After a wireless sensor network (WSN) is deployed, its operational lifetime depends on its energy resources. Available results reveal that significant improvement in WSN lifetime can be achieved by making WSNs redundant, that is, by adding to WSNs spare nodes that are initially asleep but are ready to be switched on when any primary node (i.e., a node that is not a spare) uses up its energy. We propose the LEACH-SM protocol - a modification of LEACH. It adds the spare selection phase to LEACH.

We propose a new paradigm---named the Pervasive Trust Foundation (PTF) ---for computer security in Next Generation Networks, including the Future Internet. We start with a review of basic trust-related terms and concepts. We present motivation for using PTF as the basis for security in ISO OSI networks. The paper includes our five contributions. First, we define trust in the small (TIS) and trust in the large (TIL), where TIL is equivalent to PTF. Second, we list and contrast required and prohibited features of PTF-based systems. Third, we enumerate claims of benefits derived from using PTF. Fourth, we identify two major obstacles to PTF realization, and discuss multiple approaches to overcoming these obstacles. The more important of the two obstacles can be eliminated by showing an efficient implementation of PTF-based security. Fifth, we present an outline for the Basic Reference Model for PTF for Next Generation Networks. Summary and discussion of future work concludes the paper.

Entities (e.g., users, services) have to authenticate themselves to service providers (SPs) in order to use their services. An entity provides personally identifiable information (PII) that uniquely identifies it to an SP. In the traditional application-centric Identity Management (IDM) model, each application keeps trace of identities of the entities that use it. In cloud computing, entities may have multiple accounts associated with different SPs, or one SP. Sharing PIIs of the same entity across services along with associated attributes can lead to mapping of PIIs to the entity. We propose an entity-centric approach for IDM in the cloud. The approach is based on: (1) active bundles-each including a payload of PII, privacy policies and a virtual machine that enforces the policies and uses a set of protection mechanisms to protect themselves, (2) anonymous identification to mediate interactions between the entity and cloud services using entity's privacy policies. The main characteristics of the approach are: it is independent of third party, gives minimum information to the SP and provides ability to use identity data on untrusted hosts.

Cloud computing allows the use of Internet-based services to support business processes and rental of IT-services on a utility-like basis. It offers a concentration of resources but also poses risks for data privacy. A single breach can cause significant loss. The heterogeneity of “users” represents a danger of multiple, collaborative threats. In cloud computing, entities may have multiple accounts associated with a single or multiple service providers (SPs). Sharing sensitive identity information (that is, Personally Identifiable information or PII) along with associated attributes of the same entity across services can lead to mapping of the identities to the entity, tantamount to privacy loss. Identity management (IDM) is one of the core components in cloud privacy and security and can help alleviate some of the problems associated with cloud computing. Available solutions use trusted third party (TTP) in identifying entities to SPs. The solution providers do not recommend the usage of their solutions on untrusted hosts. We propose an approach for IDM, which is independent of TTP and has the ability to use identity data on untrusted hosts. The approach is based on the use of predicates over encrypted data and multi-party computing for negotiating a use of a cloud service. It uses active bundle-which is a middleware agent that includes PII data, privacy policies, a virtual machine that enforces the policies, and has a set of protection mechanisms to protect itself. An active bundle interacts on behalf of a user to authenticate to cloud services using user's privacy policies.

Abstract In this paper, we discuss security problems, with a focus on collaborative attacks, in the Worldwide Interoperability for Microwave Access (WiMAX) scenario. The WiMAX protocol suite, which includes but is not limited to DOCSIS, DES, and AES, consists of a large number of protocols. We present briefly the WiMAX standard and its vulnerabilities. We pinpoint the problems with individual protocols in the WiMAX protocol suite, and discuss collaborative attacks on WiMAX systems. We present several typical WiMAX attack scenarios, including: bringing a large number of attackers to increase their computation power and break WiMAX protocols; assembling a sufficient number of attackers to influence the decision‐making of core machines, which includes routing attacks and Sybil attacks; and exploiting implementations that do not conform to the WiMAX specification completely, causing interoperability problems among various protocols, including the ones in typical WiMAX/WiFi/LAN deployment scenarios. We present theoretical models and practical solutions to profile, model, and analyze collaborative attacks in WiMAX. We employ attack graphs to do vulnerability analysis. Experimental results verify our models and validate our analysis. Copyright © 2009 John Wiley & Sons, Ltd.

