A botnet attacks any Victim Hosts via the multiple Command and Control (C&C) Servers, which are controlled by a botmaster. This makes it more difficult to detect the botnet attacks and harder to trace the source country of the botmaster due to the lack of the logged data about the attacks. To locate the C&C Servers during malware/bot downloading phase, we have analyzed the source IP addresses of downloads to more than 90 independent Honeypots in Japan in the CCC (Cyber Clean Center) dataset 2010 comprising over 1 million data records and almost 1 thousand malware names. Based on GeoIP services, a Time Zone Correlation model has been proposed to determine the correlation coefficient between bot downloads from Japan and other source countries. We found a strong correlation between active malware/bot downloads and time zone of the C&C Servers. As a result, our model confirms that malware/bot downloads are synchronized with time zone (country) of the corresponding C&C Servers so that the botmaster can be possibly traced.

In this paper, we propose a step size control method capable of quickly canceling acoustic echo even when double talk continues from the echo path change. This method controls the step size by substituting the norm of the difference vector between the coefficient vectors of a main adaptive filter (Main-ADF) and a sub-adaptive filter (Sub-ADF) for the estimation error provided by the former. Actually, the number of taps of Sub-ADF is limited to a quarter of that of Main-ADF, and the larger step size than that applied to Main-ADF is given to Sub-ADF; accordingly the norm of the difference vector quickly approximates to the estimation error. The estimation speed can be improved by utilizing the norm of the difference vector for the step size control in Main-ADF. We show using speech signals that in single talk the proposed method can provide almost the same estimation speed as the method whose step size is fixed at the optimum one and verify that even in double talk the estimation error, quickly decreases.

Large-scale introduction of renewable energy such as photovoltaic energy and wind is a big motivation for renovating conventional grid systems. To be independent from existing power grids and to use renewable energy as much as possible, a decentralized energy network is proposed as a new grid system. The decentralized energy network is placed among houses to connect them with each other, and each house has a PV panel and a battery. A contribution of this paper is a network topology and battery size exploration for the decentralized energy network in order to make effective use of renewable energy. The proposed method for exploring the decentralized energy network design is inspired by the design methodology of VLSI systems, especially design space exploration in system-level design. The proposed method is based on mixed integer programming (MIP) base power flow optimization, and it was evaluated for all design instances. Experimental results show that the decentralized energy network has the following features. 1) The energy loss and energy purchased due to power shortage were not affected by each battery size but largely affected by the sum of all battery sizes in the network, and 2) the network topology did not largely affect the energy loss and the purchased energy. These results will become a useful guide to designing an optimal decentralized energy network for each region.

Discrete structures are foundational material for computer science and mathematics, which are related to set theory, symbolic logic, inductive proof, graph theory, combinatorics, probability theory, etc. Many problems solved by computers can be decomposed into discrete structures using simple primitive algebraic operations. It is very important to represent discrete structures compactly and to execute efficiently tasks such as equivalency/validity checking, analysis of models, and optimization. Recently, BDDs (Binary Decision Diagrams) and ZDDs (Zero-suppressed BDDs) have attracted a great deal of attention, because they efficiently represent and manipulate large-scale combinational logic data, which are the basic discrete structures in various fields of application. Although a quarter of a century has passed since Bryant's first idea, there are still a lot of interesting and exciting research topics related to BDD and ZDD. BDD/ZDD is based on in-memory data processing techniques, and it enjoys the advantage of using random access memory. Recent commodity PCs are equipped with gigabytes of main memory, and we can now solve large-scale problems which used to be impossible due to memory shortage. Thus, especially since 2000, the scope of BDD/ZDD methods has increased. This survey paper describes the history of, and recent research activity pertaining to, techniques related to BDD and ZDD.

The 10-gigabit Ethernet passive optical network (10G-EPON) is a promising candidate for the next generation of fiber-to-the-home access systems. In the symmetric 10G-EPON system, the gigabit Ethernet passive optical network (GE-PON) and 10G-EPON will have to co-exist on the same optical network. For this purpose, an optical triplexer (10G-transmitter, 1G-transmitter, and 10G/1G-receiver) for optical line terminal (OLT) transceivers in 10G/1G co-existing EPON systems has been developed. Reducing the size and cost of the optical triplexer has been one of the largest issues in the effort to deploy 10G-EPON systems for practical use. In this paper, we describe a novel small and low-cost dual-rate optical triplexer for use in 10G-EPON applications. By reducing the optical path length by means of a light collection system with a low-magnification long-focus coupling lens, we have successfully miniaturized the optical triplexer for use in 10G-EPON OLT 10-gigabit small form factor pluggable (XFP) transceivers and decreased the number of lenses. A low-cost design of sub-assemblies also contributes to cost reduction. The triplexer's performance complies with IEEE 802.3av specifications.

