IEEE Transactions on Software Engineering - Special issue on computer security and privacy
Efficient algorithms for distributed snapshots and global virtual time approximation
Journal of Parallel and Distributed Computing - Special issue on parallel and discrete event simulation
Distributed snapshots: determining global states of distributed systems
ACM Transactions on Computer Systems (TOCS)
Intrusion detection using autonomous agents
Computer Networks: The International Journal of Computer and Telecommunications Networking - Special issue on recent advances in intrusion detection systems
Distributed Snapshots for Mobile Computing Systems
PERCOM '04 Proceedings of the Second IEEE International Conference on Pervasive Computing and Communications (PerCom'04)
A Grid-based Intrusion Detection System
ICNICONSMCL '06 Proceedings of the International Conference on Networking, International Conference on Systems and International Conference on Mobile Communications and Learning Technologies
Dependency-based distributed intrusion detection
DETER Proceedings of the DETER Community Workshop on Cyber Security Experimentation and Test on DETER Community Workshop on Cyber Security Experimentation and Test 2007
ACM Computing Surveys (CSUR)
When gossip is good: distributed probabilistic inference for detection of slow network intrusions
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
A symmetric localization algorithm for MANETs based on collapsing coordinate systems
HiPC'05 Proceedings of the 12th international conference on High Performance Computing
Incremental aggregation of latent semantics using a graph-based energy model
SPIRE'06 Proceedings of the 13th international conference on String Processing and Information Retrieval
Towards a grid-wide intrusion detection system
EGC'05 Proceedings of the 2005 European conference on Advances in Grid Computing
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Grid computing environments pose unique security concerns that are not generally relevant for conventional data management systems. An event that appears as benign on a grid node, may actually be part of a larger incident hazardous to the grid. Since a node only sees the local footprint of an event, it cannot know the contribution of this event at a global scale. The focus of this work is on detecting such kinds of anomalous behaviors that we call global anomalies. In this paper, we propose two classes of global anomalies, and a model for detection of a class of global anomalies that we call global footprint anomalies. The main challenge here is to detect anomalous behavior, which looks normal locally at any individual grid node, but when observed globally, the anomalous behavior is apparent.