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2nd International Conference on Microwave, Antenna and Communication, MAC 2024

作者： Priya, C. Ranganathan, Chitra Sabapathy Vetriselvi, D. Vanakamamidi, Rama Krishna Dhanalakshmi, S. Srinivasan, C. Department of Electronics and Communication Engineering Andhra Pradesh Puttur India Mphasis Corporation Tamil Nadu Chennai India SRM Institute of Science and Technology School of Computing Faculty of Engineering and Technology Department of Computing Technologies Tamil Nadu Chennai India HCL Technology Ltd Andhra Pradesh Vijayawada India Department of Computer Science and Engineering Tamil Nadu Namakkal India Saveetha University Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Computer Science and Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350350104

Effective connection quality is the basis of wireless network topology management and routing control. Effective link quality estimates may increase throughput and assure data transfer, extending the whole network's lifespan. Quality-of-service (QoS) routing is crucial in wireless networks to guarantee that data to be sent along a trusted channel and address the issue of energy balancing. This paper presents a Hybrid Cuckoo Search with a Fuzzy (HCSF) algorithm to improve the wireless network system. This mechanism uses the cuckoo search (CS) algorithm to select the neighbor nodes intelligently;as a result, it minimizes the routing overhead. Furthermore, it uses the fuzzy logic system to select the best forwarder from sender to receiver. Hence, it minimizes the network delay and packet loss ratio. The experimental outcomes using the Network Simulator tool significantly enhance the forward ratio and minimize the wireless network's routing overhead. © 2024 IEEE.

关键词： Quality of service

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Intelligent Forensic Investigation Using Optimal Stacked Autoencoder for Critical Industrial Infrastructures

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Computers, Materials & Continua 2022年第8期72卷 2275-2289页

作者： Abdullah S.AL-Malaise AL-Ghamdi Mahmoud Ragab F.J.Alsolami Hani Choudhry Ibrahim Rizqallah Alzahrani Information Systems Department Faculty of Computing and Information Technology King Abdulaziz UniversityJeddah21589Saudi Arabia Information Technology Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Centre of Artificial Intelligence for Precision Medicines King Abdulaziz UniversityJeddah21589Saudi Arabia Mathematics Department Faculty of ScienceAl-Azhar UniversityNaser City11884CairoEgypt Computer Science Department Faculty of Computing and Information Technology King Abdulaziz UniversityJeddah21589Saudi Arabia Biochemistry Department Faculty of ScienceKing Abdulaziz UniversityJeddah21589Saudi Arabia Computer Science and Engineering Department College of Computer Science and EngineeringUniversity of Hafr Al BatinAl JamiahHafar Al Batin39524Saudi Arabia

Industrial Control Systems(ICS)can be employed on the industrial processes in order to reduce the manual labor and handle the complicated industrial system processes as well as communicate *** of Things(IoT)integrates numerous sets of sensors and devices via a data network enabling independent *** incorporation of the IoT in the industrial sector leads to the design of Industrial Internet of Things(IIoT),which find use in water distribution system,power plants,*** the IIoT is susceptible to different kinds of attacks due to the utilization of Internet connection,an effective forensic investigation process becomes *** study offers the design of an intelligent forensic investigation using optimal stacked autoencoder for critical industrial *** proposed strategy involves the design of manta ray foraging optimization(MRFO)based feature selection with optimal stacked autoencoder(OSAE)model,named MFROFS-OSAE *** primary objective of the MFROFS-OSAE technique is to determine the presence of abnormal events in critical industrial ***-OSAE approach involves several subprocesses namely data gathering,data handling,feature selection,classification,and parameter ***,the MRFO based feature selection approach is designed for the optimal selection of feature ***,the OSAE based classifier is derived to detect abnormal events and the parameter tuning process is carried out via the coyote optimization algorithm(COA).The performance validation of the MFROFS-OSAE technique takes place using the benchmark dataset and the experimental results reported the betterment of the MFROFS-OSAE technique over the recent approaches interms of different measures.