Feature selection is a technique to screen out less important features. Many existing supervised feature selection algorithms use redundancy and relevancy as the main criteria to select features. However, feature interaction, potentially a key characteristic in real-world problems, has not received much attention. As an attempt to take feature interaction into account, we propose 1-LSMI, an 1-regularization based algorithm that maximizes a squared-loss variant of mutual information between selected features and outputs. Numerical results show that 1-LSMI performs well in handling redundancy, detecting non-linear dependency, and considering feature interaction.

The optimization of polarimetric contract enhancement (OPCE) is one of the important problems in radar polarimetry since it provides a substantial benefit for target enhancement. Considering different scattering mechanisms between the desired targets and the undesired targets, Yang et al. extended the OPCE model to the generalized OPCE (GOPCE) problem. Based on a modified GOPCE model and the linear discriminant analysis, a ship detector is proposed in this paper to improve the detection performance for polarimetric Synthetic Aperture Radar (SAR) imagery. In the proposed method, we modify the combination form of the three polarimetric parameters (i.e., the plane scattering similarity parameter, the diplane scattering similarity parameter and the Cloude entropy), then use an optimization function resembling the classical Fisher criterion to optimize the optimal polarization states corresponding to the radar received power and the fusion vector corresponding to the polarimetric parameters. The principle of the optimization detailed in this paper lies in maximizing the difference between the desired targets and sea clutter, and minimizing the clutter variance at the same time. RADARSAT-2 polarimetric SAR data acquired over Tanggu Port (Tianjin, China) on June 23, 2011 are used for validation. The experimental results show that the proposed method improves the contrast of the targets and sea clutter and meanwhile reduces the clutter variance. In comparison to another GOPCE based ship detector and the classical polarimetric whitening filter (PWF), the proposed method shows a better performance for weak targets. In addition, we also use the RADARSAT-2 data acquired over San-Francisco on April 9, 2008 to further demonstrate the improvement of this method for target contrast.

This paper proposes a device discovery method for consolidated IP and ZigBee home networks. The method broadcasts an IP multicasted device discovery request of UPnP, m-search, in the ZigBee network as a Constrained Application Protocol (CoAP) message. Upon receiving the m-search broadcast, ZigBee devices respond after a constant time delay with their device description Universal Resource Name (URN). We refer to this device discovery mechanism as transparent msearch. Transparent m-search enables reliable and swift device discovery in home networks which may include constrained networks such as ZigBee. It is revealed by an experiment with 41 ZigBee devices that the delayed response from ZigBee devices is essential to avoid collisions between m-search broadcast and responses from devices and, as a result, to secure the reliability of device discovery. Since the transparent m-search requires the receiving ZigBee devices to respond with their device description URNs, the execution time of device discovery is significantly improved. In our experiment with 41 ZigBee devices, a conventional m-search took 38.1 second to complete device discovery while that of transparent m-search took only 6.3 second.

The simple repetitive control system proposed by Yamada et al. is a type of servomechanism for periodic reference inputs. This system follows a periodic reference input with a small steady-state error, even if there is periodic disturbance or uncertainty in the plant. In addition, simple repetitive control systems ensure that transfer functions from the periodic reference input to the output and from the disturbance to the output have finite numbers of poles. Yamada et al. clarified the parameterization of all stabilizing simple repetitive controllers. Recently, Yamada et al. proposed the parameterization of all stabilizing two-degrees-of-freedom (TDOF) simple repetitive controllers that can specify the input-output characteristic and the disturbance attenuation characteristic separately. However, when using the method of Yamada et al., it is complex to specify the low-pass filter in the internal model for the periodic reference input that specifies the frequency characteristics. This paper extends the results of Yamada et al. and proposes the parameterization of all stabilizing TDOF simple repetitive controllers with specified frequency characteristics in which the low-pass filter can be specified beforehand.

