A Risk-aware Trust Based Secure Resource Discovery (RTSRD) Model for Pervasive Computing

While the number of devices connected together as the Internet of Things (IoT) is growing, the demand for an efficient and secure model of resource discovery in IoT is increasing. An efficient resource discovery model distributes the registration and discovery workload among many nodes and allow the resources to be discovered based on their attributes. In most cases this discovery ability should be restricted to a number of clients based on their attributes, otherwise, any client in the system can discover any registered resource. In a binary discovery policy, any client with the shared secret key can discover and decrypt the address data of a registered resource regardless of the attributes of the client. In this paper we propose Attred, a decentralized resource discovery model using the Region-based Distributed Hash Table (RDHT) that allows secure and location-aware discovery of the resources in IoT network. Using Attribute Based Encryption (ABE) and based on predefined discovery policies by the resources, Attred allows clients only by their inherent attributes, to discover the resources in the network. Attred distributes the workload of key generations and resource registration and reduces the risk of central authority management. In addition, some of the heavy computations in our proposed model can be securely distributed using secret sharing that allows a more efficient resource registration, without affecting the required security properties. The performance analysis results showed that the distributed computation can significantly reduce the computation cost while maintaining the functionality. The performance and security analysis results also showed that our model can efficiently provide the required security properties of discovery correctness, soundness, resource privacy and client privacy.

The requirement of semantic technology has been augmented day by day in IT related applications due to various features including interoperability. Effective development and organization of semantic knowledge are essential for maximum throughput in any application. We extend and develop two sub-domain computer resource ontologies and utilize them in a resource discovery process of a Grid computing environment to reduce the job rejection rate. Grid computing aggregates distributed computing resources to execute computationally complex jobs. The selection of resources in a Grid system involves finding and locating resources based on users' requirements. Identifying an appropriate resource selection mechanism for Grid jobs is a major concern because overall performance of a Grid depends on it and it also helps to schedule and allocate resources. We compute semantic similarity threshold values and employ both extended ontolgies in a decentralized resource discovery model of Grid Computing. The simulation is carried out using GridSim and PlanetSim to evaluate the effectiveness of a semantic resource discovery model. The results show improved success probability for complex jobs and reduce communication overheads compared to the non semantic resource discovery model.

Resource discovery is a crucial component in high-performance computing (HPC) systems. This paper presents a multi-agent model for resource discovery in distributed exascale systems. Agents are categorized based on resource types and behavior-specific characteristics. The model enables efficient identification and acquisition of memory, process, file, and IO resources. Through a comprehensive exploration, we highlight the potential of our approach in addressing resource discovery challenges in exascale computing systems, paving the way for optimized resource utilization and enhanced system performance.

Since the Internet of Things (IoT) will be entwined with everything we use in our daily life, the consequence of security flaws escalates. Smart objects will govern most of the home appliances and car engines yielding potential disaster scenarios. In this context, successful attacks could lead to chaos and scary scenarios (www.darkreading.com). Unprotected personal information may expose sensitive and embarrassing data to the public and attacks may threaten not only our computers and smart devices, but our intimacy and perhaps our lives too. Because persons and objects will be bonded with each other, user consent becomes critical. Therefore, thing, object, and user Identity will be the focus of future IoT security solutions, yielding a Trust, Security, and Privacy (TSP) paradigm, which may constitute the Achilles' heel of IoT. While security issues are quite straightforward, mainly from background knowledge, privacy issues are far more complex. Privacy constitutes a rather challenging task, even for the m...

In ubiquitous stub network, it is a critical challenge to realize resource discovery and share under disconnected network topology. In this paper, a cluster-based resource discovery mechanism is proposed with resource registration, distribution and routing model. Firstly, we use resource directory index nodes to assist in resource management. Secondly, we use inter-cluster mobile terminals to support resource routing. In addition, we take the nodes contact probability into account and establish the minimum expectation delay routing standard to opportunistically route between terminals. At last, the simulation result shows this mechanism is better applied to support disconnected ubiquitous resource discovery.