关键词： Industrial control systems internet of things artificial intelligence feature selection deep learning

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On the convex hull of two planar random walks

arXiv

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arXiv 2024年

作者： Ivanković, Daniela Kralj, Tomislav Sandrić, Nikola Šebek, Stjepan University of Zagreb Faculty of Science Croatia University of Zagreb Faculty of Electrical Engineering and Computing Croatia

In this paper, we study the limiting behavior of the perimeter and diameter functionals of the convex hull spanned by the first n steps of two planar random walks. As the main results, we obtain the strong law of large numbers and the central limit theorem for the perimeter and diameter of these random *** Codes 60G50, 60D05, 60F05, 60F15 Copyright © 2024, The Authors. All rights reserved.

关键词： Random processes

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Spin-energy entanglement of a time-focused neutron

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Physical Review Applied 2024年第3期22卷 L031005页

作者： J.C. Leiner S.J. Kuhn S. McKay J.K. Jochum F. Li A.A.M. Irfan F. Funama D. Mettus L. Beddrich C. Franz J. Shen S.R. Parnell R.M. Dalgliesh M. Loyd N. Geerits G. Ortiz C. Pfleiderer R. Pynn Neutron Technologies Division Physik-Department Department of Physics Center for Exploration of Energy and Matter Institute for Quantum Computing Jülich Centre for Neutron Science JCNS Laboratory for Neutron Scattering and Imaging Faculty of Applied Sciences Chilton Oxfordshire OX11 0QX United Kingdom Atominstitut Quantum Science and Engineering Center Princeton New Jersey 08540 USA Center for Quantum Engineering (ZQE) Neutron Sciences Directorate

Intraparticle entanglement of individual particles such as neutrons could enable another class of scattering probes that are sensitive to entanglement in quantum systems and materials. In this work, we present experimental results demonstrating quantum contextuality as a result of entanglement between the spin and energy modes (i.e., degrees of freedom) of single neutrons in a beam using a pair of resonant radio-frequency neutron spin flippers in the modulated intensity with zero effort configuration. We verified the mode entanglement by measuring a Clauser-Horne-Shimony-Holt contextuality witness S defined in the spin and energy subsystems, observing a clear breach of the classical bound of |S|≤2, obtaining S=2.40±0.02. These entangled beams could enable alternative approaches for directly probing dynamics and entanglement in quantum materials whose low-energy excitation scales match those of the incident entangled neutron.

关键词： Entanglement detection Quantum correlations in quantum information Quantum metrology Quantum superposition Quantum fluids & solids Neutron scattering Neutron spin echo spectroscopy Time-of-flight neutron spectroscopy

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1 Formal Security Analysis of the AMD SEV-SNP Software Interface

arXiv

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arXiv 2024年

作者： Paradžik, Petar Derek, Ante Horvat, Marko University of Zagreb Faculty of Electrical Engineering and Computing Croatia University of Zagreb Faculty of Science Croatia

AMD Secure Encrypted Virtualization technologies enable confidential computing by protecting virtual machines from highly privileged software such as hypervisors. In this work, we develop the first, comprehensive symbolic model of the software interface of the latest SEV iteration called SEV Secure Nested Paging (SEV-SNP). Our model covers remote attestation, key derivation, page swap and live migration. We analyze the security of the software interface of SEV-SNP and formally prove that most critical secrecy, authentication, attestation and freshness properties do indeed hold in the model. Furthermore, we find that the platform-agnostic nature of messages exchanged between SNP guests and the AMD Secure Processor firmware presents a potential weakness in the design. We show how this weakness leads to formal attacks on multiple security properties, including the partial compromise of attestation report integrity, and discuss possible impacts and mitigations. Copyright © 2024, The Authors. All rights reserved.

关键词： Firmware

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An Enhanced Secure Authentication Scheme for the Internet of Things

An Enhanced Secure Authentication Scheme for the Internet of...

