Encryption is a well-studied technique for protecting the confidentiality of sensitive data. However, encrypting relational databases affects the performance during query processing. Preserving the order of the encryp...
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ISBN:
(纸本)9789898425300
Encryption is a well-studied technique for protecting the confidentiality of sensitive data. However, encrypting relational databases affects the performance during query processing. Preserving the order of the encrypted values is a useful technique to perform queries over the encrypted database with a reasonable overhead. Unfortunately, the existing order preserving encryption schemes are not secure against known plaintext attacks and statistical attacks. In those attacks, it is assumed that the attacker has prior knowledge about plaintext values or statistical information on the plaintext domain. This paper presents a novel database encryption scheme called MV-POPES (Multivalued - Partial Order Preserving Encryption Scheme), which allows privacy-preserving queries over encrypted databases with an improved security level. Our idea is to divide the plaintext domain into many partitions and randomize them in the encrypted domain. Then, one integer value is encrypted to different multiple values to prevent statistical attacks. At the same time, MV-POPES preserves the order of the integer values within the partitions to allow comparison operations to be directly applied on encrypted data. Our scheme is robust against known plaintext attacks and statistical attacks. MV-POPES experiments show that security for sensitive data can be achieved with reasonable overhead, establishing the practicability of the scheme.
The paper deals with voice recognition systems. A new finite element signal processing method is obtained. Each input signal is processed by a particular frequency. Most authors analyse the cepstral coefficients in th...
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In this paper, we present fast neural networks (FNNs) for human motion detection, which might be advantageous especially in various tasks of image tracking. The proposed FNNs uses cross correlation in the frequency do...
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ISBN:
(纸本)9789604741144
In this paper, we present fast neural networks (FNNs) for human motion detection, which might be advantageous especially in various tasks of image tracking. The proposed FNNs uses cross correlation in the frequency domain between the input image and the input weights of neural networks. It is proved mathematically and practically that the number of computation steps required for the FNNs is less than that needed by conventional neural Networks (CNNs). Simulation results using MATLAB confirm the theoretical computations. Then, another neural networks to classify human motion activities (e.g. walking, running) is used. To eliminate the undesirable problems accompanying human motion such as lighting and objects, we adapt and efficiently adapt existing techniques ranging from homomorphic filtering to simple morphological operations. Moreover, an intelligent technique to optimize the process of the moving target, by significantly reducing the number of pixels using the "star" skeletonization is introduced. With this approach, no more than eleven Fourier descriptors are required to completely describe the moving target. The approach is computationally inexpensive and thus ideal for video applications including video surveillance. An experiment to certify this efficiency was performed with 100 % accuracy results.
Microblogs generate a vast amount of data in which users express their emotions regarding almost all aspects of everyday life. Capturing affective content from these context-dependent and subjective texts is a challen...
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Challenged networks (CNs) contain resource-constrained nodes deployed in regions where human intervention is difficult. Opportunistic networks (OppNets) are CNs with no predefined source-to-destination paths. Due to t...
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In the University setting, part of management recorded all education transaction since the students register until they graduate. In this point, the transaction raises several new and crucial challenges. At a closer l...
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Prediction of market price is very important for strategic planning. In this paper, a new approach for fast market price prediction is presented. Such algorithm uses fast time delay neural networks (FTDNNs). The opera...
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ISBN:
(纸本)9789604741953
Prediction of market price is very important for strategic planning. In this paper, a new approach for fast market price prediction is presented. Such algorithm uses fast time delay neural networks (FTDNNs). The operation of these networks relies on performing cross correlation in the frequency domain between the input data and the input weights of neural networks. It is proved mathematically and practically that the number of computation steps required for the presented FTDNNs is less than that needed by conventional time delay neural networks (CTDNNs). Simulation results using MATLAB confirm the theoretical computations.
In this paper a new video watermarking scheme is proposed which depends on 2-level Discrete Wavelet Transform decomposition of each component of an RGB video frame. The scheme embeds independent watermarks into differ...
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In this paper a new video watermarking scheme is proposed which depends on 2-level Discrete Wavelet Transform decomposition of each component of an RGB video frame. The scheme embeds independent watermarks into different shots. A genetic algorithm is employed to match shots to watermarks. The scheme chooses between the HL1 of red or green or blue components of each frame based on a key and embeds error correcting code into one of them. The scheme is blind. Experimental results show that the scheme is robust against attacks such as frame dropping, frame averaging, frame swapping, statistical analysis, and MPEG-2 and MPEG-4 compression. The proposed scheme uses a composite three-element key to increase the security.
Nowadays, designing and developing wearable devices that could detect many types of diseases has become inevitable for E-health field. The decision-making of those wearable devices is done by various levels of analysi...
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In this paper we examine the integration of speaker identification/verification technology into two dialogue systems developed at MIT: the Mercury air travel reservation system and the Orion task delegation system. Th...
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In this paper we examine the integration of speaker identification/verification technology into two dialogue systems developed at MIT: the Mercury air travel reservation system and the Orion task delegation system. These systems both utilize information collected from registered users that is useful in personalizing the system to specific users and that must be securely protected from imposters. Two speaker recognition systems, the MIT Lincoln Laboratory textindependent GMM based system and the MIT Laboratory for computer Science text-constrained speaker-adaptive ASRbased system, are evaluated and compared within the context of these conversational systems.
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