The way people use computing devices has been changed in some way by the relatively new pervasive computing paradigm. For example, a person can use a mobile device to obtain its location information at anytime and anywhere. There are several security issues concerning whether this information is reliable in a pervasive environment. For example, a malicious user may disable the localization system by broadcasting a forged location, and it may impersonate other users by eavesdropping their locations. In this paper, we address the verification of location information in a secure manner. We first present the design challenges for location verification, and then propose a two-layer framework VerPer for secure location verification in a pervasive computing environment. Real world GPS-based wireless sensor network experiments confirm the effectiveness of the proposed framework.KeywordsSensor NetworkWireless Sensor NetworkMobile UserPervasive ComputingMalicious UserThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

The fast development on microelectronics has promoted the increase on the computational power of hardware components. On the other hand, we are facing a significant improvement on energy consumption as well as the reduction of the physical size of such components. These improvements and the emergence of wireless networking technologies are enabling the development of small and powered mobile devices. Due to this scenario, the so-called pervasive computing paradigm, introduced by Mark Weiser in 1991 (Weiser, 1991) is becoming a reality. Such a paradigm envisions a world where environments are inhabited by computing devices, all of them seamlessly integrated into peoples’ lives, and effectively helping to carry on their daily tasks. Among others, one major characteristic of Weiser’s vision is that each device in an environment becomes a potential client or provider of resources. Not surprisingly, pervasive computing environments are becoming dynamic repositories of computational resources, all of them available to mobile users from the palm of their hands. However, devices can unpredictably join and leave such environments. Thus, resources can be dynamically made available or unavailable. Such a scenario has a great impact on the way that resources are found and used. In the case of static environments, such as the Web, it is reasonable to look up and access resources, such as Web pages, knowing the address of their providers beforehand. On the other hand, for dynamic environments, such as the pervasive computing ones, this is not a reasonable approach. This is due to the fact that one cannot guarantee that the provider of a resource will be available at any moment, because it may have left the environment or simply turned off. A better approach would be to discover these resources based on their descriptions, or any other feature that does not require the client to know the specific address of their providers. To this end, some of the current pervasive computing solutions, like Wings (Loureiro, Bublitz, Oliveira, Barbosa, Perkusich, Almeida, & Ferreira, 2006), Green (Sivaharan, Blair, & Coulson, 2005), RUNES (Costa, Coulson, Mascolo, Picco, & Zachariadis, 2005), and Scooby (Robinson, Wakeman, & Owen, 2004), are making use of a novel approach from the branch of distributed applications, the service-oriented computing paradigm (Papazoglou, 2003; Huhns & Singh, 2005). This is due to the fact that such a paradigm provides a crucial element for pervasive computing systems, the ability for dynamically binding to remote resources (Bellur & Narenda, 2005), which enables mobile devices to find needed services on demand. However, pervasive environments may be structured in different ways. They can range from wired networks to completely wireless ones, where communication among the devices is performed in an ad hoc way. Such a characteristic indicates that the way services are provisioned in a pervasive computing environment should fit in its organization, in order to enhance the access to the services available. Considering the above discussion, in this article we provide a review on service provision and its applicability in pervasive computing. More precisely, we will list the existing service provision approaches and discuss the characteristics and problems associated with each one, as well as their usage in pervasive computing environments. We start by providing introductory concepts of service-oriented and pervasive computing, respectively in the service-oriented computing and pervasive computing sections. Next, we present the service provision techniques available and how they can be applied for pervasive computing environments. The main current solutions within this scope will be introduced in the service oriented technologies section. Some of the future trends associated with research for service provision in pervasive computing environments will be presented in the future research trends section. Finally, in the conclusions sect

Efficient resource discovery is a challenge aspect in P2P applications. The topological properties of P2P overlay networks are one of the important factors that dominate the performance of resource discovery. In this paper, we present an efficient P2P network model for resource discovery. Firstly, location of the underlying physical network is taken into account during the constructions of P2P networks aiming to alleviate the topoloty mismatch problem between the P2P overlay nerwork and the phisical nerwork. Furthermore, the nodes with similar resource are clustered together which can increase the chances of finding matching resources quickly. Comparing the performance of this model with other overlay networks, the results show the model of our claims can significantly shorten the latency of the searching process and reduce the searching overhead.

Smart environments are becoming ubiquitous despite many potential security and privacy issues. But, do people understand what consequences could arise from using smart environments? To answer this research question, we conducted a survey with 575 participants from three different countries (Germany, Spain, Romania) considering smart home and health environments. Less than half of all participants mentioned at least one security and privacy issue, with significantly more German participants mentioning issues than the Spanish ones and the Spanish participants in turn mentioning significantly more security and privacy issues than the Romanian participants. Using open coding, we find that among the 275 participants mentioning security and privacy issues, 111 only expressed abstract concerns such as “security issues” and only 34 mentioned concrete harms such as “Burglaries (physical and privacy)”, caused by security and privacy violations. The remaining 130 participants who mentioned security and privacy issues named only threats (i.e. their responses were more concrete than just abstract concerns but they did not mention concrete harming scenarios).