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2023 International Conference on Sustainable Emerging Innovations in engineering and Technology, ICSEIET 2023

作者： Neetu Srivastava, Animesh Barik, Lal Bihari Dhondiyal, Shiv Ashish College of Smart Computing Coer University Roorkee India Graphic Era Hill University Department of Computer Science & Engineering Dehradun India King Abdulaziz University Faculty of Computing and Information Technology in Rabigh Department of Information Systems Saudi Arabia Department of Computer Science & Engineering Dehradun India

ISBN: (纸本)9798350329186

The Internet of Things (IoT) has led to the proliferation of interconnected devices, including smart appliances and industrial sensors. Nevertheless, the rapid expansion of the IoT ecosystem has given rise to apprehensions regarding security, as compromised devices have the potential to result in data breaches and cyber assaults. This paper presents an enhanced secure authentication scheme for the Io'T, which aims to tackle the issues above by building upon existing authentication methodologies. The multi-step system commences with an initial setup phase wherein each loT device is assigned a unique device ID and a confidential pre-shared key. A secure key exchange protocol generates a session key for each authenticated device. The authentication server generates a random attempt to join the network or execute specific tasks. The machine then signs the data with its private key to authenticate the challenge. The server verifies the answer by comparing it with the public key signature of the device. The proposed methodology enables devices to update their session keys periodically to safeguard against potential attacks. © 2023 IEEE.

关键词： Authentication

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Resource Exhaustion Attack Detection Scheme for WLAN Using Artificial Neural Network

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Computers, Materials & Continua 2023年第3期74卷 5607-5623页

作者： Abdallah Elhigazi Abdallah Mosab Hamdan Shukor Abd Razak Fuad A.Ghalib Muzaffar Hamzah Suleman Khan Siddiq Ahmed Babikir Ali Mutaz H.H.Khairi Sayeed Salih Faculty of Engineering Future UniversityKhartoum 10553Sudan Faculty of Computing and Informatics Universiti Malaysia SabahKota Kinabalu88400Malaysia Information Assurance and Security Research School of ComputingUniversiti Teknologi MalaysiaJohor81310Malaysia School of Psychology and Computer Science University of Central LancashirePreston PR12HEUK Deaptement of Management Information Systems College of Administrative ScienceApplied Science UniversityAl Eker623Bahrain Deaptement of Information Technology College of Computer and Information SciencesKing Saud UniversityRiyadh11461Saudi Arabia

IEEE 802.11 Wi-Fi networks are prone to many denial of service(DoS)attacks due to vulnerabilities at the media access control(MAC)layer of the 802.11 *** to the data transmission nature of the wireless local area network(WLAN)through radio waves,its communication is exposed to the possibility of being attacked by illegitimate ***,the security design of the wireless structure is vulnerable to versatile *** example,the attacker can imitate genuine features,rendering classificationbased methods inaccurate in differentiating between real and false *** security standards have been proposed over the last decades to overcome many wireless network attacks,effectively detecting such attacks is crucial in today’s real-world *** paper presents a novel resource exhaustion attack detection scheme(READS)to detect resource exhaustion attacks *** proposed scheme can differentiate between the genuine and fake management frames in the early stages of the attack such that access points can effectively mitigate the consequences of the *** scheme is built through learning from clustered samples using artificial neural networks to identify the genuine and rogue resource exhaustion management frames effectively and efficiently in *** proposed scheme consists of four modules whichmake it capable to alleviates the attack impact more effectively than the related *** experimental results show the effectiveness of the proposed technique by gaining an 89.11%improvement compared to the existing works in terms of detection.

关键词： 802.11 media access control(MAC) wireless local area network(WLAN) artificial neural network denial-of-service(DoS)

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Analysis of Multi-Objective Integrated Management System of engineering Project Based on Ant Colony Algorithm 2

Analysis of Multi-Objective Integrated Management System of ...

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2nd IEEE International Conference on Distributed computing and Electrical Circuits and Electronics, ICDCECE 2023

作者： Qi, Rui Qi, Yongjun Tang, Hailin Guangzhou Institute of Science and Technology School of Architectural Engineering Guangdong China Guangdong Baiyun University Faculty of Megadata and Computing Guangdong China Mongolian University of Science and Technology Ulaanbaatar Mongolia

ISBN: (纸本)9798350347456

In the field of engineering construction, project management is a very important topic because it can promote the efficient development of the project. In the process of project investment decision-making, the core is the construction and operation of the whole project. This paper can systematically improve the management of engineering projects through ant colony algorithm. This paper mainly uses the methods of experimental analysis and principal component analysis to deeply study the multi-objective integrated management system of engineering project based on ant colony algorithm. The experimental data shows that at the quality level, the results of the two main factors meet the basic requirements, reaching more than 85%. The system can effectively improve the management efficiency and level of engineering projects, optimize the scheduling scheme of engineering projects, and improve the execution efficiency and quality of engineering projects. © 2023 IEEE.