In tracking applications of wireless sensor networks (WSNs), the classification of an object or event of interest is envisaged to be one of the most computationally intensive tasks that recur frequently over the lifetime of the network. It is imperative that the implementations of such tasks be power efficient and computationally feasible for resource-constrained WSNs. Existing implementations of the best known classifiers such as maximum Aposterior (MAP) classifier are computationally infeasible for WSN environments. The focus of this paper is to investigate computational techniques to realize power efficient distributed implementation of the MAP classifier. In the MAP classifier, one of the most computationally challenging steps is the computation of the inverse of the covariance matrices. In this paper, we study computationally efficient methods for realizing the inverse of a matrix. We present a detailed discussion of one-sided Jacobi Iterations and LU Decomposition for approximating and computing the inverse of the covariance matrices. For LU Decomposition-based solutions, we also apply folding techniques to ensure equal power dissipation among the sensor network nodes. Our contribution lies in the power consumption analysis of executing the MAP classifier using LU decomposition and one-sided Jacobi Iterations to substitute the inverse of the covariance matrices. We show that MAP with one-sided Jacobi Iterations greatly simplifies classification process and makes it more feasible and efficient choice for sensor network applications.

Class 2 opportunistic networks (oppnets) are a new paradigm for Collaborative Computing that aims at integrating communication, computation, sensing, actuation, storage, and other resources and services. Oppnets achieve global tasks and goals through the collaboration and coordination of their nodes (some of which join an oppnet dynamically). We describe the concept of oppnets, discuss related work, and present the standard API framework for oppnets name Oppnet Virtual Machine (OVM). We present the design and implementation details of a small-scale proof-of-concept system, named MicroOppnet, in terms of the OVM primitives. We describe both the design and implementation of MicroOppnet, which not only is a proof of concept but also constitutes our tool for experiments in collaborative computing with oppnets. We are currently working on extending MicroOppnet into a larger oppnet prototype and an oppnet testbed.

We present a novel paradigm of opportunistic networks or oppnets in the context of emergency preparedness and response (EPR). Oppnets constitute the category of ad hoc networks where diverse systems, not employed originally as nodes of an oppnet, join it dynamically in order to perform certain tasks they have been called to participate in. After describing the oppnets and their operation, we discuss the oppnet virtual machine (OVM) - a standard implementation framework for oppnet applications. Oppnets can significantly improve effectiveness and efficiency of EPR one of the six mission areas within the national strategy for homeland security. They can also improve other diverse applications, including agriculture, environment, healthcare, manufacturing, surveillance, and transportation. Oppnets should create new application niches as yet hard to imagine. To the best of our knowledge we have been the first to work on oppnets.

Specialized ad hoc networks and systems (SAHNS) can facilitate design and implementation of applications supported by them. We propose a SAHNS taxonomy for emergency preparation and response (EPR) applications. It is constructed by a simple method based on extracting critical requirements for an arbitrary application area. Once the taxonomy is constructed, each path in the taxonomy tree identifies either an existing or a new potential SAHNS design for EPR applications. In the latter case, a new SAHNS design is discovered. In the future, existing and potential SAHNS designs will be evaluated using the parameters from the taxonomy tree. The ultimate goal of this work is development of a method and tools for systematic development of specialized ad hoc networks or systems for an arbitrary application area.

An adequate level of trust must be established between prospective partners before an interaction can begin. In asymmetric trust relationships, one of the interacting partners is stronger. The weaker partner can gain a higher level of trust by disclosing private information. Dissemination of sensitive data owned by the weaker partner starts at this moment. The stronger partner can propagate data to others, who may then choose to spread data further. The proposed scheme for privacy-preserving data dissemination enables control of data by their owner (such as a weaker partner). It relies on the ideas of bundling sensitive data with metadata, an apoptosis of endangered bundles, and an adaptive evaporation of bundles in suspect environments. Possible applications include interactions among patients and healthcare providers, customers and businesses, researchers, and suppliers of their raw data. They will contribute to providing privacy guarantees, which are indispensable for the realization of the promise of pervasive computing

Preserving privacy during Web transactions is a major concern for individuals and organizations. One of the solutions proposed in the literature is to maintain anonymity through group cooperation during Web transactions. The lack of understanding of incentives for encouraging group cooperation is a major drawback in such systems. We propose an anonymizing club mechanism, and sequential economic strategy for trusted collaboration. We model the individual transactions as a Prisoners' Dilemma, where two players either cooperate or defect while maintaining each other's anonymity. The activities of the participants over a series of transactions can be modeled as a sequential repeated game. We determine conditions to ensure cooperation among the participants in the sequential repeated game, even if defecting is a dominant strategy in each individual Prisoners' Dilemma game. Our results show that by adopting an appropriate initiation fee and adequate fine for malicious behavior, both enforced through a trusted central authority, we can sustain cooperation in the proposed anonymizing club mechanism.

