PPS: Privacy-Preserving Strategyproof Social-Efficient Spectrum Auction Mechanisms

A hybrid scheme for multicast authentication over lossy networks

Auctions are believed to be effective methods to solve the problem of wireless spectrum allocation. Existing spectrum auction mechanisms are all centralized and suffer from several critical drawbacks of the centralized systems, which motivates the design of distributed spectrum auction mechanisms. However, extending a centralized spectrum auction to a distributed one broadens the strategy space of agents from one dimension (bid) to three dimensions (bid, communication, and computation), and thus cannot be solved by traditional approaches from mechanism design. In this paper, we propose two distributed spectrum auction mechanisms, namely distributed VCG and FAITH. Distributed VCG implements the celebrated Vickrey-Clarke-Groves mechanism in a distributed fashion to achieve optimal social welfare, at the cost of exponential communication overhead. In contrast, FAITH achieves sub-optimal social welfare with tractable computation and communication overhead. We prove that both of the two proposed mechanisms achieve faithfulness, i.e., the agents' individual utilities are maximized, if they follow the intended strategies. Besides, we extend FAITH to adapt to dynamic scenarios where agents can arrive or depart at any time, without violating the property of faithfulness. We implement distributed VCG and FAITH, and evaluate their performance in various setups. Evaluation results show that distributed VCG results in optimal allocation, while FAITH is more efficient in computation and communication.

With the popularity of mobile wireless devices with various kinds of sensing abilities, a new service paradigm named Participatory Sensing has emerged to provide users with brand new life experience. However, the wide application of participatory sensing has its own challenges, among which privacy preservation and multimedia data participatory sensing are two critical problems. Unfortunately, none of the existing works has fully solved the problem of privacy preserving participatory sensing with multimedia data. In this paper, we propose SLICER, which is the first k-anonymous privacy preserving scheme for participatory sensing with multimedia data. SLICER integrates a data coding technique and message exchanging strategies, to achieve strong protection of participants' privacy, while maintaining high data accuracy. In addition, two slice transferring strategies are well designed for slice transfer to minimize the total transfer cost. Finally, we have implemented SLICER and evaluated its performance using publicly released taxi traces. Our evaluation results show that SLICER achieves high data accuracy, with low computation and communication overhead.

Dynamic spectrum redistribution---under which spectrum owners lease out under-utilized spectrum to users for financial gain---is an effective way to improve spectrum utilization. Auction is a natural way to incentivize spectrum owners to share their idle resources. In recent years, a number of strategy-proof auction mechanisms have been proposed to stimulate bidders to truthfully reveal their valuations. However, it has been shown that truthfulness is not a necessary condition for revenue maximization. Furthermore, in most existing spectrum auction mechanisms, bidders may infer the valuations---which are private information---of the other bidders from the auction outcome. In this paper, we propose a Differentially privatE spectrum auction mechanism with Approximate Revenue maximization (DEAR). We theoretically prove that DEAR achieves approximate truthfulness, privacy preservation, and approximate revenue maximization. Our extensive evaluations show that DEAR achieves good performance in terms of both revenue and privacy preservation.

In recent years, auction theory has been extensively studied and many state-of-art solutions have been proposed aiming at allocating scarce resources (e.g. spectrum resources in wireless communications). Unfortunately, most of these studies assume that the auctioneer is always trustworthy in the sealed-bid auctions, which is not always true in a more realistic scenario. On the other hand, performance guarantee, such as social efficiency maximization, is also crucial for auction mechanism design. Therefore, the goal of this work is to design a series of strategyproof and privacy preserving auction mechanisms that maximize the social efficiency. To make the designed auction model more general, we allow the bidders to express their preferences about multiple items, which is often regarded as the multi-unit auction. As computing an optimal allocation in multi-unit auction is NP-hard, we design a set of near optimal allocation mechanisms with privacy preserving separately for: (1) The auction aims at identical multi-items trading; and (2) The auction aims at distinct multi-items trading, which is also known as combinatorial auction. To the best of our knowledge, we are the first to design strategyproof multi-unit auction mechanisms with privacy preserving, which maximize the social efficiency at the same time. The evaluation results corroborate our theoretical analysis, and show that our proposed methods achieve low computation and communication complexity.

