With the expectation of ever-increasing network of service providers due to Cloud and Web services explosion, security of user information is a major concern when it comes to the implementation of these services. This paper addresses the issue of identity management in a typical service providers' environment without the need for a trusted third party to federate the user identity for acquainted service providers. We leverage the establishment of trust between cross-domain service providers (SPs) to themselves rather than relying on a third party that brokers the trust between service providers. The hence formed network of SPs is then ready to facilitate a typical identity management scenario like a single-sign-on (SSO). We also propose a graph optimization algorithm that reduces the number of edges (connections between SPs) to reduce the overall communication in the network of SPs. We also report on our implementation and some performance study in terms of the communication overhead involved among SPs.

Efficient power management is vital for increasing the life of sensor nodes in wireless sensor networks (WSN). Thus, techniques such as data aggregation have been widely used in WSN to preserve nodes' energy. Despite its appealing and powerful features, data aggregation processes require a high level of security. Ensuring accuracy with aggregating data can become an issue even due to single bit errors. Hence, many encryption techniques have been proposed to secure the data aggregation process. However, once a wireless sensor is physically compromised, the keys stored on the sensor are exposed, thus rendering the cryptography useless. Moreover, most cryptographic approaches restrict the level of collaboration with other security measures -- especially trust management, where behavior observation is vital. In this paper, we propose a trust management approach on encrypted packets to deal with the faulty nodes in sensor networks. We designed a collaborative framework which incorporates the Order-Preserved Encryption Scheme [2] and Sigmoid Trust Management approaches. We then discuss how these two can coexist and comprehensively evaluate an integrated OPES-trust management scheme in the sensing environment using both the TOSSim simulator and an actual mote implementation. The results have shown that trust management and OPES cryptography does not consume more energy than radio transmission, yet provides a fairly accurate result.

Security risk assessment and mitigation are two vital processes that need to be executed to maintain a productive IT infrastructure. On one hand, models such as attack graphs and attack trees have been proposed to assess the cause-consequence relationships between various network states, while on the other hand, different decision problems have been explored to identify the minimum-cost hardening measures. However, these risk models do not help reason about the causal dependencies between network states. Further, the optimization formulations ignore the issue of resource availability while analyzing a risk model. In this paper, we propose a risk management framework using Bayesian networks that enable a system administrator to quantify the chances of network compromise at various levels. We show how to use this information to develop a security mitigation and management plan. In contrast to other similar models, this risk model lends itself to dynamic analysis during the deployed phase of the network. A multiobjective optimization platform provides the administrator with all trade-off information required to make decisions in a resource constrained environment.

Efficient power management is vital for increasing the life of wireless sensor networks (WSN). The main reason is that the radio transmission consumes energy approximately three times comparing to other operations. Thus, techniques such as data aggregation have been widely used in WSN to preserve energy. Despite its appealing and powerful features, data aggregation requires a high level of security as tampering with aggregating data can be suspected due to small bit errors. We propose a comprehensive trust management approach to deal with the potential dishonest and faulty motes in sensor networks. Unlike other trust management approaches, we take into account multiple properties in leveraging between positive trust and behavior uncertainty so as to yield the projection of trust which represents truster's confidence in the trustee node to have the capability to complete the task. We comprehensively evaluate and compare trust management schemes in the sensing environment using TOSSim simulator. The results have shown that the proposed scheme is memory efficient and provides fairly accurate results allowing sensors to appropriately adjust themselves and manage to carry out their missions during normal and extreme environment.

Researchers have previously looked into the problem of determining if a given set of security hardening measures can effectively make a networked system secure. Many of them also addressed the problem of minimizing the total cost of implementing these hardening measures, given costs for individual measures. However, system administrators are often faced with a more challenging problem since they have to work within a fixed budget which may be less than the minimum cost of system hardening. Their problem is how to select a subset of security hardening measures so as to be within the budget and yet minimize the residual damage to the system caused by not plugging all required security holes. In this work, we develop a systematic approach to solve this problem by formulating it as a multi-objective optimization problem on an attack tree model of the system and then use an evolutionary algorithm to solve it.