A framework for data security in cloud using collaborative intrusion detection scheme

Nagar, Upasana; Nanda, Priyadarsi; He, Xiangjian; Tan, zhiyuan (Thomas)

Abstract

Cloud computing offers an on demand, elastic, global network access to a shared pool of resources that can be configured on user demand. It offers a unique pay-as-you go feature which is based on measured usage and can be compared to other utility services like electricity and water in everyday life. The advantages of cloud computing are lucrative for well-established organizations looking to reduce infrastructure cost overheads. It is equally appealing for start-up organizations as they need not invest in infrastructure and take advantage of the cloud. Thus, cloud computing promises huge cost savings and minimal management efforts. However, the users are not quite confident in entrusting their data to the cloud due to security threats and risks perceived in the cloud domain. Issues involving privacy requirements for the cloud and best practices in the cloud are suggested in this paper. Although the cloud provider ensures security in the cloud yet the flow of data, storage location, data computing process and security breaches are not transparent to the cloud customer. This distrust and lack of control on data is a major hindrance for potential cloud customers in adopting the cloud models for their businesses. Hence there is a need to research this security gap. Further cloud systems are also susceptible to the existing network attacks such as the Distributed Denial of Service (DDoS) attacks. Intrusion Detection Systems (IDSs) are widely used to detect malicious activities and are classified as Host based or Network based. However existing solutions with IDSs involving DDoS and other non-detectable events may not be suitable in applying to the cloud due to distributed data storage and a major shift in Internet access mechanisms offered by cloud providers. Hence there is a strong need to analyze an appropriate IDS to counter DDoS attacks in the cloud. In this paper we propose a novel framework for Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s).

• Presentation Conference Type: Conference Paper (Published)
• Conference Name: Proceedings of the 10th International Conference on Security of Information and Networks - SIN '17
• Start Date: Oct 13, 2017
• End Date: Oct 15, 2017
• Acceptance Date: Aug 21, 2017
• Online Publication Date: Oct 13, 2017
• Publication Date: Oct 13, 2017
• Deposit Date: Nov 8, 2017
• Publicly Available Date: Nov 9, 2017
• Journal: SIN'17 Proceedings of 10th International Conference On Security Of Information And Networks
• Publisher: Association for Computing Machinery (ACM)
• Pages: 188-193
• Book Title: Proceedings of 10th International Conference On Security Of Information And Networks
• ISBN: 9781450353038
• DOI: https://doi.org/10.1145/3136825.3136905
• Keywords: Cloud Security, collaborative Intrusion detection, HIDS, NIDS, Alert Correlation
• Public URL: http://researchrepository.napier.ac.uk/Output/1008123
• Contract Date: Nov 8, 2017