Artificial Intelligence and data in cybersecurity: fighting evolving threats

December 18, 2023

Tags: Technologies



Artificial intelligence, this is perhaps the phrase that has been heard, said and read the most in recent years and it is no coincidence: the use that has been given to this technological solution has grown impressively, becoming something that only experts in the field used it, to be in the hands of the common user. The area of cybersecurity does not escape AI.


Keeping data and other components of a software product protected is not a light task nor one that should be neglected, which is why using artificial intelligence as an aid is a smart move and one that we recommend.





Growth in the use of cybersecurity solutions in the world


Considering improving and strengthening the cybersecurity area in a company or software product is not a fortuitous option. Over the years, threats from hackers and programmatic viruses have become increasingly harmful and have “fatal” consequences, capable of bankrupting any company.


“By 2023, the cybersecurity market is projected to reach an impressive $166.2 billion worldwide. Among the various market segments, security services are expected to dominate with a projected market volume of $87.97 billion in 2023,” revealed figures from a study by Statista.


With this growth in cybersecurity, it is logical that it be used together with artificial intelligence, perhaps the most popular and widely used technology today. According to data from Statista, “the AI market size is projected to increase from US$241.8 billion in 2023 to nearly US$740 billion in 2030, representing a compound annual growth rate of 17.3%.”.




Uses of artificial intelligence in cybersecurity


Artificial intelligence (AI) plays a crucial role in improving cybersecurity measures, providing advanced capabilities to detect, prevent and respond to cyber threats. Below are some key uses of AI in cybersecurity:


Threat detection and prevention


  • Anomaly detection: AI algorithms analyze patterns of normal behavior in networks and systems. Deviations from these patterns, which may indicate potential threats, can be identified in real time.
  • Behavioral Analysis: AI can analyze the behavior of users and entities to detect suspicious activity or deviations from normal behavior, helping to identify potential insider threats.


Security endpoint


  • AI-powered antivirus: Traditional signature-based antivirus solutions are complemented by AI-powered antivirus programs that can identify and block new and unknown threats based on behavioral analysis.
  • Endpoint Protection Platforms (EPP): AI-powered EPP solutions provide real-time protection against malware and other threats to endpoints by continually learning and adapting to new attack methods.


Network security


  • Intrusion Detection and Prevention Systems (IDPS): AI enhances IDPS by analyzing network traffic patterns and identifying potential intrusions or malicious activities, enabling immediate response.
  • Firewall Management: AI helps optimize firewall rules and policies, adapting to evolving threats and ensuring more efficient network security.




Email Security


  • Phishing Detection: AI algorithms can analyze email content, sender behavior, and other factors to detect and block phishing attempts, protecting organizations from email-based threats.
  • Email Filtering: AI-based email filtering solutions can identify and filter malicious attachments, links and content, reducing the risk of malware infections.


User authentication and access control


  • Behavioral biometrics: AI can analyze user behavior, such as typing patterns and mouse movements, to create unique user profiles. Any deviation from these profiles may trigger alerts of possible unauthorized access.
  • Adaptive access control: AI-powered access control systems can dynamically adjust access permissions based on user behavior and contextual factors, minimizing the risk of unauthorized access.


Incident response


  • Automated incident analysis: AI can help quickly analyze and prioritize security incidents, providing valuable information to cybersecurity professionals and helping them respond faster to potential threats.
  • Orchestration and automation: AI-powered orchestration platforms automate incident response processes, enabling rapid containment and mitigation of cyber threats.




Monitoring and Continuous Adaptation


  • Machine learning for adaptive defense: AI systems can continually learn from new data and adapt to evolving threats, providing a more proactive and dynamic defense against cyberattacks.


By leveraging AI in these various ways, organizations can significantly improve their cybersecurity posture, staying one step ahead of cyber threats in an increasingly complex and dynamic digital landscape.


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