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Publisher

The Association of Digital Forensics, Security and Law (ADFSL)

Abstract

Finding new methods to investigate criminal activities, behaviors, and responsibilities has always been a challenge for forensic research. Advances in big data, technology, and increased capabilities of smartphones has contributed to the demand for modern techniques of examination. Smartphones are ubiquitous, transformative, and have become a goldmine for forensics research. Given the right tools and research methods investigating agencies can help crack almost any illegal activity using smartphones. This paper focuses on conducting forensic analysis in exposing a terrorist or criminal network and introduces a new Big Forensic Data Framework model where different technologies of Hadoop and EnCase software are combined in an effort to promote more effective and efficient processing of the massive Big Forensic Data. The research propositions this model postulates could lead the investigating agencies to the head of the terrorist networks. Results indicate the Big Forensic Data Framework model is capable of processing Big Forensic Data.

References

Al Mutawa, N., Baggili, I., & Marrington, A. (2012). Forensic analysis of social networking applications on mobile devices. digital investigation, 9, S24-S33.

Alam, A., & Ahmed, J. (2014). Hadoop Architecture and its issues. Paper presented at the Computational Science and Computational Intelligence (CSCI), 2014 International Conference on.

Bashir, M. S., & Khan, M. (2013). Triage in Live Digital Forensic Analysis. International journal of Forensic Computer Science, 1, 35-44.

Beneish, M. D., Lee, C. M. C., & Tarpley, R. L. (2001). Contextual Fundamental Analysis through the Prediction of Extreme Returns. Review of Accounting Studies, 6, 165-189.

Borthakur, D. HDFS Architecture Guide. Retrieved from https://hadoop.apache.org/docs/r1.2.1/hdfs_design.html

Carrier, B. (2003). Defining digital forensic examination and analysis tools using abstraction layers. International Journal of Digital Evidence, 1(4), 1-12.

Carroll, O. L., Stephen K. Brannon, & Song, T. (2008). Computer Forensics. 56.

Catanese, S., Ferrara, E., & Fiumara, G. (2013). Forensic analysis of phone call networks. Social Network Analysis and Mining, 3(1), 15-33.

Curran, K., Robinson, A., Peacocke, S., & Cassidy, S. (2012). Mobile phone forensic analysis. Crime Prevention Technologies and Applications for Advancing Criminal Investigation, 250.

Davenport, T. (2014). Three big benefits of big data analytics. Retrieved from https://www.sas.com/en_ca/news/sascom/2014q3/Big-data-davenport.html

De Jong, K. A. (2006). Evolutionary computation : a unified approach. Cambridge, Mass.: MIT Press.

Encase. (2017). EnCase Forensic Software. Retrieved from https://www.guidancesoftware.com/encase-forensic

Ferrara, E., De Meo, P., Catanese, S., & Fiumara, G. (2014). Detecting criminal organizations in mobile phone networks. Expert Systems with Applications, 41(13), 5733-5750.

Garber, L. (2001). Encase: A case study in computer-forensic technology. IEEE Computer Magazine January.

Gerhardt, B., Griffin, K., & Klemann, R. (2012). Unlocking value in the fragmented world of big data analytics. Cisco Internet Business Solutions Group, June.

Grispos, G., Storer, T., & Glisson, W. B. (2011). A comparison of forensic evidence recovery techniques for a windows mobile smart phone. digital investigation, 8(1), 23-36.

Guarino, A. (2013). Digital forensics as a big data challenge ISSE 2013 Securing Electronic Business Processes (pp. 197-203): Springer.

Katal, A., Wazid, M., & Goudar, R. (2013). Big data: issues, challenges, tools and good practices. Paper presented at the Contemporary Computing (IC3), 2013 Sixth International Conference on.

Labrinidis, A., & Jagadish, H. V. (2012). Challenges and opportunities with big data. Proceedings of the VLDB Endowment, 5(12), 2032-2033.

Marchal, S., Jiang, X., State, R., & Engel, T. (2014). A Big Data Architecture for Large Scale Security Monitoring. Paper presented at the 2014 IEEE International Congress on Big Data.

MarcSmith. (2016, 9/27/2016). NodeXL: Network Overview, Discovery and Exploration for Excel. Retrieved from http://nodexl.codeplex.com/

Pascual, A., Marchini, K., & Miller, S. (2018). Al Pascual, Kyle Marchini, Sarah Miller. Retrieved from

Patil, H. K., & Seshadri, R. (2014). Big data security and privacy issues in healthcare. Paper presented at the 2014 IEEE international congress on big data.

Quick, D., & Choo, K.-K. R. (2016). Big forensic data reduction: digital forensic images and electronic evidence. Cluster Computing, 1-18.

Raghupathi, W., & Raghupathi, V. (2014). Big data analytics in healthcare: promise and potential. Health Information Science and Systems, 2(1), 1.

Richardson, S., Tuna, I., & Wysocki, P. (2010). Accountinganomalies and fundamental analysis: A review of recent research advances. Journal of Accounting and Economics, 50(2-3), 410-454.

Sagiroglu, S., & Sinanc, D. (2013). Big data: A review. Paper presented at the Collaboration Technologies and Systems (CTS), 2013 International Conference on.

Smith, M. A., Shneiderman, B., Milic-Frayling, N., Mendes Rodrigues, E., Barash, V., Dunne, C., . . . Gleave, E. (2009). Analyzing (social media) networks with NodeXL. Paper presented at the Proceedings of the fourth international conference on Communities and technologies.

Stirparo, P., & Kounelis, I. (2012). The mobileak project: Forensics methodology for mobile application privacy assessment. Paper presented at the Internet Technology And Secured Transactions, 2012 International Conference for.

Tahir, S., & Iqbal, W. (2015). Big Data??? An evolving concern for forensic investigators. Paper presented at the Anti-Cybercrime (ICACC), 2015 First International Conference on.

Tassone, C., Martini, B., Choo, K.-K. R., & Slay, J. (2013). Mobile device forensics: A snapshot. Trends and Issues in Crime and Criminal Justice(460), 1.

The Apache Software Foundation. (2004). What Is Apache Hadoop? Retrieved from http://hadoop.apache.org/

Zawoad, S., & Hasan, R. (2015). Digital Forensics in the Age of Big Data: Challenges, Approaches, and Opportunities. Paper presented at the High Performance Computing and Communications (HPCC), 2015 IEEE 7th International Symposium on Cyberspace Safety and Security (CSS), 2015 IEEE 12th International Conferen on Embedded Software and Systems (ICESS), 2015 IEEE 17th International Conference on.

DOI

https://doi.org/10.15394/jdfsl.2018.1419

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