Detection and prevention of Cybercrime: A solution based on Artificial Intelligence and Cognitive Psychology.

Walter Fuertes Díaz – ESPE

Currently, academia and industry have shown that solutions for cybercrime do not focus only on protecting software systems and cyberspace with technical mechanisms (Cybersecurity) [3]. It involves understanding and addressing human behavior, discerning people's actions, reactions and responses to situations, stimuli and environments (Cognitive Psychology). Experience establishes that users are often the most susceptible link to Social Engineering attacks as they are deceived by psychological manipulation tactics used by cybercriminals. This essay explores how the combination of AI and cognitive psychology can improve the ability to anticipate, detect and prevent cyber threats and vulnerabilities.

Cybercrime availability and security of systems, information and users around the world [1]. The consequences range from financial losses, violation of privacy, to possible impact on national sovereignty. [2]. In response to this challenge, a strategy emerges to harness the power of machine learning and other AI approaches [3], along with an understanding of the human cognitive processes involved in online criminal actions, to develop solutions against cybercrime. [4] .

Cybercrime encompasses any illicit activity carried out through ICT through the use of computers and electronic devices in their connection with cyberspace [5] . This includes a wide variety of cybercrimes, including the theft of personal data, online fraud, ransomware, phishing or banking fraud, attacks on web applications, and state infrastructure.

Cybersecurity is defined as the preservation of information in cyberspace [6]. This involves protecting it against various cyber threats, such as cyber attacks, cyber espionage, online fraud, and data theft. AI refers to human-designed systems that imitate or replicate cognitive functions associated with human intelligence [7].

Finally, Cognitive Psychology studies mental processes such as the acquisition of knowledge, perception, memory, reasoning and decision making. Its goal is to understand how the human mind processes information, organizes thoughts, stores and retrieves memories [8].

Now, in relation to the techniques of applying AI with Cognitive Psychology to combat cybercrime, various Machine Learning (ML) algorithms are used. Among them are: Artificial Neural Networks (ANN), Support Vector Machines (SVM), Decision Trees (DT), Random Forests (RF) and Deep Learning (DL). Additionally, Natural Language Processing (NLP) and Unsupervised Machine Learning, such as clustering and anomaly detection, are used to identify suspicious behavior in network traffic or event logs [9].

In relation to the application of cognitive security techniques to combat cybercrime, algorithms incorporate principles and concepts of cognitive psychology in the design and implementation of cybersecurity solutions. These include modeling human behavior to understand users' interaction with computer systems and their susceptibility to social engineering. They also cover risk analysis and decision making , identifying cognitive biases and developing strategies to mitigate their impact. Additionally, the social engineering and psychological manipulation tactics used by cybercriminals are considered. [10][11].

Regarding the integration of AI and cognitive psychology, various applications to combat cybercrime. They include Advanced Threat Detection , as AI can analyze large volumes of data to identify anomalous behavior patterns. Fraud prevention, when used to develop predictive models that identify suspicious financial transactions or fraudulent activities online. User authentication , as AI can analyze user behavior, such as typing and browsing patterns, to detect phishing attempts or unauthorized access to online accounts. By combining this with cognitive psychology's understanding of signals of deception and manipulation in human interaction, it is possible to develop more robust and secure authentication systems, among others.

Other examples are preventing Social Engineering attacks , such as phishing and ransomware, by training ML algorithms to identify infected emails and other phishing attempts [13]. It also improves biometric authentication , using AI to develop systems that use unique physical traits such as fingerprints, facial recognition or voice patterns. In addition, AI is used in sentiment analysis on social networks to detect suspicious conversations or activities related to cybercrime.

Regarding new challenges and future lines of research in the application of AI and cognitive psychology in cybersecurity, they continue to be developed [14][15][16]. However, it still faces many challenges including ethical and privacy concerns ; It should be emphasized that cybercriminals also use AI and cognitive psychology, which highlights the importance of constant innovation.

In summary, the combination of AI and cognitive psychology provides a comprehensive approach to anticipate, detect and mitigate cyber threats. This synergy allows us to develop more effective solutions to protect systems, data and users against growing threats in cyberspace. It is crucial to promote a culture of cybersecurity through awareness strategies and cyberattack prevention training. For companies, it is essential to invest in protection mechanisms for the security of user information, their data and organizations.

References

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