Dynamic spectrum reallocation, under which the spectrum owners temporarily share the underutilized spectrum to secondary users for economic profit, is an important approach to improve the spectrum utilization ratio. Auction is believed to be a natural marketing tool to incentivize the spectrum owners, and thus redistribute the idle spectrum efficiently. Extensive researches have been done in the problem of truthful spectrum auction, in which the bidders bid based on their true valuations of the spectrum. The true valuation of the individual bidder, however, is a private information which should be protected against exposure. In this paper, we propose a privacy preserving truthful spectrum auction scheme by utilizing homomorphic encryption. The proposed scheme reveals the group bids but hides the users' bids even from the auctioneer. The evaluation results show that the proposed scheme achieves good spectrum utilization efficiency with low communication and computation overheads.

The advances in sensing capabilities of smartphones give rise to a variety of mobile participatory sensing applications that collect users' personal data. Because of the existence of both sensitive, private personal data, and untrusted aggregator, serious privacy concerns on users arise. Currently, existing privacy preserving data collection methods either require bidirectional communications between an untrusted aggregator and mobile users in every aggregation period, or have high computation or communication overhead. To address these problems, we propose an efficient data aggregation approach by which an untrusted aggregator in mobile sensing can collect the statistics over the data contributed by multiple mobile users, while supporting privacy preservation of each user and data integrity verification. In this approach, information hiding and homomorphic encryption are applied to guarantee the data privacy of mobile users. In detail, a breadth-first search tree is first constructed at the initial phase among the mobile users, and then the original datum of each user is perturbed among its neighbors in ciphertext space by using information hiding and homomorphic encryption. The evaluations of our approach show that our protocol requires lower communication and computation overhead and thus more feasible for the computation constrained mobile devices. Copyright © 2016 John Wiley & Sons, Ltd.

Lightweight anonymous authentication protocol for resource-constrained smart home devices based on elliptic curve cryptography

In cellular networks, a recent trend in research is to make spectrum access dynamic in the spatial and temporal dimensions for the sake of efficient utilization of spectrum. In one such model, the spectrum is divided into channels and periodically allocated to competing base stations using an auction-based market mechanism. An “efficient” auction mechanism is essential to the success of such a dynamic spectrum access model. A key objective in designing an auction mechanism is “truthfulness.” Combining this objective with an optimization of some social choice function (such as the social-welfare or the generated revenue) is highly desirable. In this paper, we design polynomial-time spectrum auction mechanisms that are truthful and yield an allocation with O(1)-approximate social-welfare or revenue. Our mechanisms generalize to general interference models. To the best of our knowledge, ours is the first work to design polynomial-time truthful spectrum auction mechanisms with a constant-factor approximation of either the expected revenue or the social-welfare. We demonstrate the performance of our designed mechanism through simulations.

We propose an efficient multicast source authentication protocol called efficient multi-tree-chains scheme (EMTC), which shows more loss resistibility, less communication cost, and no delay at receivers. The EMTC scheme is based on combination of single Chain scheme and Hash Tree Chains scheme, and integrates the advantages of both. In this scheme, stream is firstly divided into blocks withn packets, and each block consists ofm clusters, everyone of which contains a tree of packets. All clusters are chained together. Through EMTC, packets of one cluster can be authenticated by any packet of the previous cluster. Compared to other multicast authentication protocols, the proposed scheme has the following advantages:➀ dramatically improves the resistance to burst packets loss;➁ low computation and communication overhead;➂ imposes low delay on the sender side and no delay on the receiver side.

