Premium
Detecting misbehaving units on computational grids
Author(s) -
Martins Felipe S.,
Andrade Rossana M.,
dos Santos Aldri L.,
Schulze Bruno,
de Souza José N.
Publication year - 2010
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.1495
Subject(s) - cheating , computer science , reputation , robustness (evolution) , grid , computer security , voting , honeypot , grid computing , distributed computing , psychology , social psychology , social science , biochemistry , chemistry , geometry , mathematics , sociology , politics , political science , law , gene
Computational grids are characterized by the collaborative work among environment devices. Further, grid applications have been built based on reputation solutions. However, those applications can suffer due to attacks from malicious nodes. These nodes may not only corrupt the result from processed jobs, but also intentionally acquire a good reputation so as to obtain privileges to damage other nodes. In order to detect and isolate these malicious nodes (known as intelligent cheating nodes) from a P2P grid computing, this work proposes a system‐level diagnosis model, using a strategy based on voting and honeypots. The model is evaluated by means of scenarios that take into account different percentages of malicious and cheating nodes. Achieved results show the robustness and efficiency of our diagnosis model, once all cheating nodes can be detected, with an accuracy of 99.4% of jobs being correctly processed. Furthermore, a graphical user interface is implemented for visualizing the simulations. Copyright © 2009 John Wiley & Sons, Ltd.