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General Information
    • ISSN: 2010-3700 (Online)
    • Abbreviated Title: Int. J. Mach. Learn. Comput.
    • Frequency: Bimonthly
    • DOI: 10.18178/IJMLC
    • Editor-in-Chief: Dr. Lin Huang
    • Executive Editor:  Ms. Cherry L. Chen
    • Abstracing/Indexing: Scopus (since 2017), EI (INSPEC, IET), Google Scholar, Crossref, ProQuest, Electronic Journals Library.
    • E-mail: ijmlc@ejournal.net
Dr. Lin Huang
Metropolitan State University of Denver, USA
It's my honor to take on the position of editor in chief of IJMLC. We encourage authors to submit papers concerning any branch of machine learning and computing.

IJMLC 2015 Vol.5(6): 467-470 ISSN: 2010-3700
DOI: 10.18178/ijmlc.2015.5.6.554

Forensic Analysis to China’s Cloud Storage Services

Chen Long and Zhang Qing
Abstract—Nowadays, cloud storage is becoming increasingly popular among individuals and businesses. At the same time, there are an increasing number of illegal cases about preserving illegal information or stealing the company's confidential data through cloud storage service. Therefore, a study on digital forensic investigation of cloud storage services is necessary. Using two china’s cloud storage services(360 and Baidu cloud storage service) as case studies, this paper discusses the types of terrestrial artifacts that are likely to remain on a client’s machine and analyses the law of terrestrial artifacts after accessing to the cloud storage. At last the paper proposes a method to investigate and analyze the artifacts for reconstructing the event of user’s activities.

Index Terms—Cloud computing, cloud storage, digital forensic, user’s activities.

The authors are with the Institute of Computer Forensics, Chongqing University of Posts and Telecommunications, Chongqing 400065, China (e-mail: chenlong@cqupt.edu.cn, zhangqing7441@163.com).


Cite: Chen Long and Zhang Qing, "Forensic Analysis to China’s Cloud Storage Services," International Journal of Machine Learning and Computing vol.5, no. 6, pp. 467-470, 2015.

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