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Effects of artificial intelligence on cybersecurity

ciberseguridad

In this article we explore the transformative effect of artificial intelligence on cybersecurity, its potential benefits, as well as defense strategies.

By Eva Kozar*

Recently, artificial intelligence (AI) has emerged as a powerful tool with applications in different fields. In the field of
cybersecurity, AI has both positive and negative implications.

In this article we explore the transformative effect of artificial intelligence on cybersecurity, its potential benefits, as well as the strategies of
defense that individuals and organizations can adopt to protect against AI-empowered threats.

Leveraging AI for stronger security
In the ever-evolving cyberspace, where threats are becoming increasingly sophisticated and dangerous, traditional security measures are becoming insufficient to safeguard critical information.

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As technology advances, so do the techniques used by cybercriminals, leading to the need for a paradigm shift in how to defend against these threats.

Artificial intelligence has emerged as a powerful ally in the battle against cyber threats, giving organizations and individuals advanced capabilities to detect, prevent and respond to attacks. By harnessing the potential of machine learning, data analytics and automation, AI is transforming the cybersecurity landscape.

Let's explore in more detail how AI can be leveraged to strengthen prevention and safety measures:

Intelligent threat detection
One of the significant advantages of artificial intelligence is its ability to analyze a large amount of data in real time. AI-powered algorithms can process and interpret complex data sets, enabling the identification of patterns and anomalies that may be indications of cyber threats.

For example, a machine learning algorithm can monitor network traffic, user behavior, and system logs to detect unusual activity or suspicious patterns. By continuously analyzing these data sources, AI can lay the groundwork for normal behavior and pinpoint any derivations that may indicate a potential security breach.

In addition, AI can detect never-before-seen or "zero-day" threats that traditional systems may miss. Thanks to their self-learning capabilities, AI algorithms can adapt to new threats and adjust their detection mechanisms accordingly. This proactive approach enables organizations to respond quickly and effectively to emerging security risks.

Example: Consider a company that uses AI-based detection algorithms for fraud monitoring and detection. The AI system identifies an unusually high volume of incoming traffic originating from an employee's workstation, even if the traffic itself seemed harmless.

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Upon investigation, it is revealed that the employee's device has been compromised, and the artificial intelligence system successfully alerts this occurrence to the security team, allowing it to neutralize the threat before significant data loss occurs.

Automated incident response
In addition to intelligent threat detection, artificial intelligence can play a fundamental role in automating incident response processes. When a security event is detected, AI systems can initiate predefined response actions to minimize response time and reduce the potential impact of the incident.

AI-based incident response platforms can autonomously analyze and prioritize security alerts based on their severity and risk of impact. By integrating this with an existing security infrastructure, these systems can automatically execute countermeasures and remediation actions, such as isolating affected systems, blocking malicious traffic, or quarantining compromised devices.

The advantage of automated incident response is its speed and accuracy. Artificial intelligence can process and respond to incidents at a rate that exceeds human capabilities, reducing the window of vulnerability and mitigating the extent of potential damage caused by a cyberattack. This, in addition to safeguarding information, protects customer satisfaction by keeping service interruptions to a minimum.

Example: Suppose a financial institution, such as a bank, implements an AI-based security system to combat phishing attempts. The system then uses natural language processing and machine learning algorithms to analyze emails received by staff in real time.

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When a suspicious email is identified, the system can automatically block it, preventing the phishing attack from reaching bank employees. At the same time, the system can trigger alerts for the security team to conduct additional investigations and provide valuable findings to strengthen defenses against similar attacks in the future.


The dark side: AI as a tool for exploitation
Although artificial intelligence offers numerous advantages, unfortunately it can also be used by cybercriminals to perform sophisticated attacks. Below we examine the main malicious uses of AI:

AI-based malware
Cybercriminals can use AI algorithms to develop advanced malware capable of evading traditional security measures. These intelligent variants of malware can adapt and mutate, making detection and containment difficult. As a result, organizations must continuously improve their security measures to counter the evolution of threats using artificial intelligence.

The Deepfake of audio and video
Deepfake technology, which relies on generative intelligence, allows fraudsters to create highly convincing videos, audio recordings or images, often imitating celebrities or individuals in political life. This technique can be used to distribute disinformation, manipulate public opinion, or even conduct targeted phishing attacks.

Social engineering attacks with AI
Artificial intelligence has the potential to amplify social engineering attacks, making them more sophisticated and compelling. This involves manipulating individuals into divulging sensitive information or performing actions that compromise security. With AI capabilities, criminals can use personalized, highly targeted approaches to trick victims into gaining unauthorized access to their data. For example, chatbots or voice assistants can simulate human interactions, making it harder to discern whether you're talking to a real person or an AI-driven entity.

Defense strategies in the age of artificial intelligence
To defend against threats from artificial intelligence, organizations must take new steps and strengthen their existing strategies. Here are some practical steps worth considering.

● AI-based security solutions: Invest in state-of-the-art security systems that use machine learning algorithms, behavioral analysis and anomaly detection. These systems can continuously adapt to emerging threats, improving detection rates and reducing false positives.
● Ethical use of AI: Maintain ethical practices to ensure that AI technologies are used responsibly. The transparent use of AI helps build trust with customers and business partners, while mitigating risk and legal implications.
● Staff training on AI: Educate employees on the latest trends and risks associated with artificial intelligence such as deepfakes or social engineering attacks, as well as provide tools and procedures to identify and report these threats. Building awareness among staff is crucial to preventing human error and strengthening overall safety.
● Collaborative information sharing: Establish alliances and join specific forums or communities to share information and best practices regarding AI-related cybersecurity threats. Collaborative efforts can help develop more effective defense mechanisms against new attacks.

Final considerations
The integration of artificial intelligence into cybersecurity brings both benefits and challenges. It's true that leveraging AI can strengthen security defenses and enable faster and more effective threat detection. However, it is very important to remain vigilant as AI-based attacks continue to evolve.

The debate around the use of this revolutionary technology continues very much, because its benefits can be easily exploited by malicious actors. However, what is undeniable is that AI is here to stay, and it is the responsibility of individuals and organizations to adapt to the challenges it entails, as well as encourage its ethical and responsible use.

* Eva Kozar was born in Hungary, is a lover of Spanish-speaking cultures, which led her to do a Master's Degree in Business Administration and Marketing at the University of Oviedo. After several years working in IT and software development, Eva joined SEON in 2020, when it only had 20 fraud managers building this innovative and disruptive technology. Since then, he has supported SEON with its successful expansion not only in LATAM, but also in the rest of the world. She is passionate about traveling, cooking and music.

Duván Chaverra Agudelo
Author: Duván Chaverra Agudelo
Jefe Editorial en Latin Press, Inc,.
Comunicador Social y Periodista con experiencia de más de 16 años en medios de comunicación. Apasionado por la tecnología y por esta industria. [email protected]

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