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Secure key-alternating Feistel ciphers without key schedule

science China(Information sciences) 2021年第1期64卷 251-253页

作者： Yaobin SHEN Hailun YAN Lei WANG Xuejia LAI Department of Computer Science and Engineering Shanghai Jiao Tong University Westone Cryptologic Research Center

Dear editor,Blockciphers play an fundamental role for cryptography in information security,which usually consist of round functions and key *** one of the significant modules in blockciphers,key schedules have not received deserved ***,the key schedule takes as input a master key and outputs the so-called round keys that are used in each *** the case of AES-128,the master key is a 128-bit string and the total length of the round keys is11×128=1408 *** AES-128 key schedule can be seen as a function from{0,1}128 to{0,1}1408.

关键词： Information Systems and Communication Service

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Extinction Chains Reveal Intermediate Phases Between the Safety and Collapse in Mutualistic Ecosystems

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engineering 2024年第12期43卷 89-98页

作者： Guangwei Wang Xueming Liu Ying Xiao Ye Yuan Linqiang Pan Xiaohong Guan Jianxi Gao Hai-Tao Zhang The MOE Engineering Research Center of Autonomous Intelligent Unmanned Systems State Key Laboratory of Digital Manufacturing Equipment and TechnologySchool of Artificial Intelligence and AutomationHuazhong University of Science and TechnologyWuhan 430074China Guangdong HUST Industrial Technology Research Institute Huazhong University of Science and TechnologyDongguan 523808China Guangdong Provincial Engineering Technology Center of Autonomous Unmanned Vessels Dongguan 523808China MOE Key Laboratory of Intelligent Networks and Network Security&State Key Laboratory of Manufacturing Systems Xi’an Jiaotong UniversityXi’an 710049China Tsinghua National Laboratory of Information Science and Technology Department of AutomationTsinghua UniversityBeijing 100084China Department of Computer Science Rensselaer Polytechnic InstituteTroyNY 12180USA

Ecosystems are undergoing unprecedented persistent deterioration due to unsustainable anthropogenic human activities,such as overfishing and deforestation,and the effects of such damage on ecological stability are *** recent advances in experimental and theoretical studies on regime shifts and tipping points,theoretical tools for understanding the extinction chain,which is the sequence of species extinctions resulting from overexploitation,are still lacking,especially for large-scale nonlinear networked *** this study,we developed a mathematical tool to predict regime shifts and extinction chains in ecosystems under multiple exploitation situations and verified it in 26 real-world mutualistic networks of various sizes and *** discovered five phases during the exploitation process:safe,partial extinction,bistable,tristable,and collapse,which enabled the optimal design of restoration strategies for degraded or collapsed *** validated our approach using a 20-year dataset from an eelgrass restoration ***,we also found a specific region in the diagram spanning exploitation rates and competition intensities,where exploiting more species helps increase *** computational tool provides insights into harvesting,fishing,exploitation,or deforestation plans while conserving or restoring the biodiversity of mutualistic ecosystems.

关键词： Complex system Network science Overexploitation Regime shift Metastability

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Diode-Triode Current Mirror Inverter PUF: A Novel Mixed-Signal Low Power Analog PUF 66

Diode-Triode Current Mirror Inverter PUF: A Novel Mixed-Sign...

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2023 IEEE 66th International Midwest Symposium on Circuits and Systems, MWSCAS 2023

作者： Gisha, C.G. Chakraborty, Ananda Sankar Chakraborty, Rajat Subhra Jose, Bijoy Antony Mathew, Jimson Cochin University of Science and Technology Department of Electronics Kochi India Berkeley Wireless Research Center Uc Berkeley Berkeley United States Iit Department of Computer Science and Engineering Kharagpur India Cochin University of Science and Technology Department of Computer Science Kochi India Indian Institute of Technology Patna Department of Computer Science Bihar India

ISBN: (纸本)9798350302103

Physically Unclonable Function (PUF) is a useful and versatile lightweight hardware security primitive that takes advantage of unavoidable and unpredictable random process variations during chip manufacturing. This paper proposes a novel diode-triode low-power analog PUF circuit on CMOS current mirror inverter circuit. Due to the random process variation of the MOSFET parameters, the output voltage level of the inverter will vary based on the applied input. These analog voltage variations in the circuit output are converted into a corresponding digital response through an XOR-tree. The performance metrics of the proposed PUF circuit were estimated by simulating a 64-bit PUF circuit at a 32-nano m CMOS technology node. The proposed PUF design achieves a uniformity of 49.87%, an inter-Hamming Distance of 47.52%, average bitaliasing of 49.87%, while consuming 20.99 μW power during operation. The proposed PUF also shows excellent robustness to machine learning based modeling attacks. © 2023 IEEE.

