<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>This paper applies the emotion extraction method based on emotion lexicon to the group emotion analysis of the information system, combines the vector space model to process the text emotion in the information system, expresses the emotion in the form of vectors, and divides the different types of emotion according to the distance between the emotion vectors for identification. The five-level index system in fuzzy mathematics is chosen to measure the value of emotional intensity, and by analyzing the emotional state of the group in the information leakage incident, a decision in line with the user’s emotion is made based on the emotion of the information system security. Accordingly, the security defense index of the information system is improved according to the information security risk index. The results show that in identifying the emotions of the information system security events, the group’s emotions are mainly biased towards the negative. The proportion of negative emotions is the largest of 98%, which indicates that attention should be paid to the confidentiality of the user group’s information in the security of the information system. The maximum security event risk value in the evaluation in the information system is in the T8 period, with a value of 0.819, indicating that the security defense of the information system should be strengthened in the T8 period.</p>
</abstract>

This paper applies the emotion extraction method based on emotion lexicon to the group emotion analysis of the information system, combines the vector space model to process the text emotion in the information system, expresses the emotion in the form of vectors, and divides the different types of emotion according to the distance between the emotion vectors for identification. The five-level index system in fuzzy mathematics is chosen to measure the value of emotional intensity, and by analyzing the emotional state of the group in the information leakage incident, a decision in line with the user’s emotion is made based on the emotion of the information system security. Accordingly, the security defense index of the information system is improved according to the information security risk index. The results show that in identifying the emotions of the information system security events, the group’s emotions are mainly biased towards the negative. The proportion of negative emotions is the largest of 98%, which indicates that attention should be paid to the confidentiality of the user group’s information in the security of the information system. The maximum security event risk value in the evaluation in the information system is in the T8 period, with a value of 0.819, indicating that the security defense of the information system should be strengthened in the T8 period.

Emotional Computing Technology Applications in Information Systems Security and Their Risk Prevention

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

This paper applies the emotion extraction method based on emotion lexicon to the group emotion analysis of the information system, combines the vector space...

Emotional Computing Technology Applications in Information Systems Security and Their Risk Prevention

Publié en ligne: 26 févr. 2024

Pages: -

Reçu: 02 janv. 2024

Accepté: 08 janv. 2024

DOI: https://doi.org/10.2478/amns-2024-0335

Mots clés
Emotion vector, Vector space model, Emotion recognition method, Information system security, Risk index

© 2024 Gaofeng Huang et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Emotional Computing Technology Applications in Information Systems Security and Their Risk Prevention

Publié en ligne: 26 févr. 2024

Pages: -

Reçu: 02 janv. 2024

Accepté: 08 janv. 2024

DOI: https://doi.org/10.2478/amns-2024-0335

Mots clésEmotion vector, Vector space model, Emotion recognition method, Information system security, Risk index

© 2024 Gaofeng Huang et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Mots clés
Emotion vector, Vector space model, Emotion recognition method, Information system security, Risk index