A study of integrated prefetching and caching strategies
Proceedings of the 1995 ACM SIGMETRICS joint international conference on Measurement and modeling of computer systems
Temporal sequence learning and data reduction for anomaly detection
CCS '98 Proceedings of the 5th ACM conference on Computer and communications security
Adaptive Intrusion Detection: A Data Mining Approach
Artificial Intelligence Review - Issues on the application of data mining
Discovery of Frequent Episodes in Event Sequences
Data Mining and Knowledge Discovery
PrefixSpan: Mining Sequential Patterns by Prefix-Projected Growth
Proceedings of the 17th International Conference on Data Engineering
File System Benchmarks, Then, Now, and Tomorrow
MSS '01 Proceedings of the Eighteenth IEEE Symposium on Mass Storage Systems and Technologies
Data Mining Methods for Detection of New Malicious Executables
SP '01 Proceedings of the 2001 IEEE Symposium on Security and Privacy
Learning to detect malicious executables in the wild
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Mining Sequential Patterns from Large Data Sets (The Kluwer International Series on Advances in Database Systems)
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
MAFIA: A Maximal Frequent Itemset Algorithm
IEEE Transactions on Knowledge and Data Engineering
C-Miner: Mining Block Correlations in Storage Systems
FAST '04 Proceedings of the 3rd USENIX Conference on File and Storage Technologies
Finding Maximal Frequent Itemsets over Online Data Streams Adaptively
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
Stardust: tracking activity in a distributed storage system
SIGMETRICS '06/Performance '06 Proceedings of the joint international conference on Measurement and modeling of computer systems
Dynamic instrumentation of production systems
ATEC '04 Proceedings of the annual conference on USENIX Annual Technical Conference
CP-Miner: a tool for finding copy-paste and related bugs in operating system code
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
Reducing file system latency using a predictive approach
USTC'94 Proceedings of the USENIX Summer 1994 Technical Conference on USENIX Summer 1994 Technical Conference - Volume 1
Measuring and characterizing system behavior using kernel-level event logging
ATEC '00 Proceedings of the annual conference on USENIX Annual Technical Conference
Mining uncertain data for frequent itemsets that satisfy aggregate constraints
Proceedings of the 2010 ACM Symposium on Applied Computing
Debugging embedded multimedia application traces through periodic pattern mining
Proceedings of the tenth ACM international conference on Embedded software
Data mining MPSoC simulation traces to identify concurrent memory access patterns
Proceedings of the Conference on Design, Automation and Test in Europe
Mining frequent patterns and association rules using similarities
Expert Systems with Applications: An International Journal
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Operating systems engineers have developed tracing tools that log details about process execution at the kernel level. These tools make it easier to understand the actual execution that takes place on real systems. Unfortunately, uncovering certain types of useful information in kernel trace data is nearly impossible through manual inspection of a trace log. To detect interesting interprocess communication patterns and other recurring runtime execution patterns in operating system trace logs, we employ data mining techniques, in particular, frequent pattern mining. We present a framework for mining kernel trace data, making use of frequent pattern mining in conjunction with special considerations for the temporal characteristics of kernel trace data. We report our findings using our framework to isolate processes responsible for systemic problems on a LINUX system and demonstrate our framework is versatile and efficient.