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7th International Conference on Artificial Intelligence in Renewable Energetic Systems, IC-AIRES 2023

作者： Touhami, Sana Belghachi, Mohamed Touhami, Achouak Department of Mathematics and Computer Science Tahri Mohammed University Bechar Algeria Department of Mathematics and Computer Science Ali Kafi University Center Tindouf Algeria Information and Telecommunication Laboratory Tahri Mohamed University Bechar Algeria Energetic in Arid Zones Laboratory Tahri Mohamed University Bechar Algeria

ISBN: (纸本)9783031606281

Wireless sensor networks (WSN) are considered as one of the most widely used networks for all-inclusive applications. They are organized into many sensor nodes. The deployment of nodes in these networks is not secure, and this may lead to security attacks. In this paper we are deliberating different types of attacks in network layer and defensive mechanisms against those attacks. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Network layers

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Modeling and Clustering of Parabolic Granular Data

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第7期5卷 3728-3742页

作者： Tang, Yiming Gao, Jianwei Pedrycz, Witold Hu, Xianghui Xi, Lei Ren, Fuji Hu, Min Hefei University of Technology Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine School of Computer and Information Hefei230601 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6R 2V4 Canada Hefei University of Technology School of Computer and Information Hefei230601 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 2R3 Canada Polish Academy of Sciences Systems Research Institute Warsaw00-901 Poland Istinye University Research Center of Performance and Productivity Analysis Istanbul34010 Turkey Southeast University School of Computer Science and Engineering Nanjing211189 China University of Electronic Science and Technology of China School of Computer Science and Engineering Sichuan Chengdu611731 China

At present, there exist some problems in granular clustering methods, such as lack of nonlinear membership description and global optimization of granular data boundaries. To address these issues, in this study, revolving around the parabolic granular data, we propose an overall architecture for parabolic granular modeling and clustering. To begin with, novel coverage and specificity functions are established, and then a parabolic granular data structure is proposed. The fuzzy c-means (FCM) algorithm is used to obtain the numeric prototypes, and then particle swarm optimization (PSO) is introduced to construct the parabolic granular data from the global perspective under the guidance of principle of justifiable granularity (PJG). Combining the advantages of FCM and PSO, we propose the parabolic granular modeling and optimization (PGMO) method. Moreover, we put forward attribute weights and sample weights as well as a distance measure induced by the Gaussian kernel similarity, and then come up with the algorithm of weighted kernel fuzzy clustering for parabolic granularity (WKFC-PG). In addition, the assessment mechanism of parabolic granular clustering is discussed. In summary, we set up an overall architecture including parabolic granular modeling, clustering, and assessment. Finally, comparative experiments on artificial, UCI, and high-dimensional datasets validate that our overall architecture delivers a good improvement over previous strategies. The parameter analysis and time complexity are also given for WKFC-PG. In contrast with related granular clustering algorithms, it is observed that WKFC-PG performs better than other granular clustering algorithms and has superior stability in handling outliers, especially on high-dimensional datasets. © 2020 IEEE.

关键词： Fuzzy clustering

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E-commerce Scheme Based on Proxy t-out-of-n Oblivious Signature

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International Journal of Network Security 2024年第5期26卷 851-860页

作者： Chen, Jingyu Gong, Linming Ma, Xiangxiang Wang, Daoshun The Shaanxi Key Laboratory of Clothing Intelligence School of Computer Science Xi’an Polytechinic University Xi’an710048 China State and Local Joint Engineering Research Center for Advanced Networking and Intelligent Information Services School of Computer Science Xi’an Polytechnic University Shaanxi Xi’an710048 China Department of Computer Science and Technology Tsinghua University Beijing100084 China No. 58 Shan-gu Road Lintong Xi’an710600 China

