Malicious human behaviour in information system security: Contribution to a Threat Model for Event Detection Algorithms

Olivier de Casanove (1, 2) , Florence Sèdes (1, 2)

1 IRIT-SIG - Systèmes d’Informations Généralisées
2 UT3 - Université Toulouse III - Paul Sabatier

Among the issues our community has to fix, information system security is a global concern both for the security of data and algorithms. The security of algorithms is dependent of the reliability of the input data. This reliability is questioned, especially when the data is generated by humans (or bot operated by humans), like in online social networks. Event detection algorithms are an example of technology using this type of data, but the question of the security is not systematically considered in this literature. We propose in this paper a first contribution to a threat model to overcome this problem. This threat model is composed of a description of the subject we are modelling, assumptions made, potential threats and defense strategies.

Mots clés: Threat model; Adversarial Learning; Online Social Network; Event Detection

Domaines: Informatique [cs]; Cryptographie et sécurité [cs.CR]; Réseaux sociaux et d'information [cs.SI]; Ordinateur et société [cs.CY]

Olivier de Casanove, Florence Sèdes. Malicious human behaviour in information system security: Contribution to a Threat Model for Event Detection Algorithms. 2022. ⟨hal-03815005v2⟩