The reputation-based majority-voting approach is a promising solution for detecting malicious workers in a cloud system. However, this approach has a drawback in that it can detect malicious workers only when the number of colluders make up no more than half of all workers. In this paper, we simulate the behavior of a reputation-based method and mathematically analyze its accuracy. Through the analysis, we observe that, regardless of the number of colluders and their collusion probability, if the reputation value of a group is significantly different from those of other groups, it is a completely honest group. Based on the analysis result, we propose a new method for distinguishing honest workers from colluders even when the colluders make up the majority group. The proposed method constructs groups based on their reputations. A group with the significantly highest or lowest reputation value is considered a completely honest group. Otherwise, honest workers are mixed together with colluders in a group. The proposed method accurately identifies honest workers even in a mixed group by comparing each voting result one by one. The results of a security analysis and an experiment show that our method can identify honest workers much more accurately than a traditional reputation-based approach with little additional computational overhead.

A novel rendering algorithm with a best-matching patch is proposed to address the noise artifacts associated with Monte Carlo renderings. First, in the sampling stage, the representative patch is selected through a modified patch shift procedure, which gathers homogeneous pixels together to stay clear of the edges. Second, each pixel is filtered over a discrete set of filters, where the range kernel is computed using the selected patches. The difference between the selected patch and the filtered value is used as the pixel error, and the single filter that returns the smallest estimated error is chosen. In the reconstruction stage, pixel colors are combined with features of depth, normal and texture to form a cross bilateral filter, which highly preserves scene details while effectively removing noise. Finally, a heuristic metric is calculated to allocate additional samples in difficult regions. Compared with state-of-the art methods, the proposed algorithm performs better both in visual image quality and numerical error.

In lighting control systems, accurate data of artificial light (lighting coefficients) are essential for the illumination control accuracy and energy saving efficiency. This research proposes a novel Lambertian-Radial Basis Function Neural Network (L-RBFNN) to realize modeling of both lighting coefficients and the illumination environment for an office. By adding a Lambertian neuron to represent the rough theoretical illuminance distribution of the lamp and modifying RBF neurons to regulate the distribution shape, L-RBFNN successfully solves the instability problem of conventional RBFNN and achieves higher modeling accuracy. Simulations of both single-light modeling and multiple-light modeling are made and compared with other methods such as Lambertian function, cubic spline interpolation and conventional RBFNN. The results prove that: 1) L-RBFNN is a successful modeling method for artificial light with imperceptible modeling error; 2) Compared with other existing methods, L-RBFNN can provide better performance with lower modeling error; 3) The number of training sensors can be reduced to be the same with the number of lamps, thus making the modeling method easier to apply in real-world lighting systems.

This paper presents a new approach for circuit matching using signatures. We have defined a signature based on topology of the fanin cones of the circuit elements. Given two circuits, first we find all the circuit elements with unique signature between the two input circuits. After that, we try to expand the matching area by our expansion rules as much as possible. We iteratively find the unique matches and expand the matching area until no further matching is possible. Our experiments on IWLS2005 benchmark suite show that our method is able to find the perfect matching between two 160,000-gate IP in 5 minutes. In addition, our method is more than one order of magnitude faster than our previous signature-based matching method, while the size of the matched area is comparable or larger.

We present a rebound attack on the 4-branch type-2 generalized Feistel structure with an SPS round function, which is called the type-2 GFN-SPS in this paper. Applying a non-full-active-match technique, we construct a 6-round known-key truncated differential distinguisher, and it can deduce a near-collision attack on compression functions of this structure embedding the MMO or MP modes. Extending the 6-round attack, we build a 7-round truncated differential path to get a known-key differential distinguisher with seven rounds. The results give some evidences that this structure is not stronger than the type-2 GFN with an SP round function and not weaker than that with an SPSP round function against the rebound attack.

