Combating cyber attacks in cloud computing using machine learning techniques.

An extensive investigative survey on Cloud Computing with the main focus on gaps that is slowing down Cloud adoption as well as reviewing the threat remediation challenges. Some experimentally supported thoughts on novel approaches to address some of the widely discussed cyber-attack types using machine learning techniques. The thoughts have been constructed in such a way so that Cloud customers can detect the cyber-attacks in their VM without much help from Cloud service provide

Security Certification As a Service Over Cloud

Now a day’s Cloud computing is the best solution for IT industry as the infrastructure and application services offerings are enabled on subscription basis. Because of this most of the enterprise level companies like Amazon, IBM, Google, and Microsoft are providing useful offering to their customers as Cloud services. There are multiple criteria on the basis of which the customers may decide the appropriate cloud service provider as there are many cloud service providers are there in the IT medium, Customers don't have any framework on which they can trust, so the idea of designing a framework which can unable trust between end customer and cloud service provider along with raking them according to different attacks like DDoS, brute force, file integrity etc., the framework or solution will be known as Third Party Auditor (TPA). DOI: 10.17762/ijritcc2321-8169.15074

An elastic scaling method for cloud security

Cloud computing is being adopted in critical sectors such as transport, energy and finance. This makes cloud computing services critical in themselves. When cyber attacks and cyber disruptions happen, millions of users are affected. A cyber disruption in this context means a temporary or permanent loss of service, with impact on users of the cloud service who rely on its continuity. Intrusion detection and prevention methods are being developed to protect this sensitive information being stored, and the services being deployed. There needs to be an assurance that the confidentiality, integrity and availability of the data and resources are maintained. This paper presents a background to the critical infrastructure and cloud computing progression, and an overview to the cloud security conundrum. Analysis of existing intrusion detection methods is provided, in addition to our observation and proposed elastic scaling method for cloud security

Collaborative Intrusion Detection in Federated Cloud Environments

Moving services to the Cloud is a trend that has steadily gained popularity over recent years, with a constant increase in sophistication and complexity of such services. Today, critical infrastructure operators are considering moving their services and data to the Cloud. Infrastructure vendors will inevitably take advantage of the benefits Cloud Computing has to offer. As Cloud Computing grows in popularity, new models are deployed to exploit even further its full capacity, one of which is the deployment of Cloud federations. A Cloud federation is an association among different Cloud Service Providers (CSPs) with the goal of sharing resources and data. In providing a larger-scale and higher performance infrastructure, federation enables on-demand provisioning of complex services. In this paper we convey our contribution to this area by outlining our proposed methodology that develops a robust collaborative intrusion detection methodology in a federated Cloud environment. For collaborative intrusion detection we use the Dempster-Shafer theory of evidence to fuse the beliefs provided by the monitoring entities, taking the final decision regarding a possible attack. Protecting the federated Cloud against cyber attacks is a vital concern, due to the potential for significant economic consequences

Virtualization Technology: Cross-VM Cache Side Channel Attacks make it Vulnerable

Cloud computing provides an effective business model for the deployment of IT infrastructure, platform, and software services. Often, facilities are outsourced to cloud providers and this offers the service consumer virtualization technologies without the added cost burden of development. However, virtualization introduces serious threats to service delivery such as Denial of Service (DoS) attacks, Cross-VM Cache Side Channel attacks, Hypervisor Escape and Hyper-jacking. One of the most sophisticated forms of attack is the cross-VM cache side channel attack that exploits shared cache memory between VMs. A cache side channel attack results in side channel data leakage, such as cryptographic keys. Various techniques used by the attackers to launch cache side channel attack are presented, as is a critical analysis of countermeasures against cache side channel attacks

A MAS-Based Cloud Service Brokering System to Respond Security Needs of Cloud Customers

Cloud computing is becoming a key factor in computer science and an important technology for many organizations to deliver different types of services. The companies which provide services to customers are called as cloud service providers. The cloud users (CUs) increase and require secure, reliable and trustworthy cloud service providers (CSPs) from the market. So, it’s a challenge for a new customer to choose the highly secure provider. This paper presents a cloud service brokering system in order to analyze and rank the secured cloud service provider among the available providers list. This model uses an autonomous and flexible agent in multi-agent system (MASs) that have an intelligent behavior and suitable tools for helping the brokering system to assess the security risks for the group of cloud providers which make decision of the more secured provider and justify the business needs of users in terms of security and reliability