Volume 7, Issue 4, August 2014, Pages 785 - 795
ACO-BTM: A Behavior Trust Model in Cloud Computing Environment
Guoyuan Lin, Yuyu Bie, Min Lei, Kangfeng Zheng
Available Online 1 August 2014.
- https://doi.org/10.1080/18756891.2013.864479How to use a DOI?
- cloud computing, behavior trust, ant colony optimization, trust pheromone, heuristic pheromone
- Considering trust issues in cloud computing, we analyze the feasibility of adopting ant colony optimization algorithm to simulate trust relationships between entities in the cloud and then propose a novel behavior trust model: ACO-BTM. Trust relationships between entities in cloud computing are dynamic, uncertain and hard to quantify. ACO-BTM introduces the conception of ‘pheromone’ and transition probability to represent behavior trust. Then, it focuses on the research of dynamic trust evaluation, time constraint and some other issues. Furthermore, a detailed algorithm process of behavior trust evaluation is given in this context. Finally, ACO-BTM is applied to cloud computing platform to simulate the establishment of behavior trust relationships. The simulation experiment verifies that trust degree change with time varies and the frequency of interactions. Compared with the other model, ACO-BTM can provide better trust recommendation services and protect against attacks of malicious nodes effectively in cloud computing environment. It is proved that ACO-BTM has good flexibility, accuracy and robustness.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - JOUR AU - Guoyuan Lin AU - Yuyu Bie AU - Min Lei AU - Kangfeng Zheng PY - 2014 DA - 2014/08 TI - ACO-BTM: A Behavior Trust Model in Cloud Computing Environment JO - International Journal of Computational Intelligence Systems SP - 785 EP - 795 VL - 7 IS - 4 SN - 1875-6883 UR - https://doi.org/10.1080/18756891.2013.864479 DO - https://doi.org/10.1080/18756891.2013.864479 ID - Lin2014 ER -