A purpose of password-based anonymous authentication schemes is to provide not only password-based authentication but also user anonymity. In [19], Yang et al., proposed a password-based anonymous authentication scheme (we call it YZWB10 scheme) using the password-protected credentials. In this paper, we discuss user anonymity of the YZWB10 scheme [19] against a third-party attacker, who is much weaker than a malicious server. First, we show that a third-party attacker in the YZWB10 scheme can specify which user actually sent the login request to the server. This attack also indicates that the attacker can link different login requests to be sent later by the same user. Second, we give an effective countermeasure to this attack which does not require any security for storing users' password-protected credentials.

This letter presents a novel tensor voting mechanism — analytic tensor voting (ATV), to get rid of the difficulties in original tensor voting, especially the efficiency. One of the main advantages is its explicit voting formulations, which benefit the completion of tensor voting theory and computational efficiency. Firstly, new decaying function was designed following the basic spirit of decaying function in original tensor voting (OTV). Secondly, analytic stick tensor voting (ASTV) was formulated using the new decaying function. Thirdly, analytic plate and ball tensor voting (APTV, ABTV) were formulated through controllable stick tensor construction and tensorial integration. These make the each voting of tensor can be computed by several non-iterative matrix operations, improving the efficiency of tensor voting remarkably. Experimental results validate the effectiveness of proposed method.

In this letter, we propose a generalized quadrature spatial modulation technique (GQSM) which offers additional bits per channel use (bpcu) gains and a low complexity greedy detector algorithm, structured orthogonal matching pursuit (S-OMP)- GQSM, based on compressive sensing (CS) framework. Simulation results show that the bit error rate (BER) performance of the proposed greedy detector is very close to maximum likelihood (ML) and near optimal detectors based on convex programming.

By tracking the changing rate of hard decisions during every two consecutive iterations of the alternating direction method of multipliers (ADMM) penalized decoding, an efficient early termination (ET) criterion is proposed to improve the convergence rate of ADMM penalized decoder for low-density parity-check (LDPC) codes. Compared to the existing ET criterion for ADMM penalized decoding, the proposed method can reduce the average number of iterations significantly at low signal-to-noise ratios with negligible performance degradation.

A convenient formula for the estimation of the clutter rank of the diving platform radar is derived. Brennan's rule provides a general formula to estimate the clutter rank for the side looking radar with a linear array, which is normally called one-dimensional (1D) estimation problem. With the help of the clutter wavenumber spectrum, the traditional estimation of the clutter rank is extended to the diving scenario and the estimation problem is two-dimensional (2D). The proposed rule is verified by the numerical simulations.

The integration of VANETs with Internet is required if vehicles are to access IP-based applications. A vehicle must have an IP address, and the IP mobility service should be supported during the movement of the vehicle. VANET standards such as WAVE or C-ITS use IPv6 address auto configuration to allocate an IP address to a vehicle. In C-ITS, NEMO-BS is used to support IP mobility. The vehicle moves rapidly, so reallocation of IP address as well as binding update occurs frequently. The vehicle' communication, however, may be disrupted for a considerable amount of time, and the packet loss occurs during these events. Also, the finding of the home address of the peer vehicle is not a trivial matter. We propose a network based identifier locator separation scheme for VANETs. The scheme uses a vehicle identity based address generation scheme. It eliminates the frequent address reallocation and simplifies the finding of the peer vehicle IP address. In the scheme, a network entity tracks the vehicles in its coverage and the vehicles share the IP address of the network entity for their locators. The network entity manages the mapping between the vehicle's identifier and its IP address. The scheme excludes the vehicles from the mobility procedure, so a vehicle needs only the standard IPv6 protocol stack, and mobility signaling does not occur on the wireless link. The scheme also supports seamlessness, so packet loss is mitigated. The results of a simulation show that the vehicles experience seamless packet delivery.

The separating redundancy is an important concept in the analysis of the error-and-erasure decoding of a linear block code using a parity-check matrix of the code. In this letter, we derive new constructive upper bounds on the second separating redundancies of low-density parity-check (LDPC) codes constructed from projective and Euclidean planes over the field Fq with q even.

With the popularity of cloud computing services, outsourcing computation has entered a period of rapid development. Modular exponentiation is one of the most expensive operations in public key cryptographic systems, but the current outsourcing algorithms for modular exponentiations (MExps) with single server are inefficient or have small checkability. In this paper, we propose an efficient and fully verifiable algorithm for outsourcing multiple MExps with single untrusted server where the errors can be detected by an outsourcer with a probability of 1. The theory analysis and experimental evaluations also show that the proposed algorithm is the most efficient one compared with the previous work. Finally, we present the outsourcing schemes of digital signature algorithm (DSA) and attribute based encryption (ABE) as two applications of the proposed algorithm.

