36,079 research outputs found

    Cryptographic Approaches To Security and Privacy Issues In Pervasive Computing

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    Technological innovation has enabled tiny devices to participate in pervasive com- puting. Such devices are particularly vulnerable to security and privacy threats, because of their limited computing resources and relatively weak physical security. We investigate possible cryptographic solutions to security and privacy problems arising in two kinds of emerging pervasive computing networks: Personal Area Net- works (PANs) and the EPCglobal Network. A number of key management schemes have been proposed for use in PANs, but these schemes only support key management within a PAN. However, as people are increasingly equipped with multiple wireless devices, PANs are likely to be intercon- nected to share information or services. We introduce a term, iPANs, to name such interconnected PANs. We define system models and design goals for key manage- ment in iPANs, and propose a novel security initialisation scheme for use in iPANs. The proposed scheme achieves desirable security and efficiency properties by making use of the unique characteristics of PANs. The EPCglobal Network is designed to give efficiency and cost savings in and beyond the supply chain using Radio Frequency Identification (RFID) technology; however, privacy threats affecting such networks are particularly serious. We construct a formal privacy model for RFID systems accurately reflecting adversarial threats and power. We then give brief privacy analysis for the existing privacy-enhanced RFID schemes which have received wide attention in the literature. We then construct a secure refresh-based RFID system based on re-encryption techniques, and prove its privacy using the defined privacy model. Finally, we show that the proposed scheme can greatly enhance the security and privacy of EPC tags, making the maximum use of given tag functionalities as specified in the standards

    A policy language definition for provenance in pervasive computing

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    Recent advances in computing technology have led to the paradigm of pervasive computing, which provides a means of simplifying daily life by integrating information processing into the everyday physical world. Pervasive computing draws its power from knowing the surroundings and creates an environment which combines computing and communication capabilities. Sensors that provide high-resolution spatial and instant measurement are most commonly used for forecasting, monitoring and real-time environmental modelling. Sensor data generated by a sensor network depends on several influences, such as the configuration and location of the sensors or the processing performed on the raw measurements. Storing sufficient metadata that gives meaning to the recorded observation is important in order to draw accurate conclusions or to enhance the reliability of the result dataset that uses this automatically collected data. This kind of metadata is called provenance data, as the origin of the data and the process by which it arrived from its origin are recorded. Provenance is still an exploratory field in pervasive computing and many open research questions are yet to emerge. The context information and the different characteristics of the pervasive environment call for different approaches to a provenance support system. This work implements a policy language definition that specifies the collecting model for provenance management systems and addresses the challenges that arise with stream data and sensor environments. The structure graph of the proposed model is mapped to the Open Provenance Model in order to facilitating the sharing of provenance data and interoperability with other systems. As provenance security has been recognized as one of the most important components in any provenance system, an access control language has been developed that is tailored to support the special requirements of provenance: fine-grained polices, privacy policies and preferences. Experimental evaluation findings show a reasonable overhead for provenance collecting and a reasonable time for provenance query performance, while a numerical analysis was used to evaluate the storage overhead

    In Things We Trust? Towards trustability in the Internet of Things

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    This essay discusses the main privacy, security and trustability issues with the Internet of Things

    Mutual Authentication Protocols for RFID Systems

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    Radio-Frequency Identification Devices (RFID) is emerging as a pervasive computing technology with numerous applications. Current low-cost RFID tags are highly resource-constrained and cannot support complex security mechanisms. Hence they have potential risks and may violate the privacy of their bearers. The challenge in providing security for low-cost RFID tags lies in that they are computationally weak devices, unable to perform even basic symmetric-key cryptographic operations as proposed in currently available protocols. In this thesis we have analyzed the security issues and requirements for a RFID system. We have proposed a suite of lightweight mutual authentication protocols for low-cost RFID tags which offer an adequate level of security at much reduced cost. We also compare our proposed protocols with those proposed by others. Furthermore we apply our proposed protocol to secure a supply chain management system.Computer Science Departmen

    Design and Implementation of S-MARKS: A Secure Middleware for Pervasive Computing Applications

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    As portable devices have become a part of our everyday life, more people are unknowingly participating in a pervasive computing environment. People engage with not a single device for a specific purpose but many devices interacting with each other in the course of ordinary activity. With such prevalence of pervasive technology, the interaction between portable devices needs to be continuous and imperceptible to device users. Pervasive computing requires a small, scalable and robust network which relies heavily on the middleware to resolve communication and security issues. In this paper, we present the design and implementation of S-MARKS which incorporates device validation, resource discovery and a privacy module

    Privacy, security, and trust issues in smart environments

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    Recent advances in networking, handheld computing and sensor technologies have driven forward research towards the realisation of Mark Weiser's dream of calm and ubiquitous computing (variously called pervasive computing, ambient computing, active spaces, the disappearing computer or context-aware computing). In turn, this has led to the emergence of smart environments as one significant facet of research in this domain. A smart environment, or space, is a region of the real world that is extensively equipped with sensors, actuators and computing components [1]. In effect the smart space becomes a part of a larger information system: with all actions within the space potentially affecting the underlying computer applications, which may themselves affect the space through the actuators. Such smart environments have tremendous potential within many application areas to improve the utility of a space. Consider the potential offered by a smart environment that prolongs the time an elderly or infirm person can live an independent life or the potential offered by a smart environment that supports vicarious learning

    Localization to Enhance Security and Services in Wi-Fi Networks under Privacy Constraints

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    Developments of seamless mobile services are faced with two broad challenges, systems security and user privacy - access to wireless systems is highly insecure due to the lack of physical boundaries and, secondly, location based services (LBS) could be used to extract highly sensitive user information. In this paper, we describe our work on developing systems which exploit location information to enhance security and services under privacy constraints. We describe two complimentary methods which we have developed to track node location information within production University Campus Networks comprising of large numbers of users. The location data is used to enhance security and services. Specifically, we describe a method for creating geographic firewalls which allows us to restrict and enhance services to individual users within a specific containment area regardless of physical association. We also report our work on LBS development to provide visualization of spatio-temporal node distribution under privacy considerations
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