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Blockchain-Based Secure and Fair IoT Data Trading System with Bilateral Authorization

computers, Materials & Continua 2023年第8期76卷 1871-1890页

作者： Youngho Park Mi Hyeon Jeon Sang Uk Shin Electronics and Information Communications Research Center Pukyong National UniversityBusanKorea Department of Information Security Graduate SchoolPukyong National UniversityBusanKorea Division of Computer Engineering Pukyong National UniversityBusanKorea

These days,data is regarded as a valuable asset in the era of the data economy,which demands a trading platform for buying and selling ***,online data trading poses challenges in terms of security and fairness because the seller and the buyer may not fully trust each ***,in this paper,a blockchain-based secure and fair data trading system is proposed by taking advantage of the smart contract and matchmaking *** proposed system enables bilateral authorization,where data trading between a seller and a buyer is accomplished only if their policies,required by each other,are satisfied *** can be achieved by exploiting the security features of the matchmaking *** guarantee non-repudiation and fairness between trading parties,the proposed system leverages a smart contract to ensure that the parties honestly carry out the data trading ***,the smart contract in the proposed system does not include complex cryptographic operations for the efficiency of onchain ***,these operations are carried out by off-chain parties and their results are used as input for the on-chain *** system also uses an arbitration protocol to resolve disputes based on the trading proof recorded on the *** performance of the protocol is evaluated in terms of off-chain computation overhead and on-chain gas *** results of the experiments demonstrate that the proposed protocols can enable the implementation of a cost-effective data trading system.

关键词： Bilateral authorization blockchain data marketplace fair exchange policy matching secure data trading

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A Robust Technique for Steganography of Enhanced Audio Signals 3

A Robust Technique for Steganography of Enhanced Audio Signa...

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3rd IEEE International Conference on Electronic engineering, ICEEM 2023

作者： Nasr, Marwa A. El-Shafai, Walid El-Rabaie, El-Sayed M. El-Fishawy, Adel S. Dessouky, Moawad I. Abdel-Salam, Nariman El-Samie, Fathi E. Abd Menoufia University Faculty of Electronic Engineering Electronics and Electrical Communications Engineering Department Menouf Egypt Prince Sultan University Security Engineering Laboratory Department of Computer Science College of Engineering Riyadh Saudi Arabia Faculty of Engineering Communications and Electronics Engineering Department Giza Egypt

ISBN: (纸本)9798350323511

Audio steganography is a tool for concealing data (a secret message) inside an audio signal (a carrier). It is regarded as an essential approach for information security. This paper presents a proposed technique for audio signal steganography, which is implemented in the wavelet domain, with a pre-processing enhancement step. First, adaptive Wiener filtering is implemented to reduce the noise on audio signals. Then, the Inverse Short-Time Fourier Transform (ISTFT) is applied to convert the target image from the spectrogram-like nature to the 1-D signal-like nature. The embedding process is performed on high-frequency coefficients in the wavelet domain to keep the audio signals unchanged for human perception. The reverse process is implemented at the receiver. Hence, the embedded coefficients are extracted to recover the embedded image through Short-Time Fourier Transform (STFT). The recovered audio signal is also obtained after the removal of embedded coefficients. The major goal is to enhance the performance of the audio steganography technique, while retaining the audio signal quality. The outcomes show that the suggested technique successfully allows audio steganography and enhances the resultant audio signal quality at different Signal-to-Noise Ratio (SNR) levels. © 2023 IEEE.

关键词： Steganography

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Al-Biruni Earth Radius(BER)Metaheuristic Search Optimization Algorithm

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computer Systems Science & engineering 2023年第5期45卷 1917-1934页

作者： El-Sayed M.El-kenawy Abdelaziz A.Abdelhamid Abdelhameed Ibrahim Seyedali Mirjalili Nima Khodadad Mona A.Al duailij Amel Ali Alhussan Doaa Sami Khafaga Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Centre for Artificial Intelligence Research and Optimization Torrens University AustraliaFortitude ValleyQLD 4006Australia Yonsei Frontier Lab Yonsei UniversitySeoul03722Korea Department of Civil and Environmental Engineering Florida International UniversityMiamiUSA Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

