Integral cryptanalysis, which was introduced by Knudsen and Wagner, is one of the most powerful attacks on symmetric key ciphers. Attackers preliminarily search integral characteristics of a target cipher for the key-recovery attack. Todo proposed a novel technique named the division property to find them efficiently. In this paper, we apply this technique to the symmetric key block cipher KASUMI which was developed by modifying MISTY1. It has been used worldwide in the 3rd generation mobile communication networks. As a result, we found new 4.5-round characteristics of KASUMI for the first time. We show that 7-round KASUMI is attackable with 263data complexity and 263.3encryptions under the weak key conditions.

Midori64 proposed by Banik et al. in 2015 is an SPN-type block cipher with 128-bit secret key. The designers have evaluated the security of Midori64 against differential attack, linear attack, boomerang-type attack, impossible differential attacks, and meet-in-the-middle attack by themselves. In this paper, we discuss higher-order differential attack on Midori64, which has not been analyzed yet. Higher-order differential attack proposed by Lai is one of the generic cryptanalysis technique focusing on degree of boolean polynomial of encryption function. As a result, we show the 12th-order differential attack on the 10-round variant of Midori64 where we exploit partial-sum technique proposed by Ferguson and the first-round key assumption called a round-elimination technique. The original Midori64 is secure against our attack because it consists of 16 round functions.

The upper bound of DCPmaxis a security index of a cipher against differential cryptanalysis. It is usually evaluated by a truncated-path search with Viterbi algorithm. The search often gives an imaginary path as the resultant optimum one in generalized Feistel-type cipher, which cannot be connected as a real path. We discuss the phenomenon on example base, and propose a new search method to avoid such imaginary paths. Our method is based on carrying over a constraint equation in state transition, and can give the tighter upper bound of DCPmaxthan conventional one.

Enocoro is a family of stream ciphers proposed by Watanabe et al. in 2007. It consists of two algorithms called Enocoro-80 and Enocoro-128v1.1, whose key lengths are 80 bits and 128 bits respectively. In this paper, we show that Enocoro-128v1.1 is vulnerable against the related-key attack in which we assume a stronger attacker than one in the related-key differential attack. The attack is applicable with 2112out of 2128keys and the calculation complexity of the attack is about 265. Our attack is mainly of theoretical interest and do not present a threat to practical applications using Enocoro-128v1.1. In addition, we propose to update Enocoro-128v1.1 to Enocoro-128v2 where a patch has been applied to prevent the attack.

Sensitive information, e.g., privacy information or company secret, should be carefully managed and it is desired that only privileged users can read and edit these kinds of information. For these needs, this paper proposes cryptographic schemes for a proper use of digital document and a concrete construction for the proposed schemes. Note that the proposed schemes are called ldquocontent protection schemes (CPSs)rdquo in this paper. The proposed schemes enable a sender to decide an access control, i.e., read-write protection, on a document by public keys of recipients and a recipient can read or edit a part of the document according to the access control without any help of neither the sender nor any trusted entity. The concrete construction proposed in this paper consists of only standard cryptographic techniques. This means that the proposed construction can be easily implemented by a standard cryptographic library and that users do not need to prepare a special key set for the proposed schemes. Since the proposed schemes control the read-write protection on a digital document by private keys of recipients, they can promote proper use of digital document even if we could not manage them on a server.

Panama is a pseudo-random number generator proposed by Daemen and Clapp in 1998. It is designed to achieve high performance in software implementations, and the throughput is twice as fast as that of the AES block cipher. On the other hand, the size optimized implementation in hardware circuit is much larger than that of the AES. We are attempted to design a new hardware oriented PRNG which has a similar structure to Panama. In this paper, a family of PRNGs Enocoro is presented and especially a specific algorithm Enocoro-80 for 80-bit key is given. Enocoro-80 can be implemented with 2.7 Kgates in ASIC. The implementation results are comparable to other ciphers selected as the eSTREAM Profile 2 candidates (hardware oriented ciphers). As a result, we confirm that the design of Panama is suitable to not only a software oriented cipher, but also a hardware oriented cipher.

In line-of-sight (LOS) environments, the signal detection of multiple-input multiple-output (MIMO) systems becomes difficult because the correlation among channels becomes higher when the phase differences of direct paths are close to each other. In this paper, we propose a MIMO system with precoding to maximize the minimum distance (denoted hereafter as Max-dminprecoding) to improve the performance of MIMO systems in LOS environments. Max-dminprecoding can improve the detection performance of maximum likelihood detection (MLD) by maximizing the minimum Euclidean distance between symbol points at the receiver side, but the design becomes complicated as the number of substreams increases. The design of our proposed Max-dminprecoding is easy by using the property that the first eigenvalue of channel matrix becomes dominant in LOS environments even when the number of substreams is large. We use long-term average channel state information (CSI) instead of instantaneous CSI for precoding. Moreover, we propose a reduced-complexity MLD that uses the ordered reliability of symbols that results from Max-dminprecoding. From the results of computer simulation, we show that our proposed scheme with reduced-complexity MLD can achieve low complexity and good bit error rate (BER) performance in LOS environments with Rician factor K = 5 dB.

