Technology has always been a powerful tool for shaping the world. In recent decades, there has been tremendous progress in the development and scale of information technology.

In today’s world, there are thousands of cybersecurity solutions and information technologies. One of the most remarkable developments in technology is AI-powered cybersecurity solutions.

By 2023, artificial intelligence (AI) and machine learning are the fastest growing trends in the cybersecurity industry and cybersecurity.

In fact, the latest report from Verified Market Research states that the market size of intelligent products in the cybersecurity industry is expected to increase towards the US. $80.83 billion in 2030 and the market size in 2022 is equal to $7.58 billion.

What is A.I Solution to Online Protection?

Artificial intelligence is a unique and powerful tool for providing cognitive functions to build systems. Logic and decision trees are used by AI to artificially simulate mental processes.

In this sense, AI can perform complex tasks through learning, analysis, reasoning, decision-making, etc.

AI includes many subsets and subfields such as robotics, NLP (natural language processing), machine learning, learning a deeper — which is also a product subfield is studying.

Companies can increase operational efficiencies, integrate automated analytics, deliver faster and more accurate decisions, and provide more complete datasets.

These benefits can be seen directly in AI-driven solutions AI can help companies automate routine tasks, improve risk identification, and eliminate weaknesses and risks. We will now expand on the range of AI-powered solutions and examine their impact on cybersecurity and online security.

AI-driven tools and automation of security are part of the upcoming cyber security trends in 2023. Artificial intelligence dominates in shaping the future of the cybersecurity industry and online protection.

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AI-powered malware and phishing detection, task automation, threat detection, behavior analysis, network monitoring, and vulnerability management are all going mainstream thanks to the current trends.

The main functions of AI in cybersecurity are categorized into 3 sections: detection, prediction, and response. Cybersecurity solutions supported by AI and ML (machine learning) help to mitigate human error, analyze large datasets, and detect and eliminate cybersecurity threats altogether. 

Malware and Phishing Detection 

Malware is one of the most common cybersecurity risks and is designed as malicious software to perform unauthorized actions once breached into a device or a network.

Malware functions may include file deletion, monitoring user activity, data encryption, controlling a device remotely, and many other unauthorized actions.

Also, malware comes in various forms such as viruses, trojans, worms, spyware, and ransomware. It is necessary to detect and deter such malicious software with the proper tools for your online safety. 

Although there is existing software for malware detection, their efficiency is debatable when it comes to dynamically changing malicious agents.

That’s because filtering out such codes or software is problematic. AI-powered malware detection tools are proven to be more effective for all file formats.

With machine learning, these tools not only detect but classify malware in real time. Also, there are numerous techniques for AI-driven malware detection tools such as using computer vision and neural networks. 

In the case of phishing where cybercriminals aim to acquire sensitive data through malicious links, AI and machine learning is essential for phishing detection because of the fact that billions of websites and emails exist.

Again with machine learning, AI-driven systems can analyze, classify and detect websites or emails whether they are phishing traps or not. 

AI-Powered Task Automation

AI-powered tools enable businesses to automate repetitive operations and security tasks while ensuring the utmost efficiency and accuracy.

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AI-powered task automation also helps to alleviate dependency on cybersecurity experts and human resources. For instance, incident response and patch management can be conducted by AI-based task automation. 

Additionally, AI-powered automated solutions help to streamline the process of taking proper measures after detecting cyber threats within a device, system, or network.

Taking immediate action when dealing with cyber threats is extremely crucial. Even a few seconds matter because more time equals more damage done by cybersecurity threats.

For instance, AI-powered automated solutions for threat detection and incident response process billions of network assets such as data, endpoints, requests, and users in a matter of minutes to take immediate measures whereas this isn’t possible in such a short duration without AI.

That’s because manual threat detection and incident response can take hours or even days. 

Additionally, AI-based automated compliance and governance solutions are available. These tools automatically monitor security controls, identify potential violations and report them.  

User and Entity Behavior Analytics (UEBA)

AI and machine learning can also be a part of user and entity behavior analytics where the characteristics and actions of users and entities are analyzed to detect any anomalies and identify threats.

Anomalies in user and entity behavior may indicate insider threats or APTs (advanced persistent threats). Again, detecting behavior anomalies as soon as possible is vital since insider threats can cause irreversible damage to businesses over time.

AI-powered solutions implement machine learning to learn insights and recognize behavior patterns from user and entity data. AI and ML allow solutions to improve their efficiency and accuracy in decision-making, analysis, and detection. 

Network Monitoring

Besides analyzing the behavioral patterns of users and entities, monitoring the network and all traffic is a great way to prevent any cybersecurity threats and ensure online protection.

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AI-based network monitoring enables intrusion detection and prevention systems to function precisely. Intrusions can be detected promptly and accurately with the use of AI.

For instance, AI and machine learning can be trained to determine activity patterns and characteristics of specific attack types.

Also, AI-based network monitoring allows systems to identify sudden traffic increases.  AI-based network monitoring is an effective tool for real-time threat intelligence, analysis, and response. 

Vulnerability Management and Penetration Testing

Vulnerability management and penetration testing are other areas where AI implementation is possible and available.

Every digitally connected industry has to implement vulnerability management and conduct penetration testing regularly since they are becoming increasingly appealing to cybercriminals for infiltration.

With AI and machine learning, penetration testing results can be implemented in the vulnerability management process more accurately and efficiently.   

Every day, the amount and complexity of vulnerabilities increase. In the last year alone, 22 thousand new vulnerabilities and exposures were reported. This amount of vulnerabilities isn’t suitable for manual vulnerability management.

AI-powered vulnerability management can analyze security signals and keep track of all vulnerabilities in this case.

Final Remarks

The development of AI technology has been a foundation for many remarkable tools and solutions. For cybersecurity and online protection, AI-powered solutions are now trending globally.

Since they offer improved efficiency, task automation, improved threat detection and response, and many more. But keep in mind that cybercriminals utilize AI for their malicious purposes like any other technology. 

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