Pervasive Computing Environments Research Articles

Secure and Private Service Discovery in Pervasive Computing Environments

With the convergence of embedded computers and wireless communication, pervasive computing has become the inevitable future of computing. Every year, billions of computing devices are built. They are ubiquitously deployed and are gracefully integrated with people and their environments. Service discovery is an essential step for the devices to properly discover, configure, and communicate with each other. Authentication for pervasive service discovery is difficult. In this chapter, we introduce a user-centric service discovery model, called PrudentExposure, which automates authentication processes. It encodes hundreds of authentication messages in a novel code word form. Perhaps the most serious challenge for pervasive service discovery is the integration of computing devices with people. A critical privacy challenge can be expressed as a “chicken-andegg problem”: both users and service providers want the other parties to expose sensitive information first. We discuss how a progressive and probabilistic model can protect both users’ and service providers’ privacy.

On the consistency of distributed proofs with hidden subtrees

Previous work has shown that distributed authorization systems that fail to sample a consistent snapshot of the underlying system during policy evaluation are vulnerable to a number of attacks. Unfortuantely, the consistency enforcement solutions presented in previous work were designed for systems in which only CA-certified evidence is used during the decision-making process, all of which is available to the decision-making node at runtime. In this article, we generalize previous results and present light-weight mechanisms through which consistency constraints can be enforced in proof systems in which the full details of a proof may be unavailable to the querier due to information release policies, and the existence of certificate authorities for certifying evidence is unlikely; these types of distributed proof systems are likely candidates for use in pervasive computing and sensor network environments. We present modifications to one such distributed proof system that enable three types of consistency constraints to be enforced while still respecting the same confidentiality and integrity policies as the original proof system. We then discuss how these techniques can be adapted and applied to other, less restrictive, distributed proof systems. Further, we detail a performance analysis that illustrates the modest overheads of our consistency enforcement schemes.

A Solution of Data Inconsistencies in Data Integration — Designed for Pervasive Computing Environment

New challenges including how to share information on heterogeneous devices appear in data-intensive pervasive computing environments. Data integration is a practical approach to these applications. Dealing with inconsistencies is one of the important problems in data integration. In this paper we motivate the problem of data inconsistency solution for data integration in pervasive environments. We define data quality criteria and expense quality criteria for data sources to solve data inconsistency. In our solution, firstly, data sources needing high expense to obtain data from them are discarded by using expense quality criteria and utility function. Since it is difficult to obtain the actual quality of data sources in pervasive computing environment, we introduce fuzzy multi-attribute group decision making approach to selecting the appropriate data sources. The experimental results show that our solution has ideal effectiveness.

Trust Managementfor Pervasive Computing Environments

Trust Managementfor Pervasive Computing Environments

Enabling Personal Privacy for Pervasive Computing Environments

Protection of personal data in the Internet is already a challenge today. Users have to actively look up privacy policies of websites and decide whether they can live with the terms of use. Once discovered, they are forced to make a 'take or leave' decision. In future living and working environments, where sensors and context-aware services are pervasive, this becomes an even greater challenge and annoyance. The environment is much more personalized and users cannot just 'leave'. They require measures to prevent, avoid and detect misuse of sensitive data, as well as to be able to negotiate the purpose of use of data. We present a novel model of privacy protection, complementing the notion of enterprise privacy with the incorporation of personal privacy towards a holistic privacy management system. Our approach allows non-expert users not only to negotiate the desired level of privacy in a rather automated and simple way, but also to track and monitor the whole life-cycle of data.

Secure and Private Service Discovery in Pervasive Computing Environments

In pervasive computing environments, service discovery is an essential step for computing devices to properly discover, configure, and communicate with each other. We introduce a user-centric service discovery model, called PrudentExposure, which automates authentication processes. Traditional authentication approaches requires much users’ involvement. PrudentExposure encodes hundreds of authentication messages in a novel code word form. Moreover, we discuss how a progressive and probabilistic model can protect both users’ and service providers’ privacy. Perhaps the most serious challenge for pervasive service discovery is the integration of computing devices with people. In a challenging case, both users and service providers want the other parties to expose sensitive information first. Our model protects both users and service providers.

An Internet Framework for Pervasive Sensor Computing

The rapid increase of sensor networks has brought a revolution in pervasive computing. However, data from these fragmented and heterogeneous sensor networks are easily shared. Existing sensor computing environments are based on the traditional database approach, in which sensors are tightly coupled with specific applications. Such static configurations are effective only in situations where all the participating sources are precisely known to the application developers, and users are aware of the applications. A pervasive computing environment raises more challenges, due to ad hoc user requests and the vast number of available sources, making static integration less effective. This paper presents an Internet framework called iSEE (Internet Sensor Exploration Environment) which provides a more complete environment for pervasive sensor computing. iSEE enables advertising and sharing of sensors and applications on the Internet with unsolicited users much like how Web pages are publicly shared today.