This paper presents experimental results of our proposed null-space expansion scheme for multiuser massive multiple-input multiple-output (MIMO) in time varying channels. Multiuser MIMO transmission with the proposed scheme can suppress the inter-user interference (IUI) caused by outdated channel state information (CSI). The excess degrees of freedom (DoFs) of massive MIMO is exploited to perform additional null-steering using past estimated CSI. The signal-to-interference power ratio (SIR) and spectral efficiency performances achieved by the proposed scheme that uses measured CSI is experimentally evaluated. It is confirmed that the proposed scheme shows performance superior to the conventional channel prediction scheme. In addition, IUI can be stably suppressed even in high mobility environments by further increasing the null-space dimension.

Cognitive radio (CR) is considered as the most promising solution to the so-called spectrum scarcity problem, in which channel sensing is an important problem. In this paper, the problem of determining the period of medium access control (MAC)-layer channel sensing in cognitive radio networks (CRNs) is studied. In our study, the channel state is statistically modeled as a continuous-time alternating renewal process (ARP) alternating between the OFF and ON states for the primary user (PU)'s communication activity. Based on the statistical ARP model, we analyze the CRNs with different SU MAC protocols, taking into consideration the effects of practical issues of imperfect channel sensing and non-negligible channel sensing time. Based on the analysis results, a constrained optimization problem to find the optimal sensing period is formulated and the feasibility of this problem is studied for systems with different OFF/ON channel state length distributions. Numerical results are presented to show the performance of the proposed sensing period optimization scheme. The effects of practical system parameters, including channel sensing errors and channel sensing time, on the performance and the computational complexity of the proposed sensing period optimization scheme are also investigated.

This paper proposes a sequentially iterative equalizer based on Kalman filtering and smoothing (SIEKFS) for multiple-input multiple-output (MIMO) systems under frequency selective fading channels. In the proposed SIEKFS, an iteration consists of sequentially executed subiterations, and each subiteration performs equalization and detection procedures of the symbols transmitted from a specific transmit antenna. During this subiteration, all available observations for the transmission block are utilized in the equalization procedures. Furthermore, the entire soft estimate of the desired symbols to be detected does not participate in the equalization procedures of the desired symbols, i.e., the proposed SIEKFS performs input-by-input equalization procedures for a priori information nulling. Therefore, compared with the original iterative equalizer based on Kalman filtering and smoothing, which performs symbol-by-symbol equalization procedures, the proposed SIEKFS can also perform iterative equalization based on the Kalman framework and turbo principle, with a significant reduction in computation complexity. Simulation results verify that the proposed SIEKFS achieves suboptimum error performance as the size of the antenna configuration and the number of iterations increase.

Malicious software (malware) poses various significant challenges. One is the need to retrieve plain-text messages transmitted between malware and herders through an encrypted network channel. Those messages (e.g., commands for malware) can be a useful hint to reveal their malicious activities. However, the retrieving is challenging even if the malware is executed on an analysis computer. To assist analysts in retrieving the plain-text from the memory, this paper presents FCReducer(Function Candidate Reducer), which provides a small candidate set of cryptographic functions called by malware. Given this set, an analyst checks candidates to locate cryptographic functions. If the decryption function is found, she then obtains its output as the plain-text. Although existing systems such as CipherXRay have been proposed to locate cryptographic functions, they heavily rely on fine-grained dynamic taint analysis (DTA). This makes them weak against under-tainting, which means failure of tracking data propagation. To overcome under-tainting, FCReducer conducts coarse-grained DTA and generates a typical data dependency graph of functions in which the root function accesses an encrypted message. This does not require fine-grained DTA. FCReducer then applies a community detection method such as InfoMap to the graph for detecting a community of functions that plays a role in decryption or encryption. The functions in this community are provided as candidates. With experiments using 12 samples including four malware specimens, we confirmed that FCReducer reduced, for example, 4830 functions called by Zeus malware to 0.87% as candidates. We also propose a heuristic to reduce candidates more greatly.

The rotating element electric field vector (REV) method is a classical measurement technique for phased array calibration. Compared with other calibration methods, it requires only power measurements. Thus, the REV method is more reliable for operating phased array calibration systems. However, since the phase of each element must be rotated from 0 to 2π, the conventional REV method requires a large number of measurements. Moreover, the power of composite electric field vector doesn't vary significantly because only a single element's phase is rotated. Thus, it can be easily degraded by the receiver noise. A simplified REV method combined with Hadamard group division is proposed in this paper. In the proposed method, only power measurements are required. All the array elements are divided into different groups according to the group matrix derived from the normalized Hadamard matrix. The phases of all the elements in the same group are rotated at the same time, and the composite electric field vector of this group is obtained by the simplified REV method. Hence, the relative electric fields of all elements can be obtained by a matrix equation. Compared with the conventional REV method, the proposed method can not only reduce the number of measurements but also improve the measurement accuracy under the particular range of signal to noise ratio(SNR) at the receiver, especially under low and moderate SNRs.

