Wormhole attacks enable an attacker with limited resources and no cryptographic material to disrupt wireless networks. In a wormhole attack, an attacker records packets (or bits) at one location in the network, tunnel...
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ISBN:
(纸本)9781424426430
Wormhole attacks enable an attacker with limited resources and no cryptographic material to disrupt wireless networks. In a wormhole attack, an attacker records packets (or bits) at one location in the network, tunnels them (possibly selectively) to another location and retransmits them there into the network. In this paper, we present an algorithm for detecting and thus defending against wormhole attacks in wireless multi-hop networks. This algorithm uses only local and neighborhood information without requiring clock synchronization, location information or dedicated hardware. Moreover, the algorithm is independent of wireless communication models. We present simulation results for grid-like topologies and for random topologies and show that the algorithm is able to detect wormhole attacks in all cases whereas the number of false alarms (false detections) decreases rapidly if the network is sufficiently dense.
Multiple input multiple output (MIMO) wireless systems have gained increasing attention today. Based on research for the known spatial multiplexing detection algorithms, in order to improve BER performance and decreas...
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Multiple input multiple output (MIMO) wireless systems have gained increasing attention today. Based on research for the known spatial multiplexing detection algorithms, in order to improve BER performance and decrease the computational complexity, we propose a MIMO transceiver scheme using singular linear transformation (SLT) in this paper. In this scheme, the transmitted signal vectors with a proper time interval are combined together by an optimizing singular linear matrix. The signal detection at the receiver includes the coarse estimator based on zero forcing (ZF) filter and the fine estimator based on parallel interference cancelation (PIC). Simulation results show that this novel MIMO scheme can improve the receive diversity order, improve the Bit Error Rate (BER) performance, and decrease the computational complexity without loss in spectrum efficiency.
This paper proposes a novel approach to discover a set of class specific "composite features" as the feature pool for the detection and classification of complex objects using AdaBoost. Each composite featur...
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This paper proposes a novel approach to discover a set of class specific "composite features" as the feature pool for the detection and classification of complex objects using AdaBoost. Each composite feature is constructed from the combination of multiple individual features. Unlike previous works that design features manually or with certain restrictions, the class specific features are selected from the space of all combinations of a set of individual features. To achieve this, we first establish an analogue between the problem of discriminative feature selection and generative image segmentation, and then draw discriminative samples from the combinatory space with a novel algorithm called Discriminative Generalized Swendsen-Wang Cut. These samples form the initial pool of features, where AdaBoost is applied to learn a strong classifier combining the most discriminative composite features. We demonstrate the efficacy of our approach by comparing with existing detection algorithms for finding people in general pose.
This paper examines and extracts the parallelism in the AdaBoost person detection algorithm on multi-core processors. As multi-core processors become pervasive, effectively executing many threads simultaneously is cru...
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This paper examines and extracts the parallelism in the AdaBoost person detection algorithm on multi-core processors. As multi-core processors become pervasive, effectively executing many threads simultaneously is crucial in harnessing the computation power. Although the application exposes many levels of parallelism, none of them delivers a satisfactory scaling performance on newest multi-core processors due to load imbalance and parallel overhead. This paper demonstrates how to analyze the thread-level parallelism, and how to choose appropriate one to utilize current 4-core and 8-core processors. With careful optimization and parallelization, the AdaBoost person detection algorithm can efficiently utilize the power of multi-core processors, and now it is 7 times faster than the serial version.
This paper proposes a distributed coordinate-free non-triangulated hole recovery algorithm for sensor networks called 3MeSH-DR (triangular mesh distributed hole recovery), which recovers coverage holes with the minimu...