Metaheuristic optimization algorithms present an effective method for solving several optimization problems from various types of applications and *** metaheuristics and evolutionary optimization algorithms have been emerged recently in the literature and gained widespread attention,such as particle swarm optimization(PSO),whale optimization algorithm(WOA),grey wolf optimization algorithm(GWO),genetic algorithm(GA),and gravitational search algorithm(GSA).According to the literature,no one metaheuristic optimization algorithm can handle all present optimization *** novel optimization methodologies are still *** Al-Biruni earth radius(BER)search optimization algorithm is proposed in this *** proposed algorithm was motivated by the behavior of swarm members in achieving their global *** search space around local solutions to be explored is determined by Al-Biruni earth radius calculation method.A comparative analysis with existing state-of-the-art optimization algorithms corroborated the findings of BER’s validation and testing against seven mathematical optimization *** results show that BER can both explore and avoid local *** has also been tested on an engineering design optimization *** results reveal that,in terms of performance and capability,BER outperforms the performance of state-of-the-art metaheuristic optimization algorithms.

关键词： Metaheuristics evolutionary optimization exploration exploitation mutation Al-biruni earth radius

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Deep Learning Aided LLR Correction Improves the Performance of Iterative MIMO Receivers

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IEEE Transactions on Vehicular Technology 2024年第2期73卷 2045-2060页

作者： Chen, Jue Wang, Tsang-Yi Wu, Jwo-Yuh Li, Chih-Peng Ng, Soon Xin Maunder, Robert G. Hanzo, Lajos University of Southampton School of Electronics and Computer Science SouthamptonSO17 1BJ United Kingdom National Yang Ming Chiao Tung University Institute of Communications Engineering Hsinchu300 Taiwan National Sun Yat-sen University Institute of Communications Engineering Kaohsiung804 Taiwan National Science and Technology Council Department of Engineering and Technologies Taipei10622 Taiwan

A Deep Learning (DL) aided Logarithmic Likelihood Ratio (LLR) correction method is proposed for improving the performance of Multiple-Input Multiple-Output (MIMO) receivers, where it is typical to adopt reduced-complexity algorithms for avoiding the excessive complexity of optimal full-search algorithms. These sub-optimal techniques typically express the probabilities of the detected bits using LLRs that often have values that are not consistent with their true reliability, either expressing too much confidence or not enough confidence in the value of the corresponding bits, leading to performance degradation. To circumvent this problem, a Deep Neural Network (DNN) is trained for detecting and correcting both over-confident and under-confident LLRs. We demonstrate that the complexity of employing the DL-aided technique is relatively low compared to the popular reduced-complexity receiver detector techniques since it only depends on a small number of real-valued inputs. Furthermore, the proposed approach is applicable to a wild variety of iterative receivers as demonstrated in the context of an iterative detection and decoding aided MIMO system, which uses a low-complexity Smart Ordering and Candidate Adding (SOCA) scheme for MIMO detection and Low-Density Parity Check (LDPC) codes for channel coding. We adopt Extrinsic Information Transfer (EXIT) charts for quantifying the Mutual Information (MI) and show that our DL method significantly improves the BLock Error Rate (BLER). Explicitly, we demonstrate that about 0.9 dB gain can be achieved at a BLER of 10-3 by employing the proposed DL-aided LLR correction method, at the modest cost of increasing the complexity by 16% compared to a benchmarker dispensing with LLR correction. © 1967-2012 IEEE.

关键词： Iterative decoding

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Anomalous IoT Behavior Detection by Generated Power Waveforms with Hyper-parameter Tuning

Anomalous IoT Behavior Detection by Generated Power Waveform...

