Architecture and Implementation of a Trust Model for Pervasive Applications

Collaborative effort to share resources is a significant feature of pervasive computing environments. To achieve secure service discovery and sharing, and to distinguish between malevolent and benevolent entities, trust models must be defined. It is critical to estimate a device\u27s initial trust value because of the transient nature of pervasive smart space; however, most of the prior research work on trust models for pervasive applications used the notion of constant initial trust assignment. In this paper, we design and implement a trust model called DIRT. We categorize services in different security levels and depending on the service requester\u27s context information, we calculate the initial trust value. Our trust value is assigned for each device and for each service. Our overall trust estimation for a service depends on the recommendations of the neighbouring devices, inference from other service-trust values for that device, and direct trust experience. We provide an extensive survey of related work, and we demonstrate the distinguishing features of our proposed model with respect to the existing models. We implement a healthcare-monitoring application and a location-based service prototype over DIRT. We also provide a performance analysis of the model with respect to some of its important characteristics tested in various scenarios

Semantic-based policy engineering for autonomic systems

This paper presents some important directions in the use of ontology-based semantics in achieving the vision of Autonomic Communications. We examine the requirements of Autonomic Communication with a focus on the demanding needs of ubiquitous computing environments, with an emphasis on the requirements shared with Autonomic Computing. We observe that ontologies provide a strong mechanism for addressing the heterogeneity in user task requirements, managed resources, services and context. We then present two complimentary approaches that exploit ontology-based knowledge in support of autonomic communications: service-oriented models for policy engineering and dynamic semantic queries using content-based networks. The paper concludes with a discussion of the major research challenges such approaches raise

Security in Pervasive Computing: Current Status and Open Issues

Million of wireless device users are ever on the move, becoming more dependent on their PDAs, smart phones, and other handheld devices. With the advancement of pervasive computing, new and unique capabilities are available to aid mobile societies. The wireless nature of these devices has fostered a new era of mobility. Thousands of pervasive devices are able to arbitrarily join and leave a network, creating a nomadic environment known as a pervasive ad hoc network. However, mobile devices have vulnerabilities, and some are proving to be challenging. Security in pervasive computing is the most critical challenge. Security is needed to ensure exact and accurate confidentiality, integrity, authentication, and access control, to name a few. Security for mobile devices, though still in its infancy, has drawn the attention of various researchers. As pervasive devices become incorporated in our day-to-day lives, security will increasingly becoming a common concern for all users - - though for most it will be an afterthought, like many other computing functions. The usability and expansion of pervasive computing applications depends greatly on the security and reliability provided by the applications. At this critical juncture, security research is growing. This paper examines the recent trends and forward thinking investigation in several fields of security, along with a brief history of previous accomplishments in the corresponding areas. Some open issues have been discussed for further investigation

Enabling e-Research in combustion research community

Abstract This paper proposes an application of the Collaborative e-Science Architecture (CeSA) to enable e-Research in combustion research community. A major problem of the community is that data required for constructing modelling might already exist but scattered and improperly evaluated. That makes the collection of data for constructing models difficult and time-consuming. The decentralised P2P collaborative environment of the CeSA is well suited to solve this distributed problem. It opens up access to scattered data and turns them to valuable resources. Other issues of the community addressed here are the needs for computational resources, storages and interoperability amongst different data formats can also be addressed by the use of Grid environment in the CeSA

When Things Matter: A Data-Centric View of the Internet of Things

With the recent advances in radio-frequency identification (RFID), low-cost wireless sensor devices, and Web technologies, the Internet of Things (IoT) approach has gained momentum in connecting everyday objects to the Internet and facilitating machine-to-human and machine-to-machine communication with the physical world. While IoT offers the capability to connect and integrate both digital and physical entities, enabling a whole new class of applications and services, several significant challenges need to be addressed before these applications and services can be fully realized. A fundamental challenge centers around managing IoT data, typically produced in dynamic and volatile environments, which is not only extremely large in scale and volume, but also noisy, and continuous. This article surveys the main techniques and state-of-the-art research efforts in IoT from data-centric perspectives, including data stream processing, data storage models, complex event processing, and searching in IoT. Open research issues for IoT data management are also discussed