WebRTC Expert Feature

May 13, 2022

Why Artificial Intelligence Is The Future Of Cybersecurity

As the world becomes increasingly digitized, so does the landscape of cybersecurity threats. In response, security professionals are turning to artificial intelligence (AI) to help them keep pace with the ever-changing threat landscape, automate repetitive tasks, and improve their overall security posture.

AI has already begun to transform the cybersecurity industry, and its impact will only become more pronounced in the years to come. Here are four ways AI is shaping the future of cybersecurity:

Machine learning for detection and response: Machine learning is an AI that involves training computers to learn from data and improve their performance over time. Like browser protection, machine learning can be used for various tasks, including detecting and responding to cyber threats.

Machine learning can identify both known and unknown threats when detecting. Known threats are those that have been seen before and have been well-documented. On the other hand, unknown threats have not been seen before and are more difficult to detect.

Automated threat intelligence: Threat intelligence is information about current and emerging cybersecurity threats. It can include data about the techniques attackers are using, the vulnerabilities they exploit, and the tools and tactics they employ.

Threat intelligence is traditionally gathered manually by security analysts who spend their days sifting through data from various sources. However, this process is time-consuming and often results in analysts missing important information.

On the other hand, Automated threat intelligence uses AI to gather and analyze data from various sources. This allows analysts to quickly and easily identify trends and patterns in the data, which can help them more effectively defend against attacks.

Enhanced phishing detection and prevention: Phishing is a type of cyber attack in which attackers send fraudulent emails or messages to trick victims into divulging sensitive information, such as login credentials or financial data.

Phishing attacks are becoming more sophisticated, making it difficult for traditional security solutions to detect. AI, however, can identify phishing attacks. Additionally, AI can analyze emails or messages and determine whether it is likely a phishing attempt. This allows organizations to take steps to prevent attacks before they happen.

Next-generation antivirus software is designed to detect and remove malicious software, or malware, from computers and devices. However, traditional antivirus solutions are often ineffective against new or unknown malware.

AI-powered antivirus solutions can detect and remove even the most sophisticated malware. Additionally, AI can be used to analyze data about new threats and create signatures that can be used to detect and block future attacks.

Improving security operations: Security operations manage and enhance an organization's cybersecurity posture. It includes tasks such as identifying and remediating vulnerabilities, investigating incidents, and responding to attacks.

AI can automate many of the tasks involved in security operations, including vulnerability management and incident response. By automating these tasks, organizations can free up resources that can be used for other tasks, such as developing new security controls or investigating attacks.

Reducing false positives: A false positive is a security alert generated when there is no actual threat. False positives can occur for various reasons, such as the incorrect configuration of security tools or regular activity misinterpreted as malicious.

False positives can be frustrating for security analysts and the users they support. They can also lead to wasted time and resources as analysts investigate alerts that turn out to be nothing.

AI can be used to reduce false positives by analyzing data from multiple sources and only generating alerts when there is a real threat. This helps to ensure that analysts are only investigating actual threats, which saves time and resources.

Improving incident response: Incident response identifies, contains, and mitigates the effects of a security incident. It is a critical part of an organization's cybersecurity posture.

AI can be used to improve incident response in several ways. For example, AI can automatically identify and isolate infected systems. Additionally, AI can analyze data from an incident and provide recommendations for remediation.

Enhancing application security: Application security is protecting applications from security threats. It includes identifying and remediating vulnerabilities, implementing security controls, and responding to attacks.

AI can be used to improve application security in several ways. For example, AI can be used to scan code for vulnerabilities automatically. AI can also be used to monitor application behavior and identify unusual activity that may indicate an attack.

AI is quickly becoming a critical part of cybersecurity. It is being used to improve a variety of tasks, from identifying phishing attacks to responding to incidents. AI-powered solutions are helping organizations improve their cybersecurity posture and protect their data.

About the Author

Jason Boot is the Toronto-born author who spends most of his time working on his scripts for his show “Cybershorts.” His dedication to unearthing everything you need to know about cybersecurity is second to none and has made him a self-proclaimed “Prince of Protection.”


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