With the development of the internet and the demand for online shopping, intelligent online shopping systems have received widespread attention in recent years. However, existing online shopping systems’ security and privacy issues have not been well addressed. This article proposes a shopping scheme based on proxy t-out-of-n oblivious signatures, which uses t-out-of-n oblivious signature technology to ensure that users select multiple messages from a predetermined set of messages, ensuring the legality and privacy of the selection while using proxy signature technology to provide the attribute of signature unforgeability. We have analyzed the correctness of the proposed scheme and demonstrated its security in terms of integrity, unforgeability, confidentiality of selected messages, selection restriction, non-repetitive, verifiability, distinguishability, non-repudiation, and prevention of abuse. Our scheme has lower computational and communication costs than other oblivious signature schemes. In addition, the privacy-preserving multi-choice shopping scheme we propose enables users to shop more securely and conveniently. © (2024), (International Journal of Network Security). All rights reserved.

关键词： Differential privacy

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Critical Infrastructure Security Goes to Space: Leveraging Lessons Learned on the Ground

Critical Infrastructure Security Goes to Space: Leveraging L...

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Accelerating Space Commerce, Exploration, and New Discovery Conference, ASCEND 2023

作者： Ellis, Tim Hitaj, Briland Lindqvist, Ulf Shands, Deborah Tinnel, Laura DeBruhl, Bruce Computer Science Laboratory SRI International California Polytechnic State University United States Computer Science and Software Engineering Department California Polytechnic State University United States

ISBN: (数字)9781624107054

ISBN: (纸本)9781624107054

Space systems enable essential communications, navigation, imaging and sensing for a variety of domains, including agriculture, commerce, transportation, and emergency operations by first responders. Protecting the cybersecurity of these critical infrastructure systems is essential. While the space environment brings unique constraints to managing cybersecurity risks, lessons learned about risks and effective defenses in other critical infrastructure domains can help us to design effective defenses for space systems. In particular, discoveries regarding cybersecurity for industrial control systems (ICS) for energy, manufacturing, transportation, and the consumer and industrial Internet of Things (IoT) offer insights into cybersecurity for the space domain. This paper provides an overview of ICS and space system commonalities, lessons learned about cybersecurity for ICS that can be applied to space systems, and recommendations for future research and development to secure increasingly critical space systems. © 2023, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Cybersecurity

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Efficient and Lightweight Framework for Confidential Medical Image Search using Edge Computing 2

Efficient and Lightweight Framework for Confidential Medical...

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2nd International Conference on Computational Intelligence and Network Systems, CINS 2024

作者： Rajan, Arun Amaithi Vetriselvi, V. Aishwarya, R. Rajan, Anitha Amaithi Security Research Laboratory Department of Computer Science and Engineering College of Engineering Guindy Anna University Tamil Nadu Chennai600025 India Department of Computer Science and Business Systems Francis Xavier Engineering College Tamil Nadu Tirunelveli627011 India

ISBN: (纸本)9798331504106

In healthcare, medical images are playing a major role in accurate diagnosis. Cloud storage for medical images creates security risks and latency due to some critical vulnerabilities and their distance from data sources. By bringing computation closer to the source, edge computing improves efficiency, still edge servers cannot be trusted blindly, requiring robust security measures. In this article, an efficient and lightweight framework for secure medical image search and retrieval that leverages edge computing is proposed. Here, Medical images are encrypted and similarity-preserving hashcodes are generated locally at the source, which are sent to a trusted master edge server. Before being stored, searchable hashcodes undergo homomorphic encryption, allowing for secure computations on encrypted data. The master edge server generates n shares of the encrypted images by applying a Learning With Errors (LWE) based image sharing scheme and distributing them across nearby edge devices. During retrieval, to ensure resilience against device compromise, m out of n shares are used to reconstruct the image. The master edge server retrieves and reconstructs the top k relevant images in response to the query image. This framework enhances security and efficiency by reducing reliance on cloud storage and enabling secure processing on edge servers, making it ideal for modern healthcare environments. The efficiency and security of the proposed framework are proved theoretically and experimentally. Hence, it proved that the framework is performing better than existing state-of-the-art models. ©2024 IEEE.