Multiple-input multiple-output (MIMO) systems that realize a high-speed data transmission with multiple antennas at both transmitter and receiver are drawing much attention. In MIMO systems, it has been reported that the scheme that weights transmitted signals based on minimum mean square error (MMSE) criterion at the transmitter using feedback channel state information (CSI) achieves good performance (denoted hereafter as MMSE precoding). A throughput maximization transmission control scheme (TMTC) that selects the transmission mode (modulation schemes and code rates) based on CSI has been proposed. We expect that its throughput performance can be improved by addition of MMSE precoding. However, throughput performance is degraded in the presence of feedback delay. In this paper, we propose TMTC with MMSE precoding; it reduces the throughput performance degradation by using channel prediction and the receive weights robust against feedback delay. The proposed scheme selects a transmission mode (the number of substreams, modulation schemes, and code rates) and configures the precoder to achieve maximum throughput based on the SINR given by channel prediction. Simulation results show that even when feedback delay exists, the proposed scheme attains high throughput.

Random unitary beamforming is one of the schemes reducing the amount of feedback information in multiuser diversity techniques with multiple-antenna downlink transmission. In multiple-input multiple-output (MIMO) systems, throughput performance is greatly improved using AMC (adaptive modulation and coding). Throughput performance is also improved by allocating power among streams appropriately. In random unitary beamforming, transmitter has only partial channel state information (CSI) of each receiver because of reducing the amount of feedback information. Thus, the power allocation scheme needs to work with only partial CSI and low latency. In this paper, we propose a new power allocation scheme for random unitary beamforming assuming a discrete transmission rate with a small amount of feedback information and low latency. Simulation results show that the proposed scheme can improve throughput compared to conventional power allocation scheme.

Random unitary beamforming is one of the schemes reducing the amount of feedback information in multiuser diversity techniques with multiple-antenna downlink transmission. In multiple-input multiple-output (MIMO) systems, throughput performance is greatly improved using AMC (adaptive modulation and coding). Throughput performance is also improved by allocating power among streams appropriately. In random unitary beamforming, transmitter has only partial channel state information (CSI) of each receiver. Thus, it is difficult for random unitary beamforming to use conventional power allocation methods that use full CSI at all the receivers. In this paper, we propose a new scheduling algorithm with power allocation for downlink random unitary beamforming that improves throughput performance without full CSI. We provide numerical results of the proposed scheduling algorithm and compare them to those of the conventional random unitary beamforming scheduling algorithm.

In this paper, we propose the low computational complexity 2D pilot-symbol-assisted (2D PSA) MMSE channel estimation with extended estimation size for MIMO-OFDM systems. In the proposed scheme, we assume the estimated channel frequency responses of some adjacent subcarriers in an OFDM symbol and those in some adjacent OFDM symbols to be constant to reduce the computational complexity, and extend MMSE channel estimation size to improve the mean square error (MSE) performance. We show that the proposed channel estimation achieves the better MSE performance with the same or lower computational complexity than the conventional 2D PSA MMSE channel estimation.

Likelihood Ratio Test (LRT) and Best Linear Unbiased Estimator (BLUE) have been researched as estimation methods of observation event in sensor network. LRT and BLUE can estimate the observation event with high accuracy at the Fusion Center (FC) when the FC has a perfect knowledge of observation statistics of each sensor node. However, all the sensor nodes' observation statistics are not always available at the FC. In this paper, we propose a method to estimate false alarm probability and observation noise variance of each sensor node at the FC, and present the performance of LRT and BLUE using the proposed estimation method. We show that the LRT and BLUE using the proposed method achieve almost the same bit error rate (BER) as the conventional LRT and BLUE with perfect knowledge of them.

In this paper, we propose a concatenated code by combining a Recursive Systematic Convolutional (RSC) code with a Low-Density Parity-Check (LDPC) code. The proposed concatenated code is encoded in parallel by an RSC encoder and an LDPC encoder without interleavers between them. When decoding the proposed concatenated code, the information bits are decoded by two decoding algorithms, and soft information is exchanged between the RSC decoder and the LDPC decoder. This allows for the elimination of wrong codewords output by each decoder. The use of an LDPC code allows us to halt the decoding process when the valid codeword is obtained. We evaluate the error rate performance of the proposed concatenated code by computer simulations. We show that the proposed concatenated code does not have a high error floor, and achieves better BLock Error Rate (BLER) performance than either conventional LDPC codes or conventional turbo codes in the high Eb/No region. We also show that since the proposed concatenated code can correct wrong codewords output by each decoder, it achieves better BLER than the regular LDPC code at the same Bit Error Rate (BER).

