In this paper, we propose an efficient multi-party signature scheme for wireless networks where a given number of signees can jointly sign a document, and it can be verified by any entity who possesses the certified group public key. Our scheme is based on an efficient threshold key generation scheme which is able to defend against both static and adaptive adversaries. Specifically, our key generation method employs the bit commitment technique to achieve efficiency in key generation and share refreshing; our share refreshing method provides proactive protection to long-lasting secret and allows a new signee to join a signing group. We demonstrate that previous known approaches are not efficient in wireless networks, and the proposed multi-party signature scheme is flexible, efficient, and achieves strong security for low-power devices in wireless networks.

With the widespread use of mobile devices, the privacy of mobile location information becomes an important issue. In this paper, we present the requirements on protecting mobile privacy in wireless networks, and identify the privacy weakness of the third generation partnership project - authentication and key agreement (3GPP-AKA) by showing a practical attack to it. We then propose a scheme that meets these requirements, and this scheme does not introduce security vulnerability to the underlying authentication scheme. Another feature of the proposed scheme is that on each use of wireless channel, it uses a one-time alias to conceal the real identity of the mobile station with respect to both eavesdroppers and visited (honest or false) location registers. Moreover, the proposed scheme achieves this goal of identity concealment without sacrificing authentication efficiency.

This paper proposes an efficient authentication scheme, which is suitable for low-power mobile devices. It uses an elliptic-curve-eryptosystem based trust delegation mechanism to generate a delegation passcode for mobile station authentication, and it can effectively defend all known attacks to mobile networks including the denial-of-service attack. Moreover, the mobile station only needs to receive one message and send one message to authenticate itself to a visitor's location register, and the scheme only requires a single elliptic-curve scalar point multiplication on a mobile device. Therefore, this scheme enjoys both computation efficiency and communication efficiency as compared to known mobile authentication schemes.

In this paper, a non-interactive zero-knowledge proof scheme is proposed for secure identification in wireless networks, and it uses a timed oblivious transfer technique to enable a single verifier to identify multiple provers. The verifier and the prover do not need to be synchronized in this scheme. This scheme also enjoys the distance-bounding property which makes the proposed scheme invulnerable to the relay attack. We propose to use the order statistic for the detection of relay attackers. We show that it is optimal in terms of minimum variance. Finally, we shed some light on implementation issues of our proposed scheme.

In this paper, we propose a proactive share refreshing scheme for secret share in a distributed system. It enjoys a strong secrecy property against both static and adaptive adversaries. It employs bit commitment technique to make the refreshing process efficient, and the key refreshing cost is less than 50% of the key generation time with key length at 163 bits while the public key is kept intact after share refreshing, which is a nice features of our scheme.

In this paper, a non-interactive zero-knowledge proof scheme is proposed for secure identification in wireless networks, and it uses a timed oblivious transfer technique to enable a single verifier to identify multiple provers. The verifier and the prover do not need to be synchronized in this scheme. This scheme also enjoys the distance bounding property which makes the proposed scheme invulnerable to the relay attack. We propose to use the order statistic for the detection of relay attackers. We show that it is optimal in terms of minimum variance. Finally, we will shed some light on implementation issues of our proposed scheme.

Hyperspectral images have correlation at the level of pixels; moreover, images from neighboring frequency bands are also closely correlated. In this paper, we propose to use distributed source coding to exploit this correlation with an eye to a more efficient hardware implementation. Slepian-Wolf and Wyner-Ziv based correlated coding theorems have quantified how much additional rate reduction can be obtained. In order to better exploit these correlations, we first propose a prediction model to align images. This model is based on linear prediction techniques and it is simple and shown to be effective for hyperspectral images. We then propose a coding scheme to exploit these correlations. A set-partitioning approach is used on wavelet transformed data to extract bitplanes. Under our correlation model, bitplanes from neighboring bands are correlated and we then use a low-density parity-check based Slepian-Wolf code to exploit this bitplane level correlation. This scheme is appealing for hardware implementation as it is easy to parallelize and it has modest memory requirements. As for coding performance, our preliminary results for high correlation spectral bands from the NASA AVIRIS dataset show, at medium to high reconstructed qualities, gains of about a factor of 3 in compression efficiency as compared to encoding the spectral bands independently using SPIHT.

In-network processing is an appealing principle for resource conservation for sensor network applications. We propose a scheme to compress sensor array data in which one sensor has to send its readings to multiple neighbor sensors. This proposed scheme uses low-density parity-check code based Slepian-Wolf codes to compress these bit-planes extracted from wavelet coefficients with flexible rates, and each receiver uses the sum-product algorithm to decode the progressive transmission. A priori correlation statistic is not required in this scheme, and the reception rate of each receiver is close to conditional entropy with regard to the sender.