关键词： Electronic health record

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Heterogeneous UPF Integration Framework and 5G User Plane Acceleration 24

Heterogeneous UPF Integration Framework and 5G User Plane Ac...

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24th Asia-Pacific Network Operations and Management Symposium, APNOMS 2023

作者： Wang, Tse-Han Hu, Min-Chih Yen, Li-Hsing Tseng, Chien-Chao Department of Computer Science College of Computer Science National Yang Ming Chiao Tung University Hsinchu Taiwan Network Management Laboratory Chunghwa Telecom Laboratories Taoyuan Taiwan

ISBN: (纸本)9788995004395

The 3rd Generation Partnership Project (3GPP) proposes User Plane Function (UPF) in the fifth generation (5G) mobile networks to handle user data between radio access network (RAN) and data network (DN). Since pure software-based UPF does not fulfill the diversified service requirements of 5G networks, researchers have leveraged various hardware acceleration techniques to enhance the performance of UPF. However, different hardware implementations require different installations and adaptations. This paper proposes a framework to integrate various UPF implementations. It is compliant with standard UPF but decouples the control plane function (UPF-CP) from the user plane function (UPF-UP). We implemented UPF-CP by Packet Forwarding Control Protocol (PFCP) Agent with two implementations of UPF-UP: one with Intel Data Plane Development Kit (DPDK) and the other with Smart Network Interface Card (SmartNIC). We integrated the framework with an open-source 5G core network, free5GC, and evaluated the framework by experiments. The results confirm the interoperability of our work with free5GC and demonstrate the superiority of the hardware-accelerated UPF over pure software approach in terms of packet processing speed on the user plane. Copyright 2023 KICS.

关键词： 5G mobile communication systems

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Assessing radiographic findings on finger X-rays using an enhanced deep learning approach

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International Journal of Information Technology (Singapore) 2024年第7期16卷 4279-4288页

作者： Kumar, Rahul K, Suganya Devi Mohapatra, Devi Prasad Medical Imaging Laboratory Department of Computer Science and Engineering National Institute of Technology Assam Silchar 788010 India Department of Plastic Surgery JIPMER Puducherry 605006 India

The human upper extremity, which includes the shoulder, humerus, elbow, forearm, wrist, hand, and fingers, demonstrates incredible biological complexity, enabling us to make crucial and intricate movements in our daily lives. Due to its delicate construction, it is prone to a variety of fractures and injuries. Radiologists utilize a combination of visual perception, memory, pattern recognition, and cognitive reasoning when interpreting radiographic studies. However, a variety of circumstances, including clinical staff shortages, a lack of skilled radiologists, heavy caseloads, and continual distractions, can all hurt their performance, resulting in higher workloads, fatigue, wrong detection rates, and weariness. Addressing these challenges, our study introduced a novel approach employing an advanced deep learning model to enhance the accuracy and efficiency of diagnosing finger radiograph abnormalities. In this work, a modified DenseNet hybrid architecture was proposed for classifying abnormalities in finger radiographs. These models were trained using the finger dataset, a subset of the extensive Musculoskeletal Radiographs (MURA) dataset. The improved performance indicators for our proposed model over the current benchmark models demonstrated the model's effectiveness. The proposed models exhibited superior performance in Cohen's kappa metrics for classifying abnormalities in finger radiographs on the test dataset, outperforming other benchmark models. The advanced deep learning model based on DenseNet architecture showcased the promising potential for automating the classification of abnormalities in finger radiographs. © Bharati Vidyapeeth's Institute of computer Applications and Management 2024.

关键词： Convolutional neural network Deep learning DenseNet Finger radiographs Fracture detection Medical imaging

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Language Agnostic Approach for Unification of Implementation Variants for Different Computing Devices 14th

Language Agnostic Approach for Unification of Implementati...

