Biblio

Computer security has become an increasingly important hot topic in computer and communication industry, since it is important to support critical business process and to protect personal and sensitive information. Computer security is to keep security attributes (confidentiality, integrity and availability) of computer systems, which face the threats such as deny-of-service (DoS), virus and intrusion. To ensure high computer security, the intrusion tolerance technique based on fault-tolerant scheme has been widely applied. This paper presents the quantitative performance evaluation of a virtual machine (VM) based intrusion tolerant system. Concretely, two security measures are derived; MTTSF (mean time to security failure) and the effective traffic intensity. The mathematical analysis is achieved by using Laplace-Stieltjes transforms according to the analysis of M/G/1 queueing system.

Computer systems face the threat of deliberate security intrusions due to malicious attacks that exploit security holes or vulnerabilities. In practice, these security holes or vulnerabilities still remain in the system and applications even if developers carefully execute system testing. Thus it is necessary and important to develop the mechanism to prevent and/or tolerate security intrusions. As a result, the computer systems are often evaluated with confidentiality, integrity and availability (CIA) criteria from the viewpoint of security, and security is treated as a QoS (Quality of Service) attribute at par with other QoS attributes such as capacity and performance. In this paper, we present the method for quantifying a security attribute called mean time to security failure (MTTSF) of a VM-based intrusion tolerant system based on queueing theory.

Cloud computing brings in a lot of advantages for enterprise IT infrastructure; virtualization technology, which is the backbone of cloud, provides easy consolidation of resources, reduction of cost, space and management efforts. However, security of critical and private data is a major concern which still keeps back a lot of customers from switching over from their traditional in-house IT infrastructure to a cloud service. Existence of techniques to physically locate a virtual machine in the cloud, proliferation of software vulnerability exploits and cross-channel attacks in-between virtual machines, all of these together increases the risk of business data leaks and privacy losses. This work proposes a framework to mitigate such risks and engineer customer trust towards enterprise cloud computing. Everyday new vulnerabilities are being discovered even in well-engineered software products and the hacking techniques are getting sophisticated over time. In this scenario, absolute guarantee of security in enterprise wide information processing system seems a remote possibility; software systems in the cloud are vulnerable to security attacks. Practical solution for the security problems lies in well-engineered attack mitigation plan. At the positive side, cloud computing has a collective infrastructure which can be effectively used to mitigate the attacks if an appropriate defense framework is in place. We propose such an attack mitigation framework for the cloud. Software vulnerabilities in the cloud have different severities and different impacts on the security parameters (confidentiality, integrity, and availability). By using Markov model, we continuously monitor and quantify the risk of compromise in different security parameters (e.g.: change in the potential to compromise the data confidentiality). Whenever, there is a significant change in risk, our framework would facilitate the tenants to calculate the Mean Time to Security Failure (MTTSF) cloud and allow them to adopt a dynamic mitigation plan. This framework is an add-on security layer in the cloud resource manager and it could improve the customer trust on enterprise cloud solutions.