A computationally-efficient construction for the matrix-based key distribution in sensor network

This paper introduces a variant for the symmetric matrix-based key distribution in sensor network introduced by Du et al. Our slight modification shows that the usage of specific structures for the public matrix instead of fully random matrix with elements in $\mathbb{Z}_q$ can reduce the computation overhead for generating the public key information and the key itself. An intensive analysis followed by modified scheme demonstrates the value of our contribution in relation with the current work and show the equivalence of the securityComment: 4 page

Unveiling Zeus

Malware family classification is an age old problem that many Anti-Virus (AV) companies have tackled. There are two common techniques used for classification, signature based and behavior based. Signature based classification uses a common sequence of bytes that appears in the binary code to identify and detect a family of malware. Behavior based classification uses artifacts created by malware during execution for identification. In this paper we report on a unique dataset we obtained from our operations and classified using several machine learning techniques using the behavior-based approach. Our main class of malware we are interested in classifying is the popular Zeus malware. For its classification we identify 65 features that are unique and robust for identifying malware families. We show that artifacts like file system, registry, and network features can be used to identify distinct malware families with high accuracy---in some cases as high as 95%.Comment: Accepted to SIMPLEX 2013 (a workshop held in conjunction with WWW 2013

Downlink macro-diversity precoding-aided spatial modulation

In this paper, a downlink macro-diversity precodingaided spatial modulation (MD-PSM) scheme is proposed, in which two base stations (BSs) communicate simultaneously with a single mobile station (MS). As such, the proposed scheme achieved twice the spectral efficiency of the conventional PSM scheme. To render the demodulation possible, the two signal constellation sets used at the two BSs should be disjoint. Also, since the two BSs use the same spatial dimension, i.e., indices of receive antennas, the Minkowski sum of the two constellation sets should include unrepeated symbols. This is achieved through rotating the constellation set used by the second BS, where the error rate is also minimized. After obtaining the optimal rotation angles for several scenarios, a reduced complexity maximum-likelihood receiver is introduced. For an equal number of transmit and receive antennas of 4 and at a target BER of 10^{-4}, the simulation results show that the proposed MD-PSM scheme outperforms the conventional PSM by about 17.3 dB and 12.4 dB, while achieving the same and double the spectral efficiency, respectively. Also, due to the distributed nature of MDPSM, it is shown that the diversity order of the novel MD-PSM scheme is twice that of the conventional PSM.Comment: 9 pages, 6 figures, 3 tables (Journal of Communications and Networks), accepted on 2017, September 1

Mitigating the ICA Attack against Rotation Based Transformation for Privacy Preserving Clustering

The rotation based transformation (RBT) for privacy preserving data mining (PPDM) is vulnerable to the independent component analysis (ICA) attack. This paper introduces a modified multiple rotation based transformation (MRBT) technique for special mining applications mitigating the ICA attack while maintaining the advantages of the RBT.Comment: 3 pages, 1 figure, appeared as a letter in ETRI journa

Privacy Preserving Association Rule Mining Revisited

The privacy preserving data mining (PPDM) has been one of the most interesting, yet challenging, research issues. In the PPDM, we seek to outsource our data for data mining tasks to a third party while maintaining its privacy. In this paper, we revise one of the recent PPDM schemes (i.e., FS) which is designed for privacy preserving association rule mining (PP-ARM). Our analysis shows some limitations of the FS scheme in term of its storage requirements guaranteeing a reasonable privacy standard and the high computation as well. On the other hand, we introduce a robust definition of privacy that considers the average case privacy and motivates the study of a weakness in the structure of FS (i.e., fake transactions filtering). In order to overcome this limit, we introduce a hybrid scheme that considers both privacy and resources guidelines. Experimental results show the efficiency of our proposed scheme over the previously introduced one and opens directions for further development.Comment: 15 pages, to appear in proceeding of WISA 200