关键词： analog PUF current mirror inverter hardware security low power Mixed-signal PUF

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Social engineering attack types and prevention techniques- A survey 1

Social engineering attack types and prevention techniques- A...

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1st International Conference on Computational Intelligence, Communication Technology and Networking, CICTN 2023

作者： Salama, Ramiz Al-Turjman, Fadi Bhatia, Shruti Yadav, Satya Prakash Near East University Ai and Robotics Institute Research Center for Ai and IoT Department of Computer Engineering Nicosia Turkey Near East University Ai and Robotics Institute Artificial Intelligence Engineering Dept. Nicosia Turkey University of Kyrenia Research Center for Ai and IoT Faculty of Engineering Kyrenia Turkey Graphic Era Hill University Department of Computer Science and Engineering Dehradun India Department of Computer Science and Engineering Greater Noida201306 India

ISBN: (纸本)9798350338027

The term "Cyber Security"is getting more and more popular and important over the last few years. Since computers and most of the devices are connected to the internet, they are likely to be hacked by the hackers. In the past, this issue was not a big problem, because not every device is required to be connected to the internet or the internet was not popular as today. But the case has changed over the years. All the changes in the technology area also changed the cyber-attack models as well. With the development of technology and the change of usage of the internet over the last years cyber-attacks have become more common and popular by the hackers. Hackers have discovered that they have an opportunity to steal or earn money in a short time without having to spend too much effort. These days, the type of cyber-attacks is not the same as the ones in the past. As time passes, the cyber-attack methods are also changing and evolving. Today, hackers are using more advanced and effective cyber-attack methods compared to past years. There are many methods that are impossible to cover all of them in this article. Our main focus will be on social engineering attacks in this article. Social engineering attacks use different approaches to cyber attacking. Unlike trying to explode a victim's social media password etc. using advanced exporting programs, algorithms or techniques, social engineering attacks focus on fooling victims into providing their data to hackers by themselves without using or implementing any password cracking, exploiting techniques etc. We will go over what social media engineering is, type of social engineering methods, what countermeasures can be used to protect from social engineering and more in this article. © 2023 IEEE.

关键词： Crime

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Multi-omics graph convolutional networks for digestive system tumour classification and early-late stage diagnosis

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CAAI Transactions on Intelligence Technology 2024年第6期9卷 1572-1586页

作者： Lin Zhou Zhengzhi Zhu Hongbo Gao Chunyu Wang Muhammad Attique Khan Mati Ullah Siffat Ullah Khan School of Information Science and Technology University of Science and Technology of ChinaHefeiAnhuiChina Anhui Engineering Research Center on Information Fusion and Control of Intelligent Robot WuhuAnhuiChina Department of Breast Center West District of The Affiliated Hospital of University of Science and Technology of ChinaDivision of Life Sciences and MedicineUniversity of Science and Technology of ChinaHefeiAnhuiChina Institute of Advanced Technology University of Science and Technology of ChinaHefeiAnhuiChina School of Electrical and Electronic Engineering Nanyang Technological UniversitySingaporeSingapore School of Biological and Environmental Engineering Chaohu UniversityChaohu Regional Collaborative Technology Service Center for Rural RevitalizationHefeiChina Department of Artificial Intelligence College of Computer Engineering and SciencePrince Mohammad Bin Fahd UniversityAl-KhobarSaudi Arabia School of Automation Northwestern Polytechnical UniversityXi'anShaanxiChina Institute of Engineering and Computing Science University of Science and Technology of BannuKPKBannuPakistan

The prevalence of digestive system tumours(DST)poses a significant challenge in the global crusade against *** neoplasms constitute 20%of all documented cancer diagnoses and contribute to 22.5%of cancer-related *** accurate diagnosis of DST is paramount for vigilant patient monitoring and the judicious selection of optimal *** this challenge,the authors introduce a novel methodology,denominated as the Multi-omics Graph Transformer Convolutional Network(MGTCN).This innovative approach aims to discern various DST tumour types and proficiently discern between early-late stage tumours,ensuring a high degree of *** MGTCN model incorporates the Graph Transformer Layer framework to meticulously transform the multi-omics adjacency matrix,thereby illuminating potential associations among diverse samples.A rigorous experimental evaluation was undertaken on the DST dataset from The Cancer Genome Atlas to scrutinise the efficacy of the MGTCN *** outcomes unequivocally underscore the efficiency and precision of MGTCN in diagnosing diverse DST tumour types and successfully discriminating between early-late stage DST *** source code for this groundbreaking study is readily accessible for download at https://***/bigone1/MGTCN.