In this paper, we propose a compression scheme called spatial set-partitioning in hierarchical trees which exploits the spatial and temporal correlations present in sensor data. This scheme allows progressive transmission and provides scalability in adapting to the underlying correlation structure of sensed data. It uses flexible Slepian-Wolf coding based on low density parity-check codes. Two different decoding schemes are proposed for different types of resource constrained sensor nodes. This scheme outperforms known codecs by a large margin of decibel in terms of the signal-to-noise ratio. This scheme has O(n) complexity for encoding and O(nlog(n)) complexity for decoding using message passing, where n is the codeword length. Experiments and simulation results with field data sets demonstrate the viability of our proposed scheme to wireless sensor networks.

Group based transactions are becoming common via handhelds. Single key based systems may not be able to meet various security requirements. In this paper, we propose a threshold signature scheme based on Pedersen distributed key generation principle which is suitable for handheld devices and ad-hoc networks. Existing distributed key generation protocols use either cryptosystems based on the hardness of discrete logarithm over a finite field or integer factorization. Elliptic curve cryptosystems provide a promising alternative with efficiency which is suitable for low-power devices in terms of memory and processing overhead. In the proposed scheme, the public key from the key generation protocol follows a uniform distribution in the elliptic curve additive group, and the signature can be generated and verified efficiently. We evaluated the proposed key generation protocol and signature scheme using PARI/GP, and the key generation time takes a fraction of a second and the signature signing and verifying can be finished in a few milliseconds on the LINUX Intel PXA 255 processor.

Bursts consist of a varying number of asynchronous transfer mode cells corresponding to a datagram. Here, we generalized weighted fair queueing to a burst-based algorithm with preemption. The new algorithm enhances the performance of the switch service for real-time applications, and it preserves the quality of service guarantees. We study this algorithm theoretically and via simulations.

A novel coding scheme is proposed for applications over wireless microsensor networks to meet both wireless link bandwidth and node energy constraints. First, an analysis is performed on the energy efficiency of coding schemes in wireless microsensor networks. Based on this analysis, we devise a power aware coding scheme, called EESPIHT which exploits the spatio-temporal correlation of multiple sensor readings. It is also made resilient to channel errors: it selects an error correcting code based on source coding information and transmission power so that energy dissipation is minimized. Experimental results on a LINUX implementation and simulation results based on OPNET using field data sets show that the proposed scheme can reduce energy on communication by more than 60% and maintain a signal-to-noise ratio (SNR) gain of 24 dB or better compared to the non-coded case.

Sensor readings in a wireless microsensor network are correlated both spatially and temporally. Various coding and storage schemes and also other applications have been developed to exploit these correlations; therefore it is crucial to efficiently track the correlations. In this paper, a linear prediction algorithm is developed to initially establish the correlations, and the order of linear prediction has been derived from the prediction error power distribution. A tracking algorithm uses discrete Kalman filter to track the correlation once it is initially obtained. This Kalman filter based algorithm uses the gradient computed at each step as the input control vector. This approach is suitable for quantifying geographical spatial correlation and multimodality correlation. Experimental results using various data sets have shown that the proposed scheme can accurately obtain the correlation and consumes much less energy as compared to known schemes.

Sensor networks are used in a variety of applications for event monitoring, environmental sensing and outer space exploration. An important application is detecting a target in the field using sensors gathering acoustic data. In this target detection application (ATR), a cluster of wireless sensors collected acoustic data and perform signal processing. In the algorithm used for signal processing, acoustic data collected by the sensors need to be communicated to a designated head node for determining the target direction of bearing. The data collected by geometrically closely distributed sensors show high spatial correlation. In this paper, our focus is on energy efficient coding schemes for wireless sensor networks. First we give an analysis to show why conventional compression scheme give poor performance when energy consumption for encoding and decoding processing overheads are considered. We then describe a new coding scheme called EEADSC, which minimizes the Lagrangian cost function. The proposed scheme fully exploits spatial correlation in wireless sensor network and is adaptive according to tracking signal strength. We evaluated the proposed scheme using datasets from an ATR application, which achieved up to a factor of 8 data compression. EEADSC uses TCQ quantization and trellis encoding to represent a 16 bit data value by as few as 2 bits. With the scheme, we reduce the overall energy cost for communication in this application by a factor of 2.53, including the overhead processing cost in encoding/decoding. The scheme also fits well for general sensor network applications in which some data collection and aggregation are performed.

Fair queueing is a useful queueing discipline for packet switching systems. It was developed in last decade and was aimed at the general packet switching systems with varying packet length. However it is not suitable for use in the ATM networking, because the ATM cell length is very small and fixed, and so the scheduling scheme on a per cell basis is not practical. We introduce the burst and quality unit concepts in the scheduling algorithm and we make some significant modification on the fair queueing and adapt it to ATM networking to meet QoS requirements. Under the work-conserving assumption, we show that the burst based non-preemptive and preemptive algorithms provide throughput and fairness guarantees.

For pt.I see ibid. p.445-61. The scheduling scheme of a switch affects the delay, throughput and fairness of a network and thus has a great impact on the quality of service (QoS). In part I, we present a theoretical analysis of a burst scheduling for ATM switches and proved QoS guarantees on throughput and fairness of the applications. Here, we use simulation to demonstrate the superiority of the burst based weighted fair queueing over the non-burst version. Our simulation study is based on backbone and access subnetworks, which are common in the real world.