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IEEE Symposium on On-Line Testing (IOLTS)

作者： Ryusei Eda Kota Hisafuru Nozomu Togawa Department of Computer Science and Communications Engineering Waseda University

ISBN: (数字)9798350370553

ISBN: (纸本)9798350370560

With the recent spread of Internet of Things (IoT) devices, the security issues for hardware devices have increased. When an IoT device runs an application program, the power consumption of the running application is combined with the power consumption of the device hardware itself, resulting in a complex power waveform. To detect anomalous application behaviors using the power waveforms, it is necessary to subtract the steady-state power waveform due to the device hardware from the measured power waveforms and extract only the application power waveform. In this paper, we propose a method for detecting anomalous IoT behaviors using generated power waveforms by introducing hyper-parameter tuning. The proposed method detects anomalous behaviors by generating a highly accurate steady-state power waveform and an application power waveform by adjusting the waveform period through hyper-parameter tuning, even if the measured power waveform includes large noises. Experimental evaluation demonstrates that we successfully detect anomalous behaviors from an AES encryption circuit containing a hardware Trojan on an FPGA device, while the existing state-of-the-art method cannot.

关键词： Power measurement Power demand Neural networks Hardware Steady-state Internet of Things Trojan horses

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Carrying-Mode-Free Stair Ascent and Descent Estimation using Smartphones

Carrying-Mode-Free Stair Ascent and Descent Estimation using...

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IEEE International Conference on Consumer Electronics (ICCE)

作者： Dai Kajimoto Etsushi Saeki Siya Bao Nozomu Togawa Department of Computer Science and Communications Engineering Waseda University

This paper proposes a smartphone-based pedestrian dead reckoning to track stair ascent and descent. By using accelerometer and barometer information, pedestrians’ gait patterns are collected under different carrying modes to detect the stair ascent and descent motions. Also, weather influences are considered to eliminate the barometer measurement errors. We evaluate the proposed method in a seven-floor environment, and we compare our method with a conventional method without multiple carrying modes and weather considerations. The minimal error rate of the proposed method is only $4.2 \%$ when ascending or descending seven floors, and at most $14.4 \%$ error are reduced compared with the conventional method.

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Neural Network-based Prognostic Model for Cerebrovascular Accident using CT Scans 2

Neural Network-based Prognostic Model for Cerebrovascular Ac...

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2nd International Conference on Sustainable Computing and Data Communication Systems, ICSCDS 2023

作者： Fiona, Mary Rajeswari, M. Amalasweena, M. Karunya Institute of Technology and Sciences Department of Computer Science and Engineering Coimbatore India R.M.D. Engineering College Department of Electronics and Communications Engineering Kavaraipettai India

ISBN: (纸本)9781665491990

Cerebrovascular accident (CVA), stroke has a 5.5 million yearly mortality rate, making it the second most common cause of death in the world. So, it is inevitable to find a method that can efficiently predict the stroke with high accuracy and considerably in less time. Medical imaging, such as brain MRI or CT scans, helps to provide considerable information on stroke prediction, but a manual prediction can be time-consuming and considerably imprecise. Stroke prediction with empirical attributes can be beneficial but a CT scan provides detailed and accurate images of the brain and helps in the prediction of the stroke in the exact location occurrence. This study employs predicting the stroke by training the CT image dataset using the four efficient algorithms, CNN-EfficientNetB0, Random Forest, Support Vector Machines (SVM), and Decision Trees. With the help of performance measures, the models' performance is assessed. Our results showed that the early prediction of stroke with the CNN's EfficientNet-B0 architecture provides high accuracy, sensitivity, and specificity. Hence the proposed method aids in providing an efficient approach for the early prediction of stroke with less time-consuming and comparatively more precise classification. © 2023 IEEE.

关键词： Support vector machines

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Node Sociability Based Intelligent Routing for Post-Disaster Emergency Networks

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China communications 2024年第8期21卷 104-114页

作者： Li Jiameng Xiong Xuanrui Liu Min Amr Tolba School of Communications and Information Engineering Chongqing University of Posts and TelecommunicationsChongqing 400065China Graduate School of Information Production and SystemsWaseda UniversityFukuoka 808-0135Japan School of Communications and Information Engineering Chongqing College of Mobile CommunicationChongqing 401520China Computer Science Department Community CollegeKing Saud UniversityRiyadh 11437Saudi Arabia

