From security to assurance in the cloud: a survey

The cloud computing paradigm has become a mainstream solution for the deployment of business processes and applications. In the public cloud vision, infrastructure, platform, and software services are provisioned to tenants (i.e., customers and service providers) on a pay-as-you-go basis. Cloud tenants can use cloud resources at lower prices, and higher performance and flexibility, than traditional on-premises resources, without having to care about infrastructure management. Still, cloud tenants remain concerned with the cloud's level of service and the nonfunctional properties their applications can count on. In the last few years, the research community has been focusing on the nonfunctional aspects of the cloud paradigm, among which cloud security stands out. Several approaches to security have been described and summarized in general surveys on cloud security techniques. The survey in this article focuses on the interface between cloud security and cloud security assurance. First, we provide an overview of the state of the art on cloud security. Then, we introduce the notion of cloud security assurance and analyze its growing impact on cloud security approaches. Finally, we present some recommendations for the development of next-generation cloud security and assurance solutions

Cloudarmor: Supporting Reputation-Based Trust Management for Cloud Services

Cloud services have become predominant in the current technological era. For the rich set of features provided by cloud services, consumers want to access the services while protecting their privacy. In this kind of environment, protection of cloud services will become a significant problem. So, research has started for a system, which lets the users access cloud services without losing the privacy of their data. Trust management and identity model makes sense in this case. The identity model maintains the authentication and authorization of the components involved in the system and trust-based model provides us with a dynamic way of identifying issues and attacks with the system and take appropriate actions. Further, a trust management-based system provides us with a new set of challenges such as reputation-based attacks, availability of components, and misleading trust feedbacks. Collusion attacks and Sybil attacks form a significant part of these challenges. This paper aims to solve the above problems in a trust management-based model by introducing a credibility model on top of a new trust management model, which addresses these use-cases, and also provides reliability and availability

XRay: Enhancing the Web's Transparency with Differential Correlation

Today's Web services - such as Google, Amazon, and Facebook - leverage user data for varied purposes, including personalizing recommendations, targeting advertisements, and adjusting prices. At present, users have little insight into how their data is being used. Hence, they cannot make informed choices about the services they choose. To increase transparency, we developed XRay, the first fine-grained, robust, and scalable personal data tracking system for the Web. XRay predicts which data in an arbitrary Web account (such as emails, searches, or viewed products) is being used to target which outputs (such as ads, recommended products, or prices). XRay's core functions are service agnostic and easy to instantiate for new services, and they can track data within and across services. To make predictions independent of the audited service, XRay relies on the following insight: by comparing outputs from different accounts with similar, but not identical, subsets of data, one can pinpoint targeting through correlation. We show both theoretically, and through experiments on Gmail, Amazon, and YouTube, that XRay achieves high precision and recall by correlating data from a surprisingly small number of extra accounts.Comment: Extended version of a paper presented at the 23rd USENIX Security Symposium (USENIX Security 14

Towards Achieving Data Security with the Cloud Computing Adoption Framework

Offering real-time data security for petabytes of data is important for Cloud Computing. A recent survey on cloud security states that the security of users’ data has the highest priority as well as concern. We believe this can only be able to achieve with an approach that is systematic, adoptable and well-structured. Therefore, this paper has developed a framework known as Cloud Computing Adoption Framework (CCAF) which has been customized for securing cloud data. This paper explains the overview, rationale and components in the CCAF to protect data security. CCAF is illustrated by the system design based on the requirements and the implementation demonstrated by the CCAF multi-layered security. Since our Data Center has 10 petabytes of data, there is a huge task to provide real-time protection and quarantine. We use Business Process Modeling Notation (BPMN) to simulate how data is in use. The use of BPMN simulation allows us to evaluate the chosen security performances before actual implementation. Results show that the time to take control of security breach can take between 50 and 125 hours. This means that additional security is required to ensure all data is well-protected in the crucial 125 hours. This paper has also demonstrated that CCAF multi-layered security can protect data in real-time and it has three layers of security: 1) firewall and access control; 2) identity management and intrusion prevention and 3) convergent encryption. To validate CCAF, this paper has undertaken two sets of ethical-hacking experiments involved with penetration testing with 10,000 trojans and viruses. The CCAF multi-layered security can block 9,919 viruses and trojans which can be destroyed in seconds and the remaining ones can be quarantined or isolated. The experiments show although the percentage of blocking can decrease for continuous injection of viruses and trojans, 97.43% of them can be quarantined. Our CCAF multi-layered security has an average of 20% better p- rformance than the single-layered approach which could only block 7,438 viruses and trojans. CCAF can be more effective when combined with BPMN simulation to evaluate security process and penetrating testing results

Semantic hierarchies for extracting, modeling, and connecting compliance requirements in information security control standards

Companies and government organizations are increasingly compelled, if not required by law, to ensure that their information systems will comply with various federal and industry regulatory standards, such as the NIST Special Publication on Security Controls for Federal Information Systems (NIST SP-800-53), or the Common Criteria (ISO 15408-2). Such organizations operate business or mission critical systems where a lack of or lapse in security protections translates to serious confidentiality, integrity, and availability risks that, if exploited, could result in information disclosure, loss of money, or, at worst, loss of life. To mitigate these risks and ensure that their information systems meet regulatory standards, organizations must be able to (a) contextualize regulatory documents in a way that extracts the relevant technical implications for their systems, (b) formally represent their systems and demonstrate that they meet the extracted requirements following an accreditation process, and (c) ensure that all third-party systems, which may exist outside of the information system enclave as web or cloud services also implement appropriate security measures consistent with organizational expectations. This paper introduces a step-wise process, based on semantic hierarchies, that systematically extracts relevant security requirements from control standards to build a certification baseline for organizations to use in conjunction with formal methods and service agreements for accreditation. The approach is demonstrated following a case study of all audit-related controls in the SP-800-53, ISO 15408-2, and related documents. Accuracy, applicability, consistency, and efficacy of the approach were evaluated using controlled qualitative and quantitative methods in two separate studies