This paper presents a novel defense scheme for DDoS attacks that uses an image processing method. This scheme especially focused on the prevalence of adjacent neighbor spoofing, called subnet spoofing. It is rarely studied and there is few or no feasible approaches than other spoofing attacks. The key idea is that a “DDoS attack with IP spoofing” is represented as a specific pattern such as a “line” on the spatial image planes, which can be recognized through an image processing technique. Applying the clustering technique to the lines makes it possible to identify multiple attack source networks simultaneously. For the identified networks in which the zombie hosts reside, we then employ a signature-based pattern extraction algorithm, called a pivoted movement, and the DDoS attacks are filtered by correlating the IP and media access control pairing signature. As a result, this proposed scheme filters attacks without disturbing legitimate traffic. Unlike previous IP traceback schemes such as packet marking and path fingerprinting, which try to diagnose the entire attack path, our proposed scheme focuses on identifying only the attack source. Our approach can achieve an adaptive response to DDoS attacks, thereby mitigating them at the source, while minimizing the disruption of legitimate traffic. The proposed scheme is analyzed and evaluated on the IPv4 and IPv6 network topology from CAIDA, the results of which show its effectiveness.

Recently, multi-user multiple-input multiple-output (MU-MIMO) systems are being widely studied. For interference cancellation, MU-MIMO commonly uses spatial precoding techniques. These techniques, however, require the transmitters to have perfect knowledge of the downlink channel state information (CSI), which is hard to achieve in high mobility environments. Instead of spatial precoding, a collaborative interference cancellation (CIC) technique can be implemented for these environments. In CIC, mobile stations (MSs) collaborate and share their received signals to increase the demultiplexing capabilities. To obtain efficient signal-exchange between collaborating users, signal selection can be implemented. In this paper, a signal selection scheme suitable for a QRM-MLD algorithm is proposed. The proposed scheme uses the minimum Euclidean distance criterion to obtain an optimum bit error rate (BER) performance. Numerical results obtained through computer simulations show that the proposed scheme is able to provide BER performance near to that of MLD even when the number of candidates in QRM-MLD is relatively small. In addition, the proposed scheme is feasible to implement owing to its low computational complexity.

This paper describes, for the first time, the circuit design considerations and measurements of core building blocks that support a 1.9-GHz-band (Band I) BiFET MMIC three-power-mode power amplifier (PA) for WCDMA handset applications. The blocks are a reference voltage (Vref) generator, a control logic circuit, and ESD protection circuits. Our proposed Vref-generator, based on a current-mirror topology, can successfully suppress Vref variation against threshold voltage (Vth) dispersion in the FET as well as current gain dispersion in the HBT. On-wafer measurements over several wafer lots show that the standard deviation of Vref is as small as 18 mV over a Vth dispersion range from -0.6 V to -1.0 V. As a result, the measured quiescent current dispersion in the HPM is also suppressed to less than 5.4 mA, despite the fact that the average quiescent current is relatively high, at 81.3 mA. Several simulations reveal that small decoupling capacitances of approximately 1 pF added to the gate control lines of RF switch FETs ensure stable operation of the control logic even if an undesired RF coupling is present between an RF signal path and the gate lines. An empirical and useful design approach for ESD protection using HBT base-collector diodes allows easy and precise estimation of the HBM ESD robustness. With the above building blocks, a 3 mm × 3 mm PA was designed and fabricated by an in-house BiFET process. Measurements conducted under the conditions of a 3.4-V supply voltage and a 1.95-GHz WCDMA modulated signal are as follows. The PA delivers a 28.3-dBm output power (Pout), a 28.2-dB power gain (Gp), and 40% PAE while restricting the ACLR1 to less than -42 dBc in the HPM. In the MPM, 17.4 dBm of Pout, 15.9 dB of Gp, and 25.3% of PAE are obtained, while in the LPM, the PA delivers 7 dBm of Pout, 11.7 dB of Gp, and 13.9% of PAE. The HBM ESD robustness is 2 kV.

With the increase of network components connected to the Internet, the need to ensure secure connectivity is becoming increasingly vital. Intrusion Detection Systems (IDSs) are one of the common security components that identify security violations. This paper proposes a novel multilevel hybrid classifier that uses different feature sets on each classifier. It presents the Discernibility Function based Feature Selection method and two classifiers involving multilayer perceptron (MLP) and decision tree (C4.5). Experiments are conducted on the KDD'99 Cup and ISCX datasets, and the proposal demonstrates better performance than individual classifiers and other proposed hybrid classifiers. The proposed method provides significant improvement in the detection rates of attack classes and Cost Per Example (CPE) which was the primary evaluation method in the KDD'99 Cup competition.

