports. As a result, before you start analyzing data, you need to bring it to a single view model and normalize it. In order for" human-readable " text to be used, it needs to be analyzed, determine its relevance, and select information about malicious entities from the text. Machine learning technologies can be used to reduce the cost of human and time resources required for manual text processing.
The use of machine learning technologies is not a "magic pill". To a greater extent, these technologies are complementary. They help you save time and effort for a cyber threat analyst, and prepare large volumes of difficult-to-understand data. A person should still interpret the data obtained and make appropriate decisions.
Result
Artificial intelligence and information security will be inextricably linked in the future. At the moment, the role of AI and machine learning is more supportive and helps a person reduce the load created by a large layer of data for analysis.Experts see a huge prospect in such AI technologies and are confident that in the near future a number of tools will be created that will be able not only to analyze, group data and offer solutions, but also to make them. But in order to determine whether the decision made by the machine is adequate, you will still need a person.
We can say that today information security tools based on artificial intelligence technologies are only being formed. It is hard to imagine how widespread their use will be in 10 years, but it is absolutely certain that it will become the basis for a new level of cybersecurity.
