How AI and ML are Used in Cybersecurity?
Artificial Intelligence (AI) and Machine Learning (ML) are booming technologies used in the cybersecurity industry to automate the process of detecting cyber threats. Nowadays, with the enhancement of Information Technology (IT), the techniques and tricks to attack the organization’s network and systems are becoming more complex. Cybersecurity teams find it challenging to analyze and take appropriate action against the identified security threat.
Table of Contents
AI and ML
How is AI used in cybersecurity?
How is ML used in cybersecurity?
Advantages of using AI and ML
Companies using AI and ML for cybersecurity
Fortunately, AI and ML technologies are making it possible to automate the process of identifying, analyzing, and responding to millions of cybersecurity threats. Many companies are leveraging the support of AI and ML to combat security threats and enhance organizations’ security posture.
AI and ML
Artificial Intelligence is the main branch of Machine Learning and Deep Learning designed to analyze millions of security risks, speed up the incident response process and help enhance security operations. It refers to the algorithms and techniques that mimic human intelligence to perform business operations that require human intelligence.
Machine Learning (ML) is a part of Artificial Intelligence designed to execute algorithms in AI and allow learning from past use cases to enhance the security posture. It will enable the system to learn from the training data and detailed applications.
How is AI used in cybersecurity?
AI is used in many areas of cybersecurity to protect organizations from attackers. It helps to eliminate the cyber attacker’s activities and automates the threat detection and response process more effectively than traditional methods. The following are the various applications of AI in cybersecurity:
- Detecting New Security Threats: AI technology helps to identify security threats and malicious activities automatically using algorithms in the system. AI systems help identify threats, run patterns, and detect anomalies effectively.
- Endpoint Protection: AI plays a significant role in securing the endpoints while many devices are connected remotely. AI-driven endpoint protection creates a secure connection with the devices. If any abnormal activities are triggered, the AI will identify and take action to protect from cyber-attacks.
- Identity Analytics and Fraud Detection: AI helps create models to identify the system’s fraud patterns and helps reduce fraudulent threats.
- IT Asset Inventory: AI systems help predict IT asset inventory and vulnerable threats that create an attack surface. It helps to plan and assign resources to the vulnerable region to fix it before an attacker attempts to exploit the system.
- Smart Botnets: AI and ML are used to analyze website traffic and differentiate the good bots, bad bots, and humans. AI and ML analyze the abnormal activity of the bot using behavioral patterns. It also allows us to understand the invention of bad bots and prevents serious security threats such as data theft.
- Automated Malware Detection and Prevention: AI helps to automate the threat detection and response process more than traditional software-driven processes. It improves the process of detecting unknown malware using AI and ML techniques and algorithms.
How is ML used in cybersecurity?
ML is used in cybersecurity by understanding past cyber attack experiences and improving security processes. It helps the security team to identify, prioritize, respond, and remediate cyber-attacks quickly. The following are various applications of ML in cybersecurity:
- Automated Security Workflow: ML helps to automate the time-taking repetitive process such as malware analysis, security assessments, and network log analysis. It allows organizations to accomplish tasks much faster and mitigate cyber threats.
- Network Risk Scoring: ML is used to analyze past cyberattack data sets and define the area of networks involved in the cyber attack. The network risk score helps quantify the cyberattack’s impact and helps organizations fix the vulnerabilities before malicious attackers exploit them.
- Threat Detection and Classification: ML automatically analyzes the big data sets of security events and attack patterns for detecting and responding to similar cyberattacks. It uses the Indicators of Compromise (IOCs) data sets to define the behavior of malware and helps to monitor, detect, and respond to security threats.
Advantages of using AI and ML
Many organizations incorporate AI and ML technologies in cybersecurity to avail the following advantages:
- Increases the Detection and Response Process: AI and ML help to analyze huge chunks of data very quickly. It implements security patches and mitigates cybersecurity threats in real time by enhancing the response time.
- Improves Security Posture: The organization’s security posture becomes robust with AI and ML technologies and proactively identifies malicious activities. It also protects the security infrastructure at micro and macro levels to achieve effectiveness.
- Reduces the Workloads: AI and ML reduce the workload for Security Analysts by automating the threat detection and responses process with less time than a manual process. With the help of AI and ML methods, the Security Analyst can manage complex security threats with less effort.
- Low IT Cost: AI and ML are cost-effective technologies for detecting and responding to cybersecurity threats.
AI and ML will have a prominent role in the cybersecurity industry in the upcoming years. The AI market is predicted to reach $38.2 billion in 2026, becoming integral to cybersecurity. AI and Ml are great weapons to fight against complex cybersecurity threats in today’s competitive world.
Companies using AI and ML for cybersecurity
The following are some of the companies using AI and ML technologies for cybersecurity:
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