Replication of information across a server cluster provides a promising way to support popular Web sites. However a Web server cluster requires some mechanism for directing requests to the best server. One common approach is to use the Domain Name Server (DNS) as a centralized schedule. However address caching mechanisms and the non-uniformity of the load from different client domains complicate the load balancing issue and make existing scheduling algorithms for traditional distributed systems not applicable to Web server clusters. We consider the theoretical DNS policies that require some system state information. We extend them to realistic situations where state information needs to be estimated with low computation and communication overhead. We show that by incorporating these estimators into the DNS policies, load balancing improves substantially, even if the DNS control is limited to a small portion of client requests.

Intra-session network coding is known to be vulnerable to Byzantine attacks: malicious nodes can inject bogus packets, which get combined with legitimate blocks at downstream nodes, thus preventing decoding of original packets and degrading the overall performance. In this paper, we provide a novel approach that can identify the precise location of all Byzantine attackers in systems with intra-session network coding. A key ingredient of our approach is a novel homomorphic MAC scheme for expanding subspaces (SpaceMac) that allows to eliminate any uncertainty in identifying attackers via subspace properties. To the best of our knowledge, our scheme is the first that can identify precisely all Byzantine attackers, and at the same time has both low computation (sub- millisecond) and communication overhead (20 bytes per data block). Simulation results show that, even when there are multiple colluding attackers in a network, all of them can be successfully identified in a very short time.

In the emerging area of sensor-based systems, a significant challenge is to develop scalable, fault-tolerant methods to extract useful information from the data the sensors collect. An approach to this data management problem is the use of sensor database systems, exemplified by TinyDB and Cougar, which allow users to perform aggregation queries such as MIN, COUNT and AVG on a sensor network. Due to power and range constraints, centralized approaches are generally impractical, so most systems use in-network aggregation to reduce network traffic. However, these aggregation strategies become bandwidth-intensive when combined with the fault-tolerant, multipath routing methods often used in these environments. For example, duplicate-sensitive aggregates such as SUM cannot be computed exactly using substantially less bandwidth than explicit enumeration. To avoid this expense, we investigate the use of approximate in-network aggregation using small sketches. Our contributions are as follows: 1) we generalize well known duplicate-insensitive sketches for approximating COUNT to handle SUM, 2) we present and analyze methods for using sketches to produce accurate results with low communication and computation overhead, and 3) we present an extensive experimental validation of our methods.

The controller area network (CAN) is facing a great opportunity. The maturity of this technology makes many researchers believe that CAN may be adopted in more critical systems. However, the suitability of CAN for these challenging applications strongly depends on our capacity to integrate all the solutions already available into a single, comprehensive architecture. We claim that clock synchronization plays a fundamental role in such architecture. Therefore, the means to achieve a solution fulfilling the expected requirements on reliability, cost, and precision must be deeply investigated. This paper discusses the relevance of clock synchronization in the future of CAN systems and describes a novel solution to supply this service. This solution exhibits several advantages: it provides very high precision, causes very low communication and computation overhead, and includes mechanisms to provide fault tolerance. Moreover, and in contrast to previous proposals, it is designed to be orthogonal to the rest of the system. Thus, it can be directly incorporated to any CAN system, without having to replace any of the components, which reduces the cost increment caused by the new service.

An aggregatable subvector commitment (aSVC) scheme is a vector commitment (VC) scheme that can aggregate multiple proofs into a single, small subvector proof. In this paper, we formalize aSVCs and give a construction from constant-sized polynomial commitments. Our construction is unique in that it has linear-sized public parameters, it can compute all constant-sized proofs in quasilinear time, it updates proofs in constant time and it can aggregate multiple proofs into a constant-sized subvector proof. Furthermore, our concrete proof sizes are small due to our use of pairing-friendly groups. We use our aSVC to obtain a payments-only stateless cryptocurrency with very low communication and computation overheads. Specifically, our constant-sized, aggregatable proofs reduce each block’s proof overhead to a single group element, which is optimal. Furthermore, our subvector proofs speed up block verification and our smaller public parameters further reduce block size.