Smart cities have brought significant improvements in quality of life and services to citizens and urban environments. They are fully enabled to control the physical objects in real time and provide intelligent information to citizens in terms of transport, healthcare, smart buildings, public safety, smart parking, and traffic system as well as smart agriculture, and so on. The applications of smart cities are able to collect sensitive information. However, various security and privacy issues may arise at different levels of the architecture. Therefore, it is important to be aware of these security and privacy issues while designing and implementing the applications. This chapter highlights main applications of smart cities and addresses the major privacy and security issues in the architecture of the smart cities’ applications. It also reviews some of the current solutions regarding the security and privacy of information-centric smart cities’ applications and presents future research challenges that still need to be considered for performance improvement.

Shadow attacks on users’ anonymity in pervasive computing environments

Grid computing is the next generation of distributed system. Its goal is to create a huge, independent and powerful virtual machine, and it has been created by gathering different machines with the aim of sharing them. Resource discovery is the most fundamental phase of resource management which has been considered in our work. Considering the advantages and disadvantages of P2P and grid and their architectural similarity; using some of P2P approaches as a solution in Grid can improve the performance of Grid. Semantic technology and fuzzy logic are the two intelligent approaches, which recently apply on P2P network and Grid environment. In P2P networks, nodes are grouping based on their interests. Moreover semantic can be very useful for grouping nodes. This paper follows the identification of resource discovery in grid environment with the help of semantic and fuzzy theory and seeking to present a resource discovery algorithm with respect to exiting obstacles. The proposed approach is assessed in simulated grid environment and the results are compared with other approaches in same conditions. The goals of our approach are to obtain precious matching by clustering nodes which have services semantically related, improving search expressiveness by considering the distances between nodes (delay) in clustering phase, and decreasing response time and processing time by considering the nodes computational capabilities and free space of each node. We evaluate the performance of our approach with some distributed semantic based grid resource discovery models. The results of the experiments show the efficiency of the proposed approach in term of scalability, precision, search expressiveness and response time.

The paper presents a new security solution in ubiquitous computing, which is a new and hot research point for computer scientists. Ubiquitous computing environments with their interconnected devices and services promise seamless integration of digital infrastructure into our daily lives. While the focus of current research is on how to connect new devices and build useful applications to improve functionality, the security and privacy issues in such environments have not been deployed widely to justify the evidence of threats, risk and vulnerability in real situations. Existing policies and mechanisms may not provide adequate guarantees to deal with new exposures and vulnerabilities introduced by the ubiquitous computing paradigm. In this paper we explore the challenges for building security and privacy into ubiquitous computing, describe our prototype implementation based on neural cryptography, and propose some directions for future work in the end.

Identification of individuals is ubiquitous with increasing reliance by financial and governmental organizations on reliable and robust personal recognition systems to determine and confirm the identity and policy constraints for specific individuals in 'real-time' when reacting to service requests. The traditional identification approaches to user validation are not robust and deficiencies in such approaches are becoming increasingly apparent in the current information-oriented society. With developments in research into the human brain, biometric methods based on brain wave signals have received increased attention as an effective approach to user validation as an individuals' brain wave signals cannot be duplicated, discarded or stolen. Targeted at pervasive systems and the identified deficiencies in traditional approaches to user identification and validation, an electroencephalogram (EEG)-based biometric system for use in pervasive environments is proposed in this paper. A significant problem of EEG-based biometrics in pervasive environment is the requirement of real-time and convenience. In our study, only one active electrode with a portable EEG collection device was used and no other instructions to users for convenience; in addition, the signal analysis methods we used were efficient to achieve less time consumption. In our prototype system, 11 subjects were identified with recognition accuracy in the range 66.02% to 100%; the recognition accuracy increased with increases in the EEG sample time; and the computational time of signal analysis was about 0.5s. The low computational time of EEG data analysis validates this model when implemented in pervasive environments. For differing applications we can define a suitable balance point to optimize the conflicting demands of data collection time length and recognition accuracy.

In this paper we explore the potential for securing a distributed Arabic Optical Character Recognition (OCR) system via cloud computing technology in a pervasive and mobile environment. The goal of the system is to achieve full accuracy, high speed and security when taking into account large vocabularies and amounts of documents. This issue has been resolved by integrating the recognition process and the security issue with multiprocessing and distributed computing technologies.