An Automated Approach for Digital Forensic Analysis of Heterogeneous Big Data

Mohammed, Hussam J.; Clarke, Nathan; Li, Fudong

doi:10.15394/jdfsl.2016.1384

Cited by 31 publications

(23 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…TARZAN applications can utilize HDFS as suggested in a conceptual model of big data forensics by Zawoad and Hasan [26]. Also a framework for the forensic analysis of big heterogeneous data presented by Mohammed et al [18] can be realized using the TARZAN platform. Their framework has three layers that follow acquisition, examination, and analysis approach to extract metadata from acquired data sources and build a semantic web-based model for further analysis.…”

Section: Discussionmentioning

confidence: 99%

Big Data Security Analysis withTARZAN Platform

Rychl

Ryˇsav´

2018

JCSM

View full text Add to dashboard Cite

The TARZAN platform is an integrated platform for analysis of digital data from security incidents. The platform serves primarily as a middleware between data sources and data processing applications, however, it also provides several supporting services and a runtime environment for the applications. The supporting services, such as a data storage, a resource and application registry, a synchronization service, and a distributed computing platform, are utilized by the TARZAN applications for various securityoriented analyses on the integrated data ranging from an IT security incident detection to inference analyses of data from social networks or crypto-currency transactions. To cope with a large amount of distributed data, both streamed in real-time and stored, and for the need of a large scale distributed computing, the platform has been designed as a big data processing system ensuring reliable, scalable, and cost-effective solution. The platform is demonstrated on the case of a security analysis of network traffic.

show abstract

Section: Discussionmentioning

confidence: 99%

Big Data Security Analysis withTARZAN Platform

Rychl

Ryˇsav´

2018

JCSM

View full text Add to dashboard Cite

show abstract

“…TARZAN applications can utilize HDFS as suggested in a conceptual model of big data forensics by Zawoad and Hasan [24]. Also a framework for the forensic analysis of big heterogeneous data presented by Mohammed et al [25] can be realized using the TARZAN platform. Their framework has three layers that follow acquisition, examination, and analysis approach to extract metadata from acquired data sources and build a semantic web-based model for further analysis.…”

Section: Discussionmentioning

confidence: 99%

TARZAN: An Integrated Platform for Security Analysis

Rychlý

Ryšavý

2017

Proceedings of the 2017 Federated Conference on Computer Science and Information Systems

View full text Add to dashboard Cite

Abstract-In this paper, we present the TARZAN platform, an integrated platform for analysis of digital data from security incidents. The platform serves primarily as a middleware between data sources and data processing applications, however, it also provides several supporting services and a runtime environment for the applications. The supporting services, such as a data storage, a resource and application registry, a synchronization service, and a distributed computing platform, are utilized by the TARZAN applications for various security-oriented analyses on the integrated data ranging from an IT security incident detection to inference analyses of data from social networks or cryptocurrency transactions. To cope with a large amount of distributed data, both streamed in real-time and stored, and for the need of a large scale distributed computing, the platform has been designed as a big data processing system ensuring reliable, scalable, and cost-effective solution. The platform is demonstrated on the case of a security analysis of network traffic.

show abstract

“…In [13], the authors discussed an analysis of heterogeneous data sources in Big Data. The focus of the research was on three major problems namely data volume, data from heterogeneous sources, and understanding the relationship between different artifacts.…”

Section: A Semantic Ontologymentioning

confidence: 99%

Semantic Integration of Heterogeneous Databases of Same Domain Using Ontology

Asfand-e-yar

Ali

2020

IEEE Access

View full text Add to dashboard Cite

Heterogeneous database integration is the study of integrating data from multiple databases. Integrating the heterogeneous database of the same domain has three main challenges that make the heterogeneity problem difficult to solve. The three problems are Semantic, Syntactic and Structural Heterogeneity. Conventional heterogeneous database integration schemes, like De-duplication Techniques, Data Warehouse, and Information Retrieval (IR) Search technique lack the capability to solve the integration of databases completely. The only reason is they cannot deal with Semantic heterogeneity problems efficiently. The semantic Web ontology model is experimented and discussed in the article, which is based on the query execution model. The ontology modeling is divided into two phases, initially to translate the database rules according to ontology rules to find an abstract ontology model. Secondly, to extend the abstract ontology model according to the databases. The method facilitates to apply similarly SPQRAL queries to search the data in the databases. Therefore, the Jena API is used to retrieve semantically similar records. The experiment is based on the two heterogeneous Universities Library Databases. The results show the effectiveness and scalability of the methodology.

show abstract

An Automated Approach for Digital Forensic Analysis of Heterogeneous Big Data

Cited by 31 publications

References 16 publications

Big Data Security Analysis withTARZAN Platform

Big Data Security Analysis withTARZAN Platform

TARZAN: An Integrated Platform for Security Analysis

Semantic Integration of Heterogeneous Databases of Same Domain Using Ontology

Contact Info

Product

Resources

About