A Trust Model with Tolerance against the Behavior of Malicious Users

Nowadays, in spite of the presence of defense mechanisms
and verification methods, parts of the security vulnerabilities still remain in
systems. Therefore, protecting systems against all malicious behaviors and
security attacks is nearly impossible. If the required countermeasures are not
employed against the impacts of malwares, they may lead to intrusion and the
violation of system security policies. On the other hand, intrusion-tolerant
systems are used to increase the security of systems and software. Considering
the concept of trust among the entities can play an important role to increase
the security in distributed environments such as Internet. However, like other
security mechanisms, trust is vulnerable to malicious attacks. Therefore,
devising methods against malicious behaviors are very important. In this paper,
a trust­-based approach for tolerating software against intrusion with emphasis
to the relativity of trust concept is presented. So that, the precision of
trust values for users in the whole system is increased, such that these values
are closed to real values. The goal of the proposed approach is to diminish the
challenges of absolute trust in order to make systems resilient against
malicious behaviors through detecting real and non-real ideas of users and
balancing them. The simulation results show that the proposed approach does not
allow intruders to increase trust values unfairly and it is resilient against
malicious and destructive behaviors. Furthermore, the addition of relativity to
trust concept and the detection of malicious users lead to the improvement of
the recommended method, comparing to the existing methods.