With hackers' attacks growing ever more sophisticated, it may feel like a losing battle for some users or companies. However, artificial intelligence (AI) might be able to help. It uses smart algorithms to strengthen your defenses. Let’s see what connects AI and cybersecurity and how they can protect you against cyber threats.
Artificial intelligence is intelligence exhibited by machines or other non-living entities, or the creation of cognitive functions in an artificial mechanism. AI systems can be employed in a wide range of areas ranging from robotics to economics – to cybersecurity.
Here are a few essential concepts associated with AI technology.
Machine learning is the ability of a computer to identify patterns in data and to use those patterns to perform tasks and solve problems. Such a system learns from its algorithms and develops the ability to make predictions or decisions that haven't been programmed.
Due to the ability to rapidly process large amounts of data, cybersecurity systems with integrated machine learning can help predict and prevent attacks more accurately.
Expert systems are programs emulating the decision-making process of human intelligence to solve various issues. They are designed to solve complex problems by reasoning through bodies of knowledge. An expert system usually has two subsystems — the inference engine and the knowledge base. The knowledge base represents facts and rules. The inference engine uses the rules to deduce new facts.
Artificial neural networks employ paradigms allowing a computer to learn from observational data. It emulates the biological processes of the human brain. Neural networks consist of artificial neurons that send signals. The neurons also have a weight that adjusts as the learning proceeds. The weight can increase or decrease a signal.
Artificial neural networks are used for system identification, quantum chemistry, facial and image recognition, sequence recognition, data mining, and other situations.
Deep learning is a subset of machine learning based on artificial neural networks and representation learning. It uses multiple layers to progressively extract higher-layer features from input data. So, deep learning can identify specific differences and aspects of data (for example, provide quite accurate image recognition).
Today AI can be distinguished into three types.
Assisted intelligence is the most basic level of AI. Its primary aim is to automate processes and help in decision-making by using the power of big data, the cloud, and data science.
Assisted intelligence is not self-sufficient, because it requires constant intervention from human users. It just improves the processes already running. It enables people to be more productive and efficient in the things they already do.
For example, navigation systems like Waze use assisted intelligence to speed up the processes of route finding and distance calculations. We could use navigation without AI too, but it would take much longer and require more effort.
Augmented intelligence enables people to do things they couldn’t otherwise do. It is like a collaboration between machines and humans. Augmented intelligence platforms can process tons of complex data to provide experts with multi-angled information about an analyzed issue. It uses machine learning and predictive analytics not to replace human intelligence but to enhance it.
For example, augmented intelligence can be used in the medical field to reduce the possibility of human error or in financial services to calculate customers’ needs and risks.
Autonomous intelligence can operate without human input or intervention. It is the most advanced type of artificial intelligence. While this type of AI is no longer just a sci-fi fantasy but a reality, not all organizations completely trust AI-powered systems and implement them in their IT infrastructure.
So autonomous intelligence is usually employed as an adviser on which experts base their decisions.
Cybersecurity professionals can apply AI in several ways, but there are also unique challenges.
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