关键词： digestive system tumors early-late stage multi-omics tumor types

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A Novel Obstacle Avoidance Consensus Control for Multi-AUV Formation System

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IEEE/CAA Journal of Automatica Sinica 2023年第5期10卷 1304-1318页

作者： Linling Wang Daqi Zhu Wen Pang Chaomin Luo the Shanghai Engineering Research Center of Intelligent Maritime Search&Rescue and Underwater Vehicles Shanghai Maritime UniversityShanghai 201306China the Shanghai Maritime University Shanghai 201306China the School of Mechanical Engineering University of Shanghai for Science and TechnologyShanghai 200093China the Department of Electrical and Computer Engineering Mississippi State UniversityMississippi StateMS 39762 USA

In this paper, the fixed-time event-triggered obstacle avoidance consensus control for a multi-AUV time-varying formation system in a 3D environment is presented by using an improved artificial potential field and leader-follower strategy(IAPF-LF). Firstly, the proposed fixed-time control can achieve the desired multi-AUV formation within a fixed settling time in any initial system state. Secondly, an event-triggered communication strategy is developed to govern the communication among AUVs, and the communication energy consumption can be decremented. The time-varying formation obstacle avoidance control algorithm based on IAPF-LF is designed to avoid static and dynamic obstacles, the desired formation is maintained in the presence of external disturbances, and there is no Zeno behavior under the fixed-time event-triggered consensus control *** stability of the system is proved by the Lyapunov function and inequality scaling. Finally, simulation examples and water pool experiments are reported to verify the performance of the proposed theoretical algorithms.

关键词： Autonomous underwater vehicle(AUV) event-triggered control fixed-time consensus formation obstacle avoidance improved artificial potential field and leader-follower strategy(IAPF-LF)

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Advancing Long-Wavelength InGaN Micro-LEDs as Wavelength-Selective Detectors for White-Light Communication

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ACS Photonics 2024年第8期11卷 3390-3400页

作者： Lu, Tingwei Dai, Yurong Lee, Tzu-Yi Zheng, Xi Chen, Guolong Su, Yuhan Chen, Zhong Kuo, Hao-Chung Wu, Tingzhu Fujian Engineering Research Center for Solid-State Lighting Department of Electronic Science Xiamen University Xiamen361005 China National Integrated Circuit Industry and Education Integration Innovation Platform Department of Electronic Science Xiamen University Xiamen361005 China Department of Photonics Graduate Institute of Electro-Optical Engineering College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu30010 Taiwan

Long-wavelength InGaN-based microlight emitting diodes (μLEDs) have the potential for novel display and visible light communication (VLC). In this study, red and yellow μLEDs were fabricated for VLC applications as VLC transmitters and photodiodes (PDs). Stress modulation engineering and atomic layer deposition (ALD) techniques were employed to improve the transmission and detection performance. When operating as VLC transmitters, the red and yellow μLEDs exhibits high modulation bandwidth of 439.7 and 532.5 MHz at 2000 A/cm2, achieving a data rate of 1.9 and 2.4 Gbps, respectively. When operating as VLC PDs, long-wavelength emitting μLEDs with high indium component QW exhibit longer wavelength absorption edge, which is expected to achieve higher responsivity to blue light while filtering out the fluorescence component. The response spectra of the red and yellow μLED PDs overlap a large portion of the blue signal. The red and yellow μLEDs achieved responsivities of up to 0.208 and 0.135 A/W, respectively, for 450 nm light, higher than those of the reported InGaN LED-based photodetectors. In addition, owing to the wavelength selectivity, the long-wavelength μLED PDs could filter the slow fluorescence emission, thus achieving white light modulation bandwidth several times that achieved by adopting a silicon-based detector. A white-light VLC system was experimentally demonstrated. Maximum transmission rates of 1.2 and 1.05 Gbps were achieved based on red and yellow μLEDs operating as PDs, respectively. The findings of this study indicate that employing red μLED pixels as wavelength-selective PDs in future μLED information displays is an effective strategy for phosphor-based white-light communication. © 2024 American Chemical Society

关键词： Photodetectors

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Energy-efficient computation offloading assisted by RIS-based UAV

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The Journal of China Universities of Posts and Telecommunications 2024年第1期31卷 37-48页

作者： Li Linpei Zhao Chuan Su Yu Huo Jiahao Huang Yao Li Haojin School of Intelligence Science and Technology University of Science and Technology BeijingBeijing 100083China Institute of Artificial Intelligence University of Science and Technology BeijingBeijing 100083China Shunde Innovation School University of Science and Technology BeijingFoshan 528399China School of Computer and Communication Engineering University of Science and Technology BeijingBeijing 100083China Research Department of 5G and Drone China Mobile(Chengdu)Institute of Research and DevelopmentChengdu 610200China College of Communication Engineering Chengdu University of Information TechnologyChengdu 610225China Research and Development Center Sony(China)LimitedBeijing 100027China