Fixed-complexity Sphere Encoder for Multi-user MIMO Systems

In this paper, we propose a fixed-complexity sphere encoder (FSE) for multi-user MIMO (MU-MIMO) systems. The proposed FSE accomplishes a scalable tradeoff between performance and complexity. Also, because it has a parallel tree-search structure, the proposed encoder can be easily pipelined, leading to a tremendous reduction in the precoding latency. The complexity of the proposed encoder is also analyzed, and we propose two techniques that reduce it. Simulation and analytical results demonstrate that in a 4 by 4 MU-MIMO system, the proposed FSE requires only 11.5% of the computational complexity needed by the conventional QRD-M encoder (QRDM-E). Also, the encoding throughput of the proposed encoder is 7.5 times that of the QRDM-E with tolerable degradation in the BER performance, while achieving the optimum diversity order.Comment: 7 pages, 7 figures. Accepted by Journal of Communications and Network

On Transmit Antenna Selection for Multiuser MIMO Systems with Dirty Paper Coding

In this paper, we address the transmit antenna selection in multi-user MIMO systems with precoding. The optimum and reduced complexity sub-optimum antenna selection algorithms are introduced. QR-decomposition (QRD) based antenna selection is investigated and the reason behind its sub-optimality is analytically derived. We introduce the conventional QRD-based algorithm and propose an efficient QRD-based transmit antenna scheme (maxR) that is both implementation and performance efficient. Moreover, we derive explicit formulae for the computational complexities of the aforementioned algorithms. Simulation results and analysis demonstrate that the proposed maxR algorithm requires only 1% of the computational efforts required by the optimal algorithm for a degradation of 1dB and 0.1dB in the case of linear zero-forcing and Tomlinson-Harashima precoding schemes, respectively.Comment: 5 pages, 6 figures, 1 table, [The 20th Personal, Indoor and Mobile Radio Communications Symposium 2009 (PIMRC-09)

Maximum-likelihood co-channel interference cancellation with power control for cellular OFDM networks

In cellular Orthogonal Frequency Division Multiplexing (OFDM) networks, Co-Channel Interference (CCI) leads to severe degradation in the BER performance. To solve this problem, Maximum-Likelihood Estimation (MLE) CCI cancellation scheme has been proposed in the literature. MLE CCI cancellation scheme generates weighted replicas of the transmitted signals and selects replica with the smallest Euclidean distance from the received signal. When the received power of the desired and interference signals are nearly the same, the BER performance is degraded. In this paper, we propose an improved MLE CCI canceler with closed-loop Power Control (PC) scheme capable of detecting and combating against the equal received power situation at the Mobile Station (MS) receiver by using the newly introduced parameter Power Ratio (PR). At cell edge where Signal to Interferer Ratio (SIR) is considered to have average value between -5 and 10 dB, computer simulations show that the proposed closed-loop PC scheme has a gain of 7 dB at 28 km/h and about 2 dB at 120 km/h.Comment: 5 pages, 9 figures, International Symposium on Communications and Information Technologies 200

Augmented Rotation-Based Transformation for Privacy-Preserving Data Clustering

Multiple rotation-based transformation (MRBT) was introduced recently for mitigating the apriori-knowledge independent component analysis (AK-ICA) attack on rotation-based transformation (RBT), which is used for privacy-preserving data clustering. MRBT is shown to mitigate the AK-ICA attack but at the expense of data utility by not enabling conventional clustering. In this paper, we extend the MRBT scheme and introduce an augmented rotation-based transformation (ARBT) scheme that utilizes linearity of transformation and that both mitigates the AK-ICA attack and enables conventional clustering on data subsets transformed using the MRBT. In order to demonstrate the computational feasibility aspect of ARBT along with RBT and MRBT, we develop a toolkit and use it to empirically compare the different schemes of privacy-preserving data clustering based on data transformation in terms of their overhead and privacy.Comment: 11 pages, 11 figures, and 6 table

On the achievable improvement by the linear minimum mean square error detector

Linear minimum mean square error (MMSE) detector has been shown to alleviate the noise amplification problem, resulting in the conventional zero-forcing (ZF) detector. In this paper, we analyze the performance improvement by the MMSE detector in terms of the condition number of its filtering matrix, and in terms of the post-precessing signal to noise ratio (SNR) improvement. To this end, we derive explicit formulas for the condition numbers of the filtering matrices and the post-processing SNRs. Analytical and simulation results demonstrate that the improvement achieved by the MMSE detector over the ZF detector is not only dependent on the noise variance and the condition number of the channel matrix, but also on how close the smallest singular values are to the noise variance.Comment: 5 pages, 6 figures, 1 table, International Symposium on Communications and Information Technologies 200