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This paper proposes a distributed coordinate-free non-triangulated hole recovery algorithm for sensor networks called 3MeSH-DR (triangular mesh distributed hole recovery), which recovers coverage holes with the minimum number of redundant nodes using only connectivity information. If this hole cannot be triangulated by edges between pairs of nodes closer that 2 units from each other, the boundary of the hole is detected accurately with the minimum number of edges. It is shown to be error-free by thousands of simulations with different random topologies and node densities. Because of its high reliability and modest requirements for computing power and memory, 3MeSH-DR is an efficient solution for hole detection and recovery without location information in real sensor network applications.
In this study, an innovative least-squares adaptive estimator is developed for heart fault diagnosis. The reference model of this study is the one developed by Ursino in 1998. Mitral valve function is studied in this ...
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In this study, an innovative least-squares adaptive estimator is developed for heart fault diagnosis. The reference model of this study is the one developed by Ursino in 1998. Mitral valve function is studied in this paper based on a new method which uses invasive noisy blood pressure waveform observations of left ventricle, left atrium, and left pulmonary vein. To meet this end, an adaptive algorithm is designed for estimation of discontinuous time-variant parameter values and then Ursinopsilas model simulator is utilized for the evaluation of Mitral valve non-linear gain. The results obtained, indicate the high capability of the presented model in the estimation of different cardiovascular parameters and so fault diagnosis in heart valves.
In this paper we present a novel rotation- and affine-invariant image regions detector, coined OSR (Optimum Similar Regions). The two steps of OSR is: first, segment an image with thresholds based on graph theory, the...
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In this paper we present a novel rotation- and affine-invariant image regions detector, coined OSR (Optimum Similar Regions). The two steps of OSR is: first, segment an image with thresholds based on graph theory, these regions of the segmentation results are so called similar regions. Second, the subset of similar regions is confirmed according to the regulation of the similar region’s cardinality. The paper presents experimental results on a standard evaluation set, as well as on application of wide baseline image matching. Both of them show OSR’s strong performance.
Automatic cell segmentation has various applications in different parts of science. The development of automated methods for cell segmentation, remains challenging in situations where there are touching cells. In this...
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Automatic cell segmentation has various applications in different parts of science. The development of automated methods for cell segmentation, remains challenging in situations where there are touching cells. In this paper we propose a new method for separating touching cells. As the first step, we use a combination of graph segmentation algorithm and thresholding for segmenting foreground objects and producing a binary image. Next, boundary points of separation zone are selected by using a corner detection algorithm. Finally, the marker controller watershed transform is applied to separate touching cells at selected points.
A generalized likelihood ratio test is derived for detecting target patterns in multi-band spectral images with improper complex Gaussian noise. The GLR test generalizes previously derived tests, which were restricted...
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A generalized likelihood ratio test is derived for detecting target patterns in multi-band spectral images with improper complex Gaussian noise. The GLR test generalizes previously derived tests, which were restricted to proper complex Gaussian noise. However, this generalization comes for the price of increased computational time. The GLR test is derived based on the joint multivariate pdf of the magnitude and phase of correlated complex Gaussian variables. An expression for the probability of false alarm is obtained which shows that the test achieves a constant false alarm rate. The GLR test was applied to simulation and experimental data and showed satisfying results.
We consider BCJR-like soft-input soft-output (SISO) iterative detection algorithms for ID and 2D binary-input ISI channels with AWGN. The complexity of BCJR algorithms grows exponentially with the size of the ISI mask...
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We consider BCJR-like soft-input soft-output (SISO) iterative detection algorithms for ID and 2D binary-input ISI channels with AWGN. The complexity of BCJR algorithms grows exponentially with the size of the ISI mask and is an important concern with their implementation. We consider new techniques to reduce the complexity of BCJR algorithms by decreasing the effective number of states in the trellis. The proposed state reduction technique does particularly well for mixed phase sequence ISI masks, which have higher weights for the center taps and lower weights for the peripheral taps. Other complexity reduction techniques proposed in the literature perform poorly for such masks. Moreover, the complexity of the proposed state reduction technique is comparable to other reduced complexity techniques reported in the literature. Experimental results are provided to demonstrate the advantages of the proposed state reduction technique.
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