Why is artificial intelligence key to cybersecurity?

To understand why artificial intelligence (AI) is an important tool in the cybersecurity toolbox today and in the future, you must first understand how the threat landscape is evolving and what threats Internet users face every day .

Evolving Threat Landscape

The global threat landscape is changing. Internet consumers now face a very different threat. On the one hand, there are massive, highly automated botnets infecting consumer devices. Social engineering (or phishing) attacks, on the other hand, attempt to defraud users of their money and data.

The scale of the botnet threat is growing, according to researchers: Device adoption data from the roughly 1.7 billion connected devices in North America shows that many Internet of Things (IoT) devices are becoming increasingly popular. Among these devices, threats to IP cameras and network-attached storage (NAS) devices are of particular concern because malicious actors target them more frequently than other devices.

At the same time, mobile devices (phones, tablets, and smartwatches) remain the most popular devices and face different threats. Security data from CUJOAI shows that nearly 60% of mobile device threats are related to unsafe browsing: millions of devices are accessing malware distribution, spam and spyware websites. Worryingly, approximately 20% of mobile browsing threats come from phishing campaigns – one of the most difficult threats to combat due to the ephemeral nature of phishing websites.

Using Artificial Intelligence Today to Fight Threats

In the past, security solutions were largely reactive: Researchers at a cybersecurity company would discover a new malware sample, analyze it, and Added to malware list. The industry still uses this approach, but is acting more proactively, especially when it comes to dealing with social engineering threats.

Machine learning or artificial intelligence algorithms have played a key role in this transformation. While they are not a one-stop solution to all cybersecurity problems, they are useful for quickly automating decision-making processes and inferring patterns from incomplete or changed data. These algorithms first learn from real-world data, such as existing security threats and false positives, as well as the latest threats discovered by researchers around the world.

Artificial intelligence algorithms are pattern detection machines that offer significant advantages over traditional list-based security systems. Artificial intelligence augments and outperforms these systems by detecting new threats that exhibit suspicious patterns. The learning process to reach this stage of AI proficiency is substantial and can only be achieved using robust data sources for each threat vector.

Machine learning systems are not magical and can make mistakes. Nonetheless, once algorithms have a small enough margin of error, they become indispensable in online security, as fast decision-making processes reduce user friction and do not negatively impact the user experience. This is key to enhancing cybersecurity at scale and is a welcome side effect of using artificial intelligence in cybersecurity. It not only improves security but also covers a large portion of the threat environment.

Due to their nature, AI algorithms can protect against a number of new threats: security threats, malware and countermeasures, often developed from previous exploits and malware. Relatively few truly novel threats emerge each year: most malicious actors are not developers, but users of malware-as-a-service kits or modifiers of existing leaked malicious code. Researchers revealed in a recent study on the evolution of the Sysrv botnet that most new malware strains are combinations and recombinations of other existing malicious code.

Because these linearly evolving threats are often able to avoid standard anti-malware detection, artificial intelligence is a useful tool for enhancing cybersecurity around the world. Simple tweaks are rarely enough to defeat these algorithms.

Based on past experience, the use of artificial intelligence algorithms to enhance the protection of tens of millions of families has been a huge success. has successfully combined the best practices of existing cybersecurity solutions with advances in machine learning to produce an extremely low-friction security solution that enables network operators to protect their consumers. At the scale of CUJOAI, AI can help prevent approximately 10,000 threats every minute.

Using Artificial Intelligence to Combat Future Threats

Perhaps one of the most exciting and valuable achievements of artificial intelligence in cybersecurity is the ability to detect suspicious websites, including phishing websites, before users visit them Give it a warning. Because social engineering attacks often cause the most damage and loss to consumers' privacy and finances, it's extremely important to use artificial intelligence to stop new attacks before they appear on industry databases.

Looking to the future, cloud-based AI-driven cybersecurity also has a critical capability beyond standard antivirus and firewalls, as it can be deployed on routers to enhance protection for all devices on a given network. This is very important because according to statistics, about 50% of Internet-connected devices cannot run anti-virus software.

The future of consumer cybersecurity is unimaginable without artificial intelligence, especially when it comes to the scale and threat of social engineering and IoT malware.

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