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14th International Conference on Parallel Processing and Applied Mathematics, PPAM 2022

作者： Dubey, Anshu Klosterman, Tom Mathematics and Computer Science Division Argonne National Laboratory LemontIL60439 United States Department of Computer Science University of Chicago ChicagoIL60637 United States

ISBN: (纸本)9783031304415

Scientific software used on high performance computing platforms is in a phase of transformation because of combined increase in the heterogeneity and complexity of models and hardware platforms. Having separate implementations for different platforms can easily lead to combinatorial explosion, therefore, computational science community has been looking for mechanisms to express code through abstractions that can be specialized for different platforms. Some approaches have met success through the use of template meta-programming in C++. However, their reliance upon C++ makes these approaches inaccessible to non C++ codes. In this paper, we describe a language agnostic methodology using macros that not only mimics the behavior of templates as applied in the abstractions, but also allows the use of code components as building blocks to explore implementation variants. We have successfully applied this methodology to Flash-X, a new multiphysics multicomponent code with many Fortran legacy components. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Program assemblers

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A bytecode-based integrated detection and repair method for reentrancy vulnerabilities in smart contracts

IET Blockchain

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IET Blockchain 2024年第3期4卷 235-251页

作者： Feng, Zijun Feng, Yuming He, Hui Zhang, Weizhe Zhang, Yu School of Cyberspace Science Harbin Institute of Technology Harbin China School of Computer Science and Technology Harbin Institute of Technology Shenzhen China Department of New Networks Peng Cheng Laboratory Shenzhen China Guangdong Provincial Key Laboratory of Novel Security Intelligence Technologies Shenzhen China

The reentrancy vulnerability in smart contracts has caused significant losses in the digital currency economy. Existing solutions for detecting and repairing this vulnerability are limited in scope and lack a comprehensive framework. Additionally, there is currently a lack of guidance methods for effectively pinpointing the location of vulnerabilities. The proposed bytecode-level method addresses these challenges by incorporating a detection module, an auxiliary localization module, and a repair module. An opcode classification method is introduced using vulnerability features and a BiLSTM-Attention-based sequence model to enhance detection accuracy. To overcome difficulties in vulnerability localization, an auxiliary localization method based on data flow and control flow analysis is proposed, enabling developers to better locate vulnerabilities. Current reentrancy vulnerability repair methods are analyzed and strategies for three reachable patterns are proposed. The bytecode rewriting strategy utilizes Trampoline technology for repair, while a fuel optimization method reduces bytecode generation length to optimize gas costs. Through extensive experimental validation, the effectiveness and superiority of the proposed methods are confirmed, further validating the feasibility of the entire framework. Experimental results demonstrate that the framework offers enhanced protection against reentrancy vulnerability attacks in smart contracts. © 2023 The Authors. IET Blockchain published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology.

关键词： Smart contract

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Adapting the Simulated Annealing Algorithm to Enhance the Performance of the LEACH Protocol

Adapting the Simulated Annealing Algorithm to Enhance the Pe...

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2024 International Conference on computer and Applications, ICCA 2024

作者： Benhadji, Mohammed Mohammed, Kaddi Mohammed, Omari Material Sciences Department Algeria University of Adrar Lddi Laboratory Mathematics and Computer Science Department Algeria American University of Ras Al Khaimah Computer Science and Engineering Department P.O.Box 10021 Ras Al Khaimah United Arab Emirates

ISBN: (纸本)9798350367560

In parallel with the proliferation and extension of wireless sensor networks (WSNs), as well as the diversity of their applications, such networks continue to fail to operate for lengthy periods of time due to node failure and the inability to replace sensor batteries in most circumstances. This hinders the networks' ability to remain operational over extended periods. That necessitates making the best and most efficient use of the nodes' energy. Hierarchical clustering methods augmented with metaphysical algorithms have produced amazing benefits in terms of network longevity. One of the most significant of these algorithms that draws inspiration from nature and yields excellent results is the simulated annealing technique. In this research, we report on our analysis of this method and how it performs best when used to optimize routing in WSN. © 2024 IEEE.

关键词： Simulated annealing

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