Recently, high-level synthesis techniques for FPGA designs (FPGA-HLS techniques) are strongly required in various applications. Both interconnection delays and clock skews have a large impact on circuit performance implemented onto FPGA, which indicates the need for floorplan-driven FPGA-HLS algorithms considering them. To appropriately estimate interconnection delays and clock skews at HLS phase, a reasonable model to estimate them becomes essential. In this paper, we demonstrate several experiments to characterize interconnection delays and clock skews in FPGA and propose novel estimate models called “IDEF” and “CSEF”. In order to evaluate our models, we integrate them into a conventional floorplan-driven FPGA-HLS algorithm. Experimental results demonstrate that our algorithm can realize FPGA designs which reduce the latency by up to 22% compared with conventional approaches.

This paper proposes a new design formula of coupling coefficient between antenna and resonator for an efficient design of filtering antennas consisting of an antenna and resonators. The filtering antenna can be designed by introducing a well-established filter design theory. For such a design approach, an external Q factor at input port, coupling coefficients, and a radiation Q factor of the antenna need to be evaluated. However, conventional design methods have a time-consuming procedure, since there are no effective techniques to evaluate the coupling coefficient between resonator and antenna. To solve the problem, we derive the new design formula using only amplitude property of input reflection responses obtained from a coupled structure of resonator and antenna. As an example, a third-order filtering antenna is synthesized, designed, and tested at 2.45 GHz, which numerically and experimentally validates the effectiveness of the derived equation.

In this letter, a novel robust adaptive beamforming algorithm is addressed to improve the robustness against steering vector random errors (SVREs), which eliminates the signal of interest (SOI) component from the sample covariance matrix (SCM), based on interference-plus-noise covariance matrix (IPNCM) reconstruction over annulus uncertainty sets. Firstly, several annulus uncertainty sets are used to constrain the steering vectors (SVs) of both interferences and the SOI. Additionally the IPNCM is reconstructed according to its definition by estimating each interference SV over its own annulus uncertainty set via the subspace projection algorithm. Meanwhile, the SOI SV is estimated as the prime eigenvector of the SOI covariance matrix term calculated over its own annulus uncertainty set. Finally, a novel robust beamformer is formulated based on the new IPNCM and the SOI SV, and it outperforms other existing reconstruction-based beamformers when the SVREs exist, especially in low input signal-to-noise ratio (SNR) cases, which is proved through the simulation results.

This paper presents a 60 GHz analog/digital beamforming receiver that effectively suppresses interference signals, targeting the IEEE 802.11ad/WiGig standard. Combining two-stream analog frontends with interference rejection digital signal processing, the analog beamforming steers the antenna beam to the desired direction while the digital beamforming provides gain suppression in the interference direction. A prototype has been built with 40 nm CMOS analog frontends as well as offline baseband digital signal processing. Measurements show a 3.1 dB EVM advantage over conventional two-stream diversity during a packet collision situation.

A novel resilient coarse granularity optical routing network architecture that adopts finely granular protection and finely granular add/drop is presented. The routing scheme defines optical pipes such that multiple optical paths can be carried by each pipe and can be dropped or added at any node on the route of a pipe. The routing scheme also makes it possible to enhance frequency utilization within pipes, by denser path packing in the frequency domain, as we recently verified. We develop a static network design algorithm that simultaneously realizes the independence of working and backup paths and pipe location optimization to efficiently carry these paths. The design algorithm first sequentially accommodates optical paths into the network, then tries to eliminate sparsely utilized fibers and iteratively optimizes frequency slot/wavelength assignment in each coarse granular pipe so as to limit the impairment caused by dropping the optical paths adjacent in the frequency domain. Numerical experiments elucidate that the number of fibers in a network can be reduced by up to 20% for 400Gbps channels without any modification in hardware.

A parallel Aho-Corasick (AC) approach, named PAC-k, is proposed for string matching in deep packet inspection (DPI). The proposed approach adopts graphic processing units (GPUs) to perform the string matching in parallel for high throughput. In parallel string matching, the boundary detection problem happens when a pattern is matched across chunks. The PAC-k approach solves the boundary detection problem because the number of characters to be scanned by a thread can reach the longest pattern length. An input string is divided into multiple sub-chunks with k characters. By adopting the new starting position in each sub-chunk for the failure transition, the required number of threads is reduced by a factor of k. Therefore, the overhead of terminating and reassigning threads is also decreased. In order to avoid the unnecessary overlapped scanning with multiple threads, a checking procedure is proposed that decides whether a new starting position is in the sub-chunk. In the experiments with target patterns from Snort and realistic input strings from DEFCON, throughputs are enhanced greatly compared to those of previous AC-based string matching approaches.