关键词： Efficiency

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Ecosystem of Technologies for Smart Agriculture to Improve the Efficiency and Profitability of Indian Farmers 10

Ecosystem of Technologies for Smart Agriculture to Improve t...

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17th INDIACom;2023 10th International Conference on computing for Sustainable Global Development, INDIACom 2023

作者： Sugandh, Urvashi Nigam, Swati Khari, Manju Banasthali Vidyapith Faculty of Mathematics and Computing Department of Computer Science Banasthali India School of Computing Science Engineering Galgotias University Uttar Pradesh Greater Noida India School of Computer and System Sciences Jawaharlal Nehru University New Delhi India

ISBN: (纸本)9789380544472

An increasing population demands more food, but the available resources are shrinking. The agriculture sector in India is facing several challenges such as climate change, water scarcity, soil degradation, and declining farm profitability. To address these challenges, there is a growing need for the adoption of smart agriculture practices that leverage technology. This paper presents an overview of the ecosystem of technologies for smart agriculture and their potential to improve the efficiency and profitability of Indian farmers. The paper explores the role of various technologies such as precision agriculture, IoT, artificial intelligence, drones, and robotics in improving crop yields, reducing input costs, and enhancing overall farm management. Additionally, the paper discusses the challenges that need to be overcome to ensure the successful adoption of smart agriculture technologies in India. These include the lack of awareness and access to technology, inadequate infrastructure, and limited availability of financing. The paper concludes that the ecosystem of technologies for smart agriculture holds significant promise for Indian farmers to overcome the challenges and improve the efficiency and profitability of their farms. © 2023 Bharati Vidyapeeth, New Delhi.

关键词： Profitability

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Multilevel Artificial Intelligence-Based Authentication System with Anti-spoofing Technique 9th

Multilevel Artificial Intelligence-Based Authentication Syst...

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9th International Conference on Cyber Security, Privacy in Communication Networks, ICCS 2023

作者： Kamarudin, Nazhatul Hafizah Ilyas, M.A. Zulkifli, Nor Saradatul Akmar Sallehudin, Hasimi Faculty of Information Science and Technology Universiti Kebangsaan Malaysia Selangor Bangi43600 Malaysia Department of Electrical and Electronic Engineering Faculty of Engineering Technology and Built Environment UCSI University Cheras Kuala Lumpur56000 Malaysia Faculty of Computing Universiti Malaysia Pahang Al-Sultan Abdullah Pahang Pekan26600 Malaysia

ISBN: (纸本)9789819739721

Security concerns have long been a focal point in the realm of authentication systems, particularly within the context of single-level authentication systems. Password-based authentication, in particular, is recognized as vulnerable due to its susceptibility to bypass by malicious attackers. To strengthen security and enhance authentication processes, a multilevel authentication system incorporating biometric authentication is proposed. Among the biometric methods, face recognition stands out as a robust choice. To fortify the security of face recognition, the integration of face anti-spoofing measures is crucial to detect potential attacks such as printed image and replay attacks. To implement this multifaceted authentication system, the study employs convolutional neural networks (CNNs) as a machine learning method for both face recognition and face anti-spoofing. This approach enhances the system’s security and ensures the integrity of the authentication process. In summary, this study introduces a novel multilevel authentication system that combines traditional single-level password authentication with a secondary layer of face recognition authentication, fortified by face spoofing detection. The development, dataset generation, and model training are performed using the Visual Studio Code integrated development environment (IDE). Additionally, the system is structured within the web framework Django, providing a robust foundation for its deployment and usability. The proposed multilevel authentication system, combining password-based security with face recognition and anti-spoofing detection, demonstrates outstanding accuracy in training results despite a relatively small dataset size. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Authentication Protocol

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