In a post-disaster environment characterized by frequent interruptions in communication links,traditional wireless communication networks are *** the“store-carry-forward”mechanism characteristic of Delay Tolerant Networks(DTNs)can transmit data from Internet of things devices to more reliable base stations or data centres,it also suffers from inefficient data transmission and excessive transmission *** address these challenges,we propose an intelligent routing strategy based on node sociability for post-disaster emergency network ***,we introduce an intelligent routing strategy based on node intimacy,which selects more suitable relay nodes and assigns the corresponding number of message copies based on comprehensive utility ***,we present an intelligent routing strategy based on geographical location of nodes to forward message replicas secondarily based on transmission utility ***,experiments demonstrate the effectiveness of our proposed algorithm in terms of message delivery rate,network cost ratio and average transmission delay.

关键词： delay tolerant networks Internet of things node sociability routing strategy

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Wireless modulation classification based on Radon transform and convolutional neural networks

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Journal of Ambient Intelligence and Humanized Computing 2023年第5期14卷 6263-6272页

作者： Ghanem, Hanan S. Al-Makhlasawy, Rasha M. El-Shafai, Walid Elsabrouty, Maha Hamed, Hesham F. A. Salama, Gerges M. El-Samie, Fathi E. Abd Department of Electrical Engineering Faculty of Engineering Minia University Minia61111 Egypt Department of Computers and Systems Electronics Research Institute Cairo Egypt Security Engineering Lab Computer Science Department Prince Sultan University Riyadh11586 Saudi Arabia Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt Department of Electronics and Communications Engineering Egypt-Japan University of Science and Technology Alexandria Egypt Faculty of Engineering Egyptian-Russian University Cairo Egypt Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia

Convolutional Neural Networks (CNNs) are efficient tools for pattern recognition applications. They have found applications in wireless communication systems such as modulation classification from constellation diagrams. Unfortunately, noisy channels may render the constellation points deformed and scattered, which makes the classification a difficult task. This paper presents an efficient modulation classification algorithm based on CNNs. Constellation diagrams are generated for each modulation type and used for training and testing of the CNNs. The proposed work depends on the application of Radon Transform (RT) to generate more representative patterns for the constellation diagrams to be used for training and testing. The RT has a good ability to represent discrete points in the spatial domain as curved lines. Several pre-trained networks including AlexNet, VGG-16, and VGG-19 are used as classifiers for modulation type from the spatial-domain constellation diagrams or their RTs. Several simulation experiments are presented in this paper to compare different scenarios for modulation classification at different Signal-to-Noise Ratios (SNRs) and fading channel conditions. © 2022, The Author(s).

关键词： Fading channels

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Maximum Zero-Outage Secrecy Capacity of Fading Wiretap Channels with Finite Alphabets 57

Maximum Zero-Outage Secrecy Capacity of Fading Wiretap Chann...

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57th Annual Conference on Information Sciences and Systems, CISS 2023

作者： Xu, Xiaoyang Bessert, Karl-Ludwig Lin, Pin-Hsun Jorswieck, Eduard A. Institute for Communications Technology Technische Universität Braunschweig Germany Princeton University Department of Electrical and Computer Engineering United States

ISBN: (纸本)9781665451819

When a transmitted signal encounters slow fading and the support of the fading gain contains zero, an outage event will happen inevitably, if the transmitter has no knowledge of the channel state. This will deteriorate the system performance metrics such as latency due to re-transmissions caused by the outages. For scenarios like this, we use the outage probability or the outage capacity to measure the system performance. In this work, we investigate the possibility of achieving a positive zero-outage secrecy capacity (ZOSC) for a wiretap channel with fading gains from finite alphabet sets. In particular, we investigate the minimum secrecy outage probability with respect to all possible joint distributions of the fading gains, given their marginal distributions. We propose a systematic scheme to calculate the minimum secrecy outage probability by solving linear programming problems. From this, the maximum ZOSC of the considered wiretap channel model directly follows. Interestingly, we find that scenarios with a ZOSC of zero for independent fading can support a positive ZOSC when the fading links are dependent. © 2023 IEEE.

关键词： Linear programming

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