Recently, multiple-input multiple-output (MIMO) systems that realize a high bit rate data transmission with multiple antennas at both transmitter and receiver have drawn much attention for high spectral efficiencies. In MIMO systems, eigen-beam space division multiplexing (E-SDM) that achieves good performance by weighting at the transmitter using channel state information (CSI) has been studied. Early studies for E-SDM have assumed perfect CSI at the transmitter. However, in practice, CSI fed back to the transmitter is not identical to that when the signals are transmitted owing to the time-varying nature of channels and feedback delay. As a result, the performance of E-SDM is degraded. In this paper, as methods that reduce the performance degradation of E-SDM in the presence of feedback delay, we evaluate the performance of a method that predicts CSI when the signals are transmitted at the receiver and feeds the predicted CSI back to the transmitter (denoted by channel prediction method). We also evaluate the performance of a method that uses the receive weight based on zero-forcing (ZF) or minimum mean square error (MMSE) criterion instead of those based on singular value decomposition (SVD) criterion (denoted by ZF or MMSE receive weight method). Simulation results show that bit error rate (BER) degradation of E-SDM in the presence of feedback delay is reduced by three methods. We also show that the ZF and MMSE receive weight methods achieve the identical BER with smaller amount of calculation than the channel prediction method.

A low-density parity check (LDPC) code with the belief propagation (BP) or the log-likelihood ratio belief propagation (LLR-BP) can achieve good bit error rate (BER) performance approaching the Shannon limit. When a parity check matrix of the LDPC code has the cycle, the BP and LLR-BP decoding algorithms achieve approximate maximum a posterior probability (MAP) decoding. Although the decoding algorithms are approximate MAP decoding, LDPC codes can achieve very good BER. For the short and middle length LDPC codes, BER and block error rate (BLER) performances are affected by cycle largely. In each iteration, the magnitudes of a posterior LLRs of some bits oscillate owing to cycles. The oscillation is the dominant error factor in the high Eb/Noregion for short and middle length LDPC codes. In this paper, we extend the definition of oscillation to extrinsic LLR (ex-LLR) derived in the bit node process and propose the modified LLR-BP and the modified UMP-BP decoding algorithms. To reduce effects of oscillating ex-LLRs on decoding, for oscillating ex-LLRs, we add the previous ex-LLR to the current ex-LLR. From the computer simulation, we show that for short and middle length LDPC codes, with a simple modification, our proposed decoding algorithms can improve the conventional LLR-BP and UMP-BP decoding algorithms. In particular, we show that the modified UMP-BP decoding algorithm with low complexity can achieve better BER and BLER than the conventional LLR-BP decoding algorithm

Multiple-input multiple-output (MIMO) systems can achieve high data-rate and high capacity transmission. In MIMO systems, the scheme that weight substreams based on minimum mean square error (MMSE) criterion at the transmitter using feedback channel state information (CSI) achieves good performance (denoted hereafter as MMSE precoder). However, if the optimum number of substreams is not selected based on CSI and methods for reducing the performance degradation due to feedback delay is not used, MMSE precoder cannot achieve the full performance possible. In this paper, we propose an MMSE precoder with mode selection for MIMO systems, which selects both the number of substreams and the modulation scheme for each substream to minimize the average BER at a fixed rate. We evaluate the BER of the proposed MMSE precoder with two methods for reducing performance degradation due to feedback delay, channel prediction and receive weight robust to feedback delay. We also evaluate the BER of the proposed MMSE precoder with the method that combines channel prediction with receive weight robust to feedback delay. Simulation results show that the BER of the proposed MMSE precoder is improved compared to that of the conventional MMSE precoder using the fixed number of substreams. We also show that the method that combines channel prediction with receive weight robust to feedback delay can achieve good BER even when the large feedback delay exists.

One typical use of sensor networks is monitoring targets. The sensor networks classify, detect, locate, and track targets. The ML (maximum likelihood) algorithm is one of the estimation algorithms of target location and has high accuracy to estimate target location. However, the calculation amount of the ML estimation algorithm is large. Energy-ratios source localization nonlinear least square (ER-NLS) is proposed to realize the ML algorithm. ER-NLS is the algorithm of estimating source location by using the ratio of sensors' receiving energies. However, ER-NLS has to search all the areas, so that the calculation amount of ER-NLS is large. In this paper we propose a method of reducing search area for localization. The proposed method uses the ratio of sensors' receiving energies. It can be used with the ML algorithm. We show that the proposed method with the ML algorithm can reduce the search areas to estimate the target location and thus reduce the complexity, while achieving the RMSE (root mean square error) close to that of the ML algorithm

We obtain upper bounds on the bit-error rate (BER) for the performance of linear binary block coded optical pulse position modulation (PPM) code-division multiple-access (CDMA) systems with soft-decision decoding. We use a union bounding technique to obtain these bounds, so our results correspond to the upper bounds. We consider systems using binary PPM (BPPM) and an avalanche photodiode (APD), and treat APD noise, thermal noise, and multi-user interference using a Gaussian approximation. We compare the performance of BCH-coded BPPM CDMA systems with soft-decision decoding with that of BCH-coded BPPM CDMA systems with hard-decision decoding. We show that BCH-coded optical PPM CDMA systems using soft-decision decoding can achieve much lower BER than BCH-coded optical PPM CDMA systems using hard-decision decoding.