Title :
Research on Ontology-Based Cluster Analysis in Computer Forensics
Author_Institution :
Dept. of Comput., Shandong Police Coll., Jinan, China
Abstract :
The traditional clustering methods ignores the relationship between forensic evidence and connotation between the various forensic data, in order to improve the efficiency of computer forensics data analysis, get satisfactory clustering results, this paper proposes an ontology-based clustering analysis method, Studies on the forensic data preprocessing and concept extraction method, improve the calculation method of concept similarity, bring about a clustering method based on semantic similarity and ontology. Experiments show that the clustering method greatly reduce the amount of data to be processed on the basis of the clustering accuracy, achieve clustering analysis of forensics data on the conceptual level, help to analyze forensics data and find evidence more efficiently.
Keywords :
data analysis; digital forensics; ontologies (artificial intelligence); pattern clustering; computer forensics; concept extraction method; data analysis; forensic data preprocessing; ontology-based clustering analysis method; Algorithm design and analysis; Classification algorithms; Clustering algorithms; Computers; Forensics; Ontologies; Semantics; Clustering Analysis; Computer Forensics; Ontology; Similarity;
Conference_Titel :
Computational Intelligence and Design (ISCID), 2014 Seventh International Symposium on
Print_ISBN :
978-1-4799-7004-9
DOI :
10.1109/ISCID.2014.268