Cloud Forensic Frameworks based on Machine Learning Techniques
Nandita Goyal1, Kanika Gupta2, Munesh Chandra Trivedi3
1NanditaGoyal, ABES Engineering College, Ghaziabad, Uttar Pradesh, India.
2Kanika Gupta, ABES Engineering College, Ghaziabad, Uttar Pradesh, India.
3Munesh Chandra, Chandra Trivedi Rajkiya Engineering College, Azamgarh, Uttar Pradesh, India.
Manuscript received on 09 June 2019 | Revised Manuscript received on 14 June 2019 | Manuscript Published on 08 July 2019 | PP: 569-573 | Volume-8 Issue-8S3 June 2019 | Retrieval Number: H11290688S319/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Cloud computing is considered to be one of the most significant and influential topics in the field of computing sciences. With time, cloud computing has paved its way in almost every aspect of human life. With the significant hike in number of users and service provider in the cloud environment, attackers are also increasing malicious activities in this area. Due to criticality in the area of the cloud computing, it is necessary that cloud environment should be safe . The concept of Cloud forensics has been introduced to establish a well-defined forensic capability in cloud environment. Although a lot of work has been carried out in the area of cloud forensic challenges and solutions, but the research on its frameworks and methodologies is still to be explored. The major challenge lies in providing a framework for analysis of massive amounts of forensic data in limited period. As proposed by many researchers, one of the best solutions for such analysis is the use of machine learning methods. This paper provides the study on the methodological aspect of cloud forensic analysis using various machine learning approaches. It gives a critical review of existing cloud forensic methodologies making use of machine learning for investigation of security related incidents in cloud. Furthermore, it provides a comprehensive study and comparison of existing frameworks using machine learning for digital and cloud forensic analysis, their drawbacks and scope for novel future research directions in thisarea.
Keywords: Cloud forensics, machine learning, cloud forensic methodologies, review, machine learning methodologies, cloud forensic solutions.
Scope of the Article: Machine Learning