In order to tackle a process-variation problem, we can define several scenarios, each of which corresponds to a particular LSI behavior, such as a typical-case scenario and a worst-case scenario. By designing a single LSI chip which realizes multiple scenarios simultaneously, we can have a process-variation-tolerant LSI chip. In this paper, we propose a multi-scenario high-level synthesis algorithm for variation-tolerant floorplan-driven design targeting new distributed-register architectures, called HDR architectures. We assume two scenarios, a typical-case scenario and a worst-case scenario, and realize them onto a single chip. We first schedule/bind each of the scenarios independently. After that, we commonize the scheduling/binding results for the typical-case and worst-case scenarios and thus generate a commonized area-minimized floorplan result. At that time, we can explicitly take into account interconnection delays by using distributed-register architectures. Experimental results show that our algorithm reduces the latency of the typical-case scenario by up to 50% without increasing the latency of the worst-case scenario, compared with several existing methods.

In interactive audio services, users can render audio objects rather freely to match their desires and the spatial audio object coding (SAOC) scheme is fairly good both in the sense of bitrate and audio quality. But rather perceptible audio quality degradation can occur when an object is suppressed or played alone. To complement this, the SAOC scheme with Two-Step Coding (SAOC-TSC) was proposed. But the bitrate of the side information increases two times compared to that of the original SAOC due to the bitrate needed for the residual coding used to enhance the audio quality. In this paper, an efficient residual coding method of the SAOC-TSC is proposed to reduce the side information bitrate without audio quality degradation or complexity increase.

The bug reports expressed in natural language text usually suffer from vast, ambiguous and poorly written, which causes the challenge to the duplicate bug reports detection. Current automatic duplicate bug reports detection techniques have mainly focused on textual information and ignored some useful factors. To improve the detection accuracy, in this paper, we propose a new approach calls LNG (LDA and N-gram) model which takes advantages of the topic model LDA and word-based model N-gram. The LNG considers multiple factors, including textual information, semantic correlation, word order, contextual connections, and categorial information, that potentially affect the detection accuracy. Besides, the N-gram adopted in our LNG model is improved by modifying the similarity algorithm. The experiment is conducted under more than 230,000 real bug reports of the Eclipse project. In the evaluation, we propose a new evaluation metric, namely exact-accuracy (EA) rate, which can be used to enhance the understanding of the performance of duplicates detection. The evaluation results show that all the recall rate, precision rate, and EA rate of the proposed method are higher than treating them separately. Also, the recall rate is improved by 2.96%-10.53% compared to the state-of-art approach DBTM.

In this letter, we propose a novel garbage collection technique for index structures based on flash memory systems, called Proxy Block-based Garbage Collection (PBGC). Many index structures have been proposed for flash memory systems. They exploit buffers and logs to resolve the update propagation problem, one of the a main cause of performance degradation of the index structures. However, these studies overlooked the fact that not only the record operation but also garbage collection induces the update propagation problem. The proposal, PBGC, exploits a proxy block and a block mapping table to solve the update propagation problem, which is caused by the changes in the page and block caused by garbage collection. Experiments show that PBGC decreased the execution time of garbage collection by up to 39%, compared with previous garbage collection techniques.

Performance evaluation of an improved multiband impulse radio ultra-wideband (MIR UWB) system based on sub-band selection is proposed in this paper. In the improved scheme, a data mapping algorithm is introduced to a conventional MIR UWB system, and out of all the sub-bands, only partial ones are selected to transmit information data, which can improve the flexibility of sub-bands/spectrum allocation, avoid interference and provide a variety of data rates. Given diagrams of a transmitter and receiver, the exact bit error rate (BER) of the improved system is derived. A comparison of system performance between the improved MIR UWB system and the conventional MIR UWB system is presented in different channels. Simulation results show that the improved system can achieve the same data rate and better BER performance than the conventional MIR UWB system under additive white Gaussian noise (AWGN), multipath fading and interference coexistence channels. In addition, different data transmission rates and BER performances can be easily achieved by an appropriate choice of system parameters.