We consider the problem of detecting and localizing of link quality degradations in transparent wavelength division multiplexing (WDM) networks. In particular, we consider the degradation of the optical signal-to-noise ratio (OSNR), which is a key parameter for link quality monitoring in WDM networks. With transparency in WDM networks, transmission lightpaths can bypass electronic processing at intermediate nodes. Accordingly, links cannot always be monitored by receivers at their end nodes. This paper proposes the use of optical multicast probes to monitor OSNR degradations on optical links. The proposed monitoring scheme consists of two steps. The first step is an off-line process to set up monitoring trees using integer linear programming (ILP). The set of monitoring trees is selected to guarantee that significant OSNR degradations can be identified on any link or links in the network. The second step uses optical performance monitors that are placed at the receivers identified in the first step. The information from these monitors is collected and input to the estimation algorithm to localize the degraded links. Numerical results indicate that the proposed monitoring algorithm is able to detect link degradations that cause significant OSNR changes. In addition, we demonstrate how the information obtained from monitoring can be used to detect a significant end-to-end OSNR degradation even though there is no significant OSNR degradation on individual links.

In this paper, we propose an identity-based authenticated key exchange (ID-AKE) protocol that is secure in the identity-based extended Canetti-Krawczyk (id-eCK) model in the random oracle model under the gap Bilinear Diffie-Hellman assumption. The proposed ID-AKE protocol is the most efficient among the existing ID-AKE protocols that is id-eCK secure, and it can be extended to use in asymmetric pairing.

We have developed a dedicated onboard “sensor” utilizing wireless communication devices for collision avoidance around road intersections. The “sensor” estimates the positions of transmitters on traffic participants by comparing the strengths of signals received by four ZigBee receivers installed at the four corners of a vehicle. On-board sensors involving cameras cannot detect objects in non line-of-sight (NLOS) area caused by buildings and other vehicles. Although infrastructure sensors for vehicle-to-infrastructure (V2I) cooperative systems can detect such hidden objects, they are substantially more expensive than on-board sensors. The on-board wireless “sensor” developed in this work would function as an alternative tool for collision avoidance around intersections. Herein, we extend our previous work by considering a road surface reflection model to improve the estimation accuracy. By using this model, we succeeded in reducing the error mismatches between the observed data and the calibration data of the estimation algorithm. The proposed system will be realized on the basis of these enhancements.

As wireless LAN systems become more widespread, the number of access points (APs) is increasing. A large number of APs cause overlapping cells where nearby cells utilize the same frequency channel. In the overlapping cells, inter-cell interference (ICI) degrades the throughput. This paper proposes an interference-aware multi-cell beamforming (IMB) technique to reduce the throughput degradation in the overlapping cells. The IMB technique improves transmission performance better than conventional multi-cell beamforming based on a decentralized control scheme. The conventional technique mitigates ICI by nullifying all the interference signal space (ISS) by beamforming, but the signal spaces to the user terminal (UT) is also limited because the degree of freedom (DoF) at the AP is limited. On the other hand, the IMB technique increases the signal space to the UT because the DoF at the AP is increased by selecting the ISS by allowing a small amount of ICI. In addition, we introduce a method of selecting the ISS in a decentralized control scheme. In our work, we analyze the interference channel state information (CSI) and evaluate the transmission performance of the IMB technique by using a measured CSI in an actual indoor environment. As a result, we find that the IMB technique becomes more effective as the number of UT antennas in nearby cells increases.

In LTE-Advanced heterogeneous networks, a typical cell layout to enhance frequency utilization is to incorporate picocells and femtocells in a macrocell. However, the co-channel interference between the marcocell and picocell/femtocell is an important issue when the same frequency band is used between these systems. We have already clarified how the interference from the femto(macro) cell affects on the macro(femto) cell. In this paper, we evaluate the interference rejection characteristics by an adaptive array with user equipment (UE). The characteristics are evaluated based on the K-factor used in the Nakagami-Race Fading model and the spatial correlation that is obtained in an actual outdoor environment. It is shown that a two-element adaptive array at the macro UE (M-UE) can sufficiently reduce the interference from the femto base station (F-BS) to the M-UE even if the number of total signals exceeds the degrees of freedom of the array.

Given a simple connected graph G with n vertices, the spanning tree problem involves finding a tree that connects all the vertices of G. Solutions to this problem have applications in electrical power provision, computer network design, circuit analysis, among others. It is known that highly efficient sequential or parallel algorithms can be developed by restricting classes of graphs. Circular trapezoid graphs are proper superclasses of trapezoid graphs. In this paper, we propose an O(n) time algorithm for the spanning tree problem on a circular trapezoid graph. Moreover, this algorithm can be implemented in O(log n) time with O(n/log n) processors on EREW PRAM computation model.