The new applications surge with the rapid evolution of the mobile *** explosive growth of the data traffic aroused by the new applications has posed great computing pressure on the local *** is essential to innovate the computation offloading methods to alleviate the local computing burden and improve the offloading *** edge computing(MEC)assisted by reflecting intelligent surfaces(RIS)-based unmanned aerial vehicle(UAV)is a promising method to assist the users in executing the computation tasks in proximity at low *** this paper,we propose an energy-efficient MEC system assisted by RIS-based UAV,where the UAV with RIS mounted relays the computation tasks to the MEC *** energy efficiency maximization problem is formulated by jointly optimizing the UAV's trajectory,the transmission power of all users,and the phase shifts of the reflecting elements placed on the *** that the optimization problem is non-convex,we propose a deep deterministic policy gradient(DDPG)-based *** combining the DDPG algorithm with the energy efficiency maximization problem,the optimization problem can be ***,the numerical results are illustrated to show the performance of the system and the superiority compared with the benchmark schemes.

关键词： mobile edge computing unmanned aerial vehicle reflecting intelligent surface

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Epileptic seizure detection in EEG signals via an enhanced hybrid CNN with an integrated attention mechanism

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Mathematical Biosciences and engineering 2025年第1期22卷 73-105页

作者： Mekruksavanich, Sakorn Phaphan, Wikanda Jitpattanakul, Anuchit Department of Computer Engineering School of Information and Communication Technology University of Phayao Phayao56000 Thailand Department of Applied Statistics Faculty of Applied Science King Mongkut’s University of Technology North Bangkok Bangkok10800 Thailand Department of Mathematics Faculty of Applied Science King Mongkut’s University of Technology North Bangkok Bangkok10800 Thailand Intelligent and Nonlinear Dynamic Innovations Research Center Science and Technology Research Institute King Mongkut’s University of Technology North Bangkok Bangkok10800 Thailand

Epileptic seizures, a prevalent neurological condition, necessitate precise and prompt identification for optimal care. Nevertheless, the intricate characteristics of electroencephalography (EEG) signals, noise, and the want for real-time analysis require enhancement in the creation of dependable detection approaches. Despite advances in machine learning and deep learning, capturing the intricate spatial and temporal patterns in EEG data remains challenging. This study introduced a novel deep learning framework combining a convolutional neural network (CNN), bidirectional gated recurrent unit (BiGRU), and convolutional block attention module (CBAM). The CNN extracts spatial features, the BiGRU captures long-term temporal dependencies, and the CBAM emphasizes critical spatial and temporal regions, creating a hybrid architecture optimized for EEG pattern recognition. Evaluation of a public EEG dataset revealed superior performance compared to existing methods. The model achieved 99.00% accuracy in binary classification, 96.20% in three-class tasks, 92.00% in four-class scenarios, and 89.00% in five-class classification. High sensitivity (89.00–99.00%) and specificity (89.63–99.00%) across all tasks highlighted the model’s robust ability to identify diverse EEG patterns. This approach supports healthcare professionals in diagnosing epileptic seizures accurately and promptly, improving patient outcomes and quality of life. © 2025 American Institute of Mathematical sciences. All rights reserved.

关键词： Electroencephalography

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A Comprehensive Study of Plant Disease Detection Using Deep Learning Methods 1st

A Comprehensive Study of Plant Disease Detection Using Deep ...

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1st International Conference on Advanced Communication and Intelligent Systems, ICACIS 2022

作者： Haider, Kashan Prasandeep Ahmed, Maaz Pal, Ankit Rawat, Sur Singh Gupta, Vimal Shaw, Rabindra Nath Ghosh, Ankush Student Department of Computer Science and Engineering JSS Academy of Technical Education Noida201301 India Faculty Department of Computer Science and Engineering JSS Academy of Technical Education Noida201301 India University Center for Research and Development Chandigarh University Punjab India

ISBN: (纸本)9783031250873

Growing crops for human consumption and financial benefit is known as agriculture. It is the capability of using cutting-edge methods to cultivate crops and raise animals. As a result, the quality of the crop production is crucial to the development of the economy. In the agriculture industry, plant diseases and pests pose the biggest threat to crop production. Thus, it is essential to develop a method for accurately recognizing these illnesses so that the appropriate steps can be taken to treat them, increasing crop quality and quantity. A reliable disease detection system can be created by combining tools for classifying and extracting information with computer vision or image processing techniques employing deep learning. Different researchers have offered different approaches for identifying plant diseases. This study analyses these techniques. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Cultivation

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