Cloud Log Forensics: foundations, state of the art, and future directions

Khan, Suleman, Gani, Abdullah, Wahab, Ainuddin Wahid Abdul, Bagiwa, Mustapha Aminu, Shiraz, Muhammad, Khan, Samee U., Buyya, Rajkumar and Zomaya, Albert Y. (2016) Cloud Log Forensics: foundations, state of the art, and future directions. ACM Computing Surveys, 49 (1). ISSN 0360-0300

Full text not available from this repository.
Official URL: http://dx.doi.org/10.1145/2906149

Abstract

Cloud log forensics (CLF) mitigates the investigation process by identifying the malicious behavior of attackers through profound cloud log analysis. However, the accessibility attributes of cloud logs obstruct accomplishment of the goal to investigate cloud logs for various susceptibilities. Accessibility involves the issues of cloud log access, selection of proper cloud log file, cloud log data integrity, and trustworthiness of cloud logs. Therefore, forensic investigators of cloud log files are dependent on cloud service providers (CSPs) to get access of different cloud logs. Accessing cloud logs from outside the cloud without depending on the CSP is a challenging research area, whereas the increase in cloud attacks has increased the need for CLF to investigate the malicious activities of attackers. This paper reviews the state of the art of CLF and highlights different challenges and issues involved in investigating cloud log data. The logging mode, the importance of CLF, and cloud log-as-a-service are introduced. Moreover, case studies related to CLF are explained to highlight the practical implementation of cloud log investigation for analyzing malicious behaviors. The CLF security requirements, vulnerability points, and challenges are identified to tolerate different cloud log susceptibilities. We identify and introduce challenges and future directions to highlight open research areas of CLF for motivating investigators, academicians, and researchers to investigate them.

Item Type: Article
Uncontrolled Keywords: Cloud computing, cloud log forensics, big data, correlation of cloud logs, confidentiality, integrity, authenticity
Subjects: G400 Computer Science
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Paul Burns
Date Deposited: 22 Oct 2019 12:11
Last Modified: 22 Oct 2019 12:11
URI: http://nrl.northumbria.ac.uk/id/eprint/41199

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