Data Security and Privacy Protection in Pervasive Computing Environments

Data Security and Privacy Protection in Pervasive Computing Environments

Security Analysis of the Full-Round CHESS-64 Cipher Suitable for Pervasive Computing Environments

Security Analysis of the Full-Round CHESS-64 Cipher Suitable for Pervasive Computing Environments

Agent‐based task representation and processing in pervasive computing environment

AbstractIt is an effective approach to adopt software agent in pervasive computing (Per‐Com) environment. Meanwhile, task execution is the key problem which is affected directly by task representation method in Per‐Com environment. The task of agent in Per‐Com environment is dynamic and changeful, so the task representation should be flexible and agent‐oriented. However, most of the existing task representation methods cannot present task relationship clearly and lack unified format, which leads to a drawback that the corresponding task processing efficiency is not satisfying. In this paper, firstly, an agent‐based Per‐Com architecture is presented in which the agent is endowed with certain role. Secondly, through analyzing task relationship, an agent role based task relationship tree (TRT) model and an XML‐based agent task representation method are proposed. Thirdly, based on TRT, an agent task decomposing and online multi‐agent scheduling algorithm are presented to solve time‐optimal problems. Meanwhile, a load balancing strategy based on probability is proposed to increase agent utilization. Finally, a prototype of an application on traffic monitoring is presented. The results of evaluation indicate that the architecture is feasible and the simulation tests of time performance indicate that the proposed TRT‐based task processing methods have a better performance than others. Copyright © 2009 John Wiley & Sons, Ltd.

Context and Adaptivity in Pervasive Computing Environments: Links with Software Engineering and Ontological Engineering

In this article we present a review of selected literature of context-aware pervasive computing while integrating theory and practice from various disciplines in order to construct a theoretical grounding and a technical follow-up path for our future research. This paper is not meant to provide an extensive review of the literature, but rather to integrate and extend fundamental and promising theoretical and technical aspects found in the literature. Our purpose is to use the constructed theory and practice in order to enable anywhere and anytime adaptive e-learning environments. We particularly elaborate on context, adaptivity, context-aware systems, ontologies and software development issues. Furthermore, we represent our view point for context-aware pervasive application development particularly based on higher abstraction where ontologies and semantic web activities, also web itself, are of crucial.

Decision Support-Related Resource Presence and Availability Awareness for DSS in Pervasive Computing Environments

Over the last 10 years, pervasive computing environments and mobile networks have become extremely popular. Despite the many end user benefits of pervasive computing, the intrinsic instability and context ambiguities of these environments pose impediments to data-oriented decision support systems. In pervasive computing environments where users, systems, and computing resources are distributed or mobile, the online or “available” state of decision support-related resources may be intermittent or delayed. Awareness or knowledge of these resources’ online presence and availability can affect the decision making process. This article discusses issues related to data-driven decision support systems (DSS) in pervasive computing environments (PCE) and demonstrates that a decision maker’s awareness of online status and availability can improve decision outcomes. A model for extending DSS resource presence and availability awareness to decision makers is presented and the impact of this knowledge on decision outcomes is evaluated using a management problem simulation.

An Impregnable Lightweight Device Discovery (ILDD) Model for the Pervasive Computing Environment of Enterprise Applications

The worldwide use of handheld devices (personal digital assistants, cell phones, etc.) with wireless connectivity will reach 2.6 billion units this year and 4 billion by 2010. More specifically, these handheld devices have become an integral part of industrial applications. These devices form pervasive ad hoc wireless networks that aide in industry applications. However, pervasive computing is susceptible and vulnerable to malicious active and passive snoopers. This is due to the unavoidable interdevice dependency, as well as a common shared medium, very transitory connectivity, and the absence of a fixed trust infrastructure. In order to ensure security and privacy in the pervasive environment, we need a mechanism to maintain a list of valid devices that will help to prevent malicious devices from participating in any task. In this paper, we will show the feasibility of using a modified human- computer authentication protocol in order to prevent the malicious attacks of ad hoc networks in industrial applications. We will also present two separate models for both large and small networks, as well as several possible attack scenarios for each network.

Physical, Social, and Experiential Knowledge in Pervasive Computing Environments

Pervasive computing designers and researchers often create services and applications to help people record their experiences. At the same time, cheap, small, and easy-to-deploy recording technologies are quickly emerging throughout public spaces. In many ways, these technologies are pervasive computing realized. Understanding how people deal with audio and video recording is therefore a good way to explore how people might adopt, adapt, and react to pervasive computing technologies in general. A long-term deployment of a system for recording experiences in informal spaces demonstrates that people use physical, social, and experiential knowledge to determine new technologies' relative utility and safety. In this paper, we aim to add significantly to the research surrounding security and privacy concerns by focusing on them rather than just noting them as a side effect of testing an application's utility and usability.