Ethernet passive optical network (EPON) is one of the energy-efficient access networks. Many studies have been done to reach maximum energy saving in the EPON. However, it is a trade-off between achieving maximum energy saving and guaranteeing QoS. In this paper, a predictive doze mode mechanism in an enhanced EPON architecture is proposed to achieve energy saving by using a logistic regression (LR) model. The optical line terminal (OLT) in the EPON employs an enhanced Doze Manager practicing the LR model to predict the doze periods of the optical network units (ONUs). The doze periods are estimated more accurately based on the historical high-priority traffic information, and logistic regression DBA (LR-DBA) performs dynamic bandwidth allocation accordingly. The proposed LR-DBA mechanism is compared with a scheme without energy saving (IPACT) and another scheme with energy saving (GDBA). Simulation results show that LR-DBA effectively improves the power consumption of ONUs in most cases, and the improvement can be up to 45% while it guarantees the QoS metrics, such as the high-priority traffic delay and jitter.

Finding linear functions that maximize AUC scores is important in ranking research. A typical approach to the ranking problem is to reduce it to a binary classification problem over a new instance space, consisting of all pairs of positive and negative instances. Specifically, this approach is formulated as hard or soft margin optimization problems over pn pairs of p positive and n negative instances. Solving the optimization problems directly is impractical since we have to deal with a sample of size pn, which is quadratically larger than the original sample size p+n. In this paper, we reformulate the ranking problem as variants of hard and soft margin optimization problems over p+n instances. The resulting classifiers of our methods are guaranteed to have a certain amount of AUC scores.

Given the worldwide proliferation of cyberattacks, it is imperative that cybersecurity education and training are addressed in a timely manner. These activities typically require trainees to do hands-on practice in order to consolidate and improve their skills, for which purpose training environments called cyber ranges are used. In this paper we present an open-source system named CyRIS (Cyber Range Instantiation System) that supports this endeavor by fully automating the training environment setup, thus making it possible for any organization to conduct more numerous and variate training activities. CyRIS uses a text-based representation in YAML format to describe the characteristics of the training environment, including both environment setup and security content generation. Based on this description, CyRIS automatically creates the corresponding cyber range instances on a computer and network infrastructure, for simultaneous use by multiple trainees. We have evaluated CyRIS in various realistic scenarios, and our results demonstrate its suitability for cybersecurity education and training, both in terms of features and performance, including for large-scale training sessions with hundreds of participants.

Multivariate Public Key Cryptosystems (MPKCs) are often touted as future-proofing against Quantum Computers. In 2009, it was shown that hardware advances do not favor just “traditional” alternatives such as ECC and RSA, but also makes MPKCs faster and keeps them competitive at 80-bit security when properly implemented. These techniques became outdated due to emergence of new instruction sets and higher requirements on security. In this paper, we review how MPKC signatures changes from 2009 including new parameters (from a newer security level at 128-bit), crypto-safe implementations, and the impact of new AVX2 and AESNI instructions. We also present new techniques on evaluating multivariate polynomials, multiplications of large finite fields by additive Fast Fourier Transforms, and constant time linear solvers.

Two wideband circularly polarized (CP) equilateral triangular slot (ETS) antennas are proposed for communication system and the Global Navigation Satellite System (GNSS) Radio Occultation (RO) sensor of the GAIA-I microsatellite. These wide slot antennas use the ring slot antenna CP generation method due to their shape. The compact antennas employ truncated corners, grounded equilateral triangular perturbation patch and branched feed line to create CP radiation. A 3-dB axial ratio bandwidth (ARBW) enhancement is achieved by inserting a pair of slits into the ETS. A parametric study on the influence of those shape modifications in reflection coefficient and axial ratio is presented. An ETS antenna for communication system of the GAIA-I is fabricated and measured, which is shown to agree well with its simulated performance by providing CP fractional bandwidth of 52%. An ETS antenna designed for the GNSS RO sensor of GAIA-I delivers 3-dB ARBW of 41.6%. The ETS antenna offers uni-directional radiation by mounting a 3D printed truncated cone reflector underneath which also enhances antenna gain.

Many subjective quality assessment methods have been standardized. Experimenters can select a method from these methods in accordance with the aim of the planned subjective assessment experiment. It is often argued that the results of subjective quality assessment are affected by range effects that are caused by the quality distribution of the assessment videos. However, there are no studies on the double stimulus continuous quality-scale (DSCQS) and absolute category rating with hidden reference (ACR-HR) methods that investigate range effects in the high-quality range. Therefore, we conduct experiments using high-quality assessment videos (high-quality experiment) and low-to-high-quality assessment videos (low-to-high-quality experiment) and compare the DSCQS and ACR-HR methods in terms of accuracy, stability, and discrimination ability. Regarding accuracy, we find that the mean opinion scores of the DSCQS and ACR-HR methods were marginally affected by range effects, although almost all common processed video sequences showed no significant difference for the high- and low-to-high-quality experiments. Second, the DSCQS and ACR-HR methods were equally stable in the low-to-high-quality experiment, whereas the DSCQS method was more stable than the ACR-HR method in the high-quality experiment. Finally, the DSCQS method had higher discrimination ability than the ACR-HR method in the low-to-high-quality experiment, whereas both methods had almost the same discrimination ability for the high-quality experiment. We thus determined that the DSCQS method is better at minimizing the range effects than the ACR-HR method in the high-quality range.