The quasi-partitioning paradigm of operation for partitioned database systems is discussed in which a broken main link between two partitions can be replaced by a much slower backup link (e.g. a dial-up telephone connection). The paradigm solves the problem of preparation for network partitioning. The quasi-partitioning mode of operation has two primitive operations: creeping retrieval and creeping merge. Creeping retrieval increases data availability by crossing partition boundaries (over backup links) to read foreign data. Similarly, creeping merge improves the degree of partition-consistency by crossing partition boundaries to perform merge actions. A quasi-partitioning protocol consists of an adaptation protocol and a merge protocol. Taxonomies are shown for quasi-partitioning adaptation protocols and for quasi-partitioning merge protocols (for restoring partition-consistency after system reconnection). Since merge protocols and adaptation protocols are interdependent, it is indicated here how these protocols should be paired.>

A communication link failure can result in a network partitioning that fragments a distributed database system into isolated parts. If a severed high-speed link (e.g. satellite link) between the partitions can be replaced by a much slower backup link (e.g. a dial-up telephone line), the partitioning becomes a quasipartitioning. Two protocols for transaction processing in quasipartitioned databases are proposed. The protocols are pessimistic in that they permit transactions to be updated in exactly one partition. The first protocol is defined for a fully partition-replicated database in which every partition contains a copy of every data object. The second protocol is defined for a partially partition-replicated database in which some objects have no copies in some partitions. Both protocols improve their major performance measures linearly with the backup link speed but are not visibly affected by duration of the partitioning or the database size.>

A study is made of a known implementation of an optimistic concurrency-control algorithm for centralized database systems and improvements are suggested to the algorithm. The authors propose an implementation of an algorithm for the basic timestamp-ordering concurrency control in centralized database systems. The two algorithms are compared by simulation experiments. As expected, the optimistic approach is better for transaction mixes dominated by retrievals. For transaction mixes dominated by updates, the optimistic algorithm spends time performing operations that have a good chance of being voided by earlier conflicting operations. The authors expected the timestamp algorithm to be better in these circumstances but, this is not the case. They attribute this to the fact that transactions used in the experiments are short, and therefore the execution time lost due to an abort is small.>

The authors propose two protocols for transaction processing in quasi-partitioned databases. The protocols are pessimistic in that they permit the execution of update transactions in exactly one partition. The first protocol is defined for a fully partition-replicated database in which every partition contains a copy of every data object. The second protocol is defined for a partially partition-replicated database in which some objects have no copies in some partitions. Both protocols improve their major performance measures linearly with the backup link speed but are not visibly affected by either duration of the partitioning or the database size. This is a desirable property, since the backup link speed is the only controllable parameter.>

We propose new adaptive techniques for distributed query optimization. These techniques are divided into two groups: the ones that improve efficiency of query execution (directly) and the ones that improve cost estimations for query execution strategies. Some of the proposed techniques utilize semantic information and knowledge acquisition to adapt to the environment. The latter, in contrast to the former, is not a well-established idea. This is a disturbing fact since knowledge acquisition can give significant improvements in performance of a query optimization algorithm. Performing analysis manually is extrernely time consuming and tedious. Therefore, some learning capacity should be added to the system. Some knowledge acquisition techniques that result in adaptive (dynamic) adjustment to run-time changes are proposed.

When a crash occurs in a transaction processing system, the database can enter an unacceptable state. To continue the processing, the recovery system has three tasks: 1) verification of the database state for acceptability, 2) restoration of an acceptable database state, and 3) restoration of an acceptable history of transaction processing. Unfortunately these tasks are not trivial and the computational complexity of the algorithms for most of them is either NP-complete or NP-hard. In this paper we discuss the concepts and design issues of a construct called database integrity block (DIB). The implementation of this construct allows for efficient verification of the database state by employing a set of integrity assertions and restoration of transaction history by utilizing any database restoration technique such as audit trail or differential file. This paper presents approximation algorithms for minimizing the costs of evaluation of integrity assertions by modeling the problem as the directed traveling salesman problem, and presents a methodology to compare the costs of audit trail and differential file techniques for database restoration. The applicability of integrity verification research to the problem of multiple-query optimization is also included.

A database management system can ensure the semantic integrity of a database via an integrity control subsystem. A technique for implementation of such a subsystem is proposed. After a database is updated by transactions, its integrity must be verified by evaluation of a set of semantic integrity assertions. For evaluation of an integrity assertion a number of database pages need to be transferred from the secondary storage to the fast memory. Since certain pages may be required for evaluation of different integrity assertions, the order of the evaluation of the integrity assertions determines the total number of pages fetched from the secondary storage. Hence, the schedule for the evaluation determines the cost of the database verification process. We show that the search for an optimal schedule is an NP-hard problem. Four approximation algorithms that find suboptimal schedules are proposed. They are based on the utilization of intersections among sets of pages required for the evaluation of different integrity assertions. The theoretical worst case behaviors of these algorithms are studied. Finally, the algorithms are compared via a simulation study to a naive, random order verification approach. The methods proposed for minimizing the costs of the batch integrity verification also apply to other problems that can be abstracted to the directed traveling salesman optimization problem. For example, the methods are applicable to multiple to multiple-query optimization and to concurrency control via the predicate locks.