This paper proposes a reduced-complexity multiband multiple-input multiple-output (MIMO) receiver that can be used in cognitive radios. The proposed receiver uses heterodyne reception implemented with a wide-passband band-pass filter in the radio frequency (RF) stage. When an RF Hilbert transformer is utilized in the receiver, image-band interference occurs because of the transformer's imperfections. Thus, the imperfection of the Hilbert transformer is corrected in the intermediate frequency (IF) stage to reduce the hardware complexity. First, the proposed receiver estimates the channel impulse response in the presence of the strong image-band interference signals. Next, the coefficients are calculated for the correction of the imperfection at the IF stage, and are fed back to the IF stage through a feedback loop. However, the imperfection caused by the digital-to-analog (D/A) converter and the baseband amplifier in the feedback loop corrupts the coefficients on the way back to the IF stage. Therefore, the proposed receiver corrects the imperfection of the analog devices in the feedback loop. The performance of the proposed receiver is verified by using computer simulations. The proposed receiver can maintain its performance even in the presence of strong image-band interference signals and imperfection of the analog devices in the feedback loop. In addition, this paper also reveals the condition for rapid convergence.

In this paper, 1) it is shown that amplitude-only images (AOIs) have quite wide intensity ranges (IRs), and 2) an IR reduction method for AOIs is proposed. An AOI is the inversely transformed amplitude spectra of an image, and it is used in the privacy- and copyright-protected image trading system because of its invisibility. Since an AOI is the coherent summation of cosine waves with the same phase, the IR of the AOI is too large to be stored and/or transmitted. In the proposed method, random signs are applied to discrete Fourier transformed amplitude coefficients to obtained AOIs with significantly lower IRs without distortion while keeping the invisibility of images. With reasonable processing time, high correct watermark extracting rates, inversely quantized AOIs with low mean squared errors, and reconstructed images with high peak signal-to-noise ratios are obtained by a linear quantizer in the proposed method.

This paper provides a novel normalized sign least-mean square (NSLMS) algorithm which updates only a part of the filter coefficients and simultaneously performs sparse updates with the goal of reducing computational complexity. A combination of the partial-update scheme and the set-membership framework is incorporated into the context of L∞-norm adaptive filtering, thus yielding computational efficiency. For the stabilized convergence, we formulate a robust update recursion by imposing an upper bound of a step size. Furthermore, we analyzed a mean-square stability of the proposed algorithm for white input signals. Experimental results show that the proposed low-complexity NSLMS algorithm has similar convergence performance with greatly reduced computational complexity compared to the partial-update NSLMS, and is comparable to the set-membership partial-update NLMS.

This paper examines two-pass authenticated key exchange (AKE) protocols that are secure without the NAXOS technique under the gap Diffie-Hellman assumption in the random oracle model: FHMQV [18], KFU1 [21], SMEN- [13], and UP [17]. We introduce two protocol, biclique DH protocol and multiplied biclique DH protocol, to analyze the subject protocols, and show that the subject protocols use the multiplied biclique DH protocol as internal protocols. The biclique DH protocol is secure, however, the multiplied biclique DH protocol is insecure. We show the relations between the subject protocols from the viewpoint of how they overcome the insecurity of the multiplied biclique DH protocol: FHMQV virtually executes two multiplied biclique DH protocols in sequence with the same ephemeral key on two randomized static keys. KFU1 executes two multiplied biclique DH protocols in parallel with the same ephemeral key. UP is a version of KFU1 in which one of the static public keys is generated with a random oracle. SMEN- can be thought of as a combined execution of two multiplied biclique DH protocols. In addition, this paper provides ways to characterize the AKE protocols and defines two parameters: one consists of the number of static keys, the number of ephemeral keys, and the number of shared secrets, and the other is defined as the total sum of these numbers. When an AKE protocol is constructed based on some group, these two parameters indicate the number of elements in the group, i.e., they are related to the sizes of the storage and communication data.

Scale-Invariant Feature Transform (SIFT) has lately attracted attention in computer vision as a robust keypoint detection algorithm which is invariant for scale, rotation and illumination changes. However, its computational complexity is too high to apply in practical real-time applications. This paper proposes a low complexity keypoint extraction algorithm based on SIFT descriptor and utilization of the database, and its real-time hardware implementation for Full-HD resolution video. The proposed algorithm computes SIFT descriptor on the keypoint obtained by corner detection and selects a scale from the database. It is possible to parallelize the keypoint detection and descriptor computation modules in the hardware. These modules do not depend on each other in the proposed algorithm in contrast with SIFT that computes a scale. The processing time of descriptor computation in this hardware is independent of the number of keypoints because its descriptor generation is pipelining structure of pixel. Evaluation results show that the proposed algorithm on software is 12 times faster than SIFT. Moreover, the proposed hardware on FPGA is 427 times faster than SIFT and 61 times faster than the proposed algorithm on software. The proposed hardware performs keypoint extraction and matching at 60 fps for Full-HD video.