Semantics for the intuitive governance of autonomic user‐centered pervasive computing environments

As Pervasive Computing environments become more richly populated with sensors and computing power it may be possible for the environment to observe and interpret user actions and pre‐emptively provide accurate support for those actions. This requires accurate inference of user intent. Though individual user acts may be inferable from environmental context sensing, the inference of intent for which appropriate support might be offered is more challenging. Numerous researchers have used probabilistic techniques such as Bayesian Analysis techniques to attempt such inference. Unlike a desktop environment, however, pervasive computing environments are extremely heterogeneous, so any heuristics used must be tailored to the physical environment and the users in question. Thus these techniques are only likely to be accurate if configured with accurate knowledge of routine user behavior. Many existing approaches attempt to learn such knowledge from operational data, but this often requires user involvement in training and expert configuration of probabilistic processing structure. In this paper we examine a complimentary approach where users are presented with an intuitive interface to support the direct configuration of probabilistic structure by users with appropriate knowledge. By treating an intent inference system for a particular pervasive computng environment as an autonomic system, we approach the problem as the design of an intuitive governance interface for this system. We then present the design and usability evaluation of this governance interface.

Privacy-enhanced, Attack-resilient Access Control in Pervasive Computing Environments with Optional Context Authentication Capability

In pervasive computing environments (PCEs), privacy and security are two important but contradictory objectives. Users enjoy services provided in PCEs only after their privacy issues being sufficiently addressed. That is, users could not be tracked down for wherever they are and whatever they are doing. However, service providers always want to authenticate the users and make sure they are accessing only authorized services in a legitimate way. In PCEs, such user authentication may include context authentication in addition to the entity authentication. In this paper, we propose a novel privacy enhanced anonymous authentication and access control scheme to secure the interactions between mobile users and services in PCEs with optional context authentication capability. The proposed scheme seamlessly integrates two underlying cryptographic primitives, blind signature and hash chain, into a highly flexible and lightweight authentication and key establishment protocol. It provides explicit mutual authentication and allows multiple current sessions between a user and a service, while allowing the user to anonymously interact with the service. The proposed scheme is also designed to be DoS resilient by requiring the user to prove her legitimacy when initializing a service session.

A Novel Privacy Preserving Authentication and Access Control Scheme for Pervasive Computing Environments

Privacy and security are two important but seemingly contradictory objectives in a pervasive computing environment (PCE). On one hand, service providers want to authenticate legitimate users and make sure they are accessing their authorized services in a legal way. On the other hand, users want to maintain the necessary privacy without being tracked down for wherever they are and whatever they are doing. In this paper, a novel privacy preserving authentication and access control scheme to secure the interactions between mobile users and services in PCEs is proposed. The proposed scheme seamlessly integrates two underlying cryptographic primitives, namely blind signature and hash chain, into a highly flexible and lightweight authentication and key establishment protocol. The scheme provides explicit mutual authentication between a user and a service while allowing the user to anonymously interact with the service. Differentiated service access control is also enabled in the proposed scheme by classifying mobile users into different service groups. The correctness of the proposed authentication and key establishment protocol is formally verified based on Burrows-Abadi-Needham logic

Resource Adaptation Scheme for QoS Provisioning in Pervasive Computing Environments: A Welfare Economic Approach

Management of applications in the new world of pervasive computing requires new mechanisms to be developed for admission control, QoS negotiation, allocation and scheduling. To solve such resource-allocation and QoS provisioning problems within pervasive and ubiquitous computational environments, distribution and decomposition of the computation are important. In this paper we present a QoS-based welfare economic resource management model that models the actual price-formation process of an economy. We compare our economy-based approach with a mathematical approach we previously proposed. We use the constructs of application benefit functions and resource demand functions to represent the system configuration and to solve the resource allocation problems. Finally empirical studies are conducted to evaluate the performance of our proposed pricing model and to compare it with other approaches such as priority-based scheme and greedy method.

Mobile Agent Connection Establishment and Management (CEMA)—Message Exchange for Pervasive Computing Environments

Pervasive computing is an emerging technology that offers new possibilities to distributed computing and computer networking; it employs a wide variety of smart, ubiquitous devices throughout an individual's working and living environment. Mobile agents are software entities that can migrate between servers (mobile agent environments) of the network accomplishing various tasks on the behalf of their owners. The objective of this paper is to describe a test and prototyping environment for experimenting with mobile agents in pervasive environments. A prototype environment for a novel, proactive infrastructure is described for mobile agent assisted pervasive computing. In addition, a new message passing algorithm is provided for mobile agent connection establishment and management (CEMA). Simulation results show the performance of the proposed approach.

Toward context-aware computing: experiences and lessons

To minimize distractions, a pervasive-computing environment must be context-aware. The authors define an activity-attention framework for context-aware computing, discuss the spatial and temporal aspects of applications they developed, and introduce a pervasive-computing architecture.