NDLI: Inferring User Actions from Provenance Logs

Content Provider	IEEE Xplore Digital Library
Author	Xin Li Joshi, C. Tan, A.Y.S. Ko, R.K.L.
Copyright Year	2015
Description	Author affiliation: Dept. of Comput. Sci., Univ. of Waikato Hamilton, Hamilton, New Zealand (Tan, A.Y.S.; Ko, R.K.L.) \|\| Dept. of Stat., Univ. of Waikato Hamilton, Hamilton, New Zealand (Xin Li; Joshi, C.)
Abstract	Progger, a kernel-spaced cloud data provenance logger which provides fine-grained data activity records, was recently developed to empower cloud stakeholders to trace data life cycles within and across clouds. Progger logs have the potential to allow analysts to infer user actions and create a data-centric behaviour history in a cloud computing environment. However, the Progger logs are complex and noisy and therefore, currently this potential can not be met. This paper proposes a statistical approach to efficiently infer the user actions from the Progger logs. Inferring logs which capture activities at kernel-level granularity is not a straightforward endeavour. This paper overcomes this challenge through an approach which shows a high level of accuracy. The key aspects of this approach are identifying the data preprocessing steps and attribute selection. We then use four standard classification models and identify the model which provides the most accurate inference on user actions. To our best knowledge, this is the first work of its kind. We also discuss a number of possible extensions to this work. Possible future applications include the ability to predict an anomalous security activity before it occurs.
Starting Page	742
Ending Page	749
File Size	492486
Page Count	8
File Format	PDF
e-ISBN	9781467379526
DOI	10.1109/Trustcom.2015.442
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-08-20
Publisher Place	Finland
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Cloud computing User Actions Data security Data preprocessing Data-centric Logger Data Provenance Cloud Computing Provenance Mining Training data Log Mining Data models Data Security Kernel Progger Testing
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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