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Optimized Biometric Authentication using MTCNN and Dynamic Signature Detection: A Unified Approach for Enhanced security

Optimized Biometric Authentication using MTCNN and Dynamic S...

引用

distributed systems, computer networks and Cybersecurity (ICDSCNC), international conference on

作者： Sunil S Harakannanavar G V. Jayasree Keerthana Shubha K Srushti S. K Department of Electronics and Communication Engineering Nitte Meenakshi Institute of Technology Bangalore India

ISBN: (数字)9798350375442

ISBN: (纸本)9798350375459

Automatic photo and signature detection using MTCNN (Multi-task Cascaded Convolutional networks) is a vital component in various applications such as identity verification and document processing. MTCNN, initially designed for face detection, has been adapted to detect signatures and other features with remarkable accuracy. Performance metrics including precision, recall, F1-score, and accuracy are used to evaluate its effectiveness. In photo detection, MTCNN exhibits high precision, recall, and accuracy, making it suitable for tasks like facial recognition and person identification. In signature detection, while precision, recall, and accuracy remain moderate to high, MTCNN proves adept at recognizing signatures in documents and forms and the model performs results better with an accuracy of 98.65%.

关键词： Measurement Handwriting recognition Accuracy Face recognition Feature extraction Multitasking Software Face detection Convolutional neural networks computer security

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Ensuring Data security and Routing Efficiency in Warehouse Sensor networks Using Wireless Blockchain Technology 11th

Ensuring Data Security and Routing Efficiency in Warehouse S...

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11th international conference on Intelligent Computing and Applications, ICRTC 2023

作者： Anitha Rajakumari, P. Karthick, S. Mahapatra, Rajendra Prasad Parwekar, Pritee Department of Computer Science and Engineering SRM Institute of Science and Technology Delhi-NCR Campus Ghaziabad India

ISBN: (纸本)9789819717231

The integration of wireless sensor networks (WSNs) and blockchain technology has gained significant attention in recent years due to its potential in addressing security and privacy concerns in various applications. In this paper, we propose blockchain technology with wireless-based secure warehouse system (BCWS2) that leverages wireless blockchain technology along with an efficient routing policy to ensure data integrity, authenticity, and confidentiality in a warehouse environment. The proposed system consists of a network of battery-powered wireless sensors deployed within the warehouse premises to monitor various environmental parameters such as temperature, humidity, and light levels. These sensors collect data and transmit it securely to a blockchain network using cryptographic techniques to prevent unauthorized access and tampering. The blockchain network, powered by smart contracts, acts as a decentralized ledger, ensuring the immutability and transparency of the collected sensor data. Each sensor node contributes to the blockchain by forming a consensus on the validity of the data through a distributed consensus protocol. This enables secure and tamper-proof storage of the collected data, eliminating the need for a central authority or trusted intermediary. In order to enhance routing efficiency within the warehouse sensor network, we present a highly efficient routing policy that leverages machine learning algorithms. Our proposed routing policy aims to optimize the path selection process, ensuring effective and streamlined communication within the network. The policy dynamically adjusts the routing paths based on the current network conditions, such as node congestion, battery levels, and signal strength. The proposed routing approach significantly enhances network performance, minimizes energy consumption, and guarantees prompt delivery of sensor data to the blockchain network. This system effectively tackles various challenges encountered in conventiona

关键词： Blockchain

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A Comparative Study of Neural networks Algorithms in Cyber-security to Detect Domain Generation Algorithms Based on Mixed Classes of Data

A Comparative Study of Neural Networks Algorithms in Cyber...

引用

international conference on Advanced Intelligent systems for Sustainable Development, AI2SD 2022

作者： Hassaoui, Mohamed Hanini, Mohamed El Kafhali, Said Hassan First University of Settat Settat Morocco

ISBN: (纸本)9783031352508

Domain Generation Algorithms (DGAs) are often used to generate huge amounts of domain names to maintain command and control (C2) between the infected computer and the master bot. Blacklist approaches become ineffective way to detect DGA as the number of domain names to block are large and vary over time. Since DGAs are unexpectedly distributed, conventional approaches have trouble detecting DGAs. Several deep learning architectures that accept a series of characters as a raw input signal and automatically classify them have recently been suggested. This paper compares three neural network algorithms in cyber security systems to detect domain generation algorithm, in particular, long-short-term memory (LSTM), convolution neural network (CNN) and bidirectional long-short-term memory (biLSTM). We examine in detail these three neural network algorithms for detecting DGAs based on mixed classes of DGA data containing more than 30 classes of DGAs, and we discuss the drawbacks and strengths of each method. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Long short-term memory

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Optimization of Data Encryption Algorithms in Information Construction

Optimization of Data Encryption Algorithms in Information Co...

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distributed systems, computer networks and Cybersecurity (ICDSCNC), international conference on

作者： Shuai Zhu Yi You Bo Zhou Chuanting Chen Xueqin Yi Network Information Center Hankou University Wuhan China School of Computer Science and Technology Hankou University Wuhan China Library and Information Center Wuhan University of Engineering Science Wuhan China School of Music Hankou University Wuhan China Board Office Hankou University Wuhan China

ISBN: (数字)9798350375442

ISBN: (纸本)9798350375459

Data encryption algorithms play a crucial role in information construction, effectively protecting data security. The problems in traditional research include a lack of targeting, a balance between efficiency and safety, and a lack of comprehensive consideration. Therefore, this article proposed targeted optimization strategies and methods by in-depth analyzing the needs and scenarios of information construction, combined with the characteristics and problems of data encryption algorithms. Meanwhile, this article also comprehensively considered the integration, deployment, management, and maintenance of algorithms to achieve optimal matching and collaborative work between algorithms and information systems. Through research, this article aimed to promote the application and development of data encryption algorithms in information construction, and improve the efficiency, security, and availability of data encryption algorithms in protecting data security. The results showed that the efficiency of the data encryption algorithm based on RSA (Rivest-Shamir-Adleman) reached the highest of 89.6%. This article provides strong support for the application and development of data encryption algorithms, promoting the sustainable development of information construction and the protection of data security.

关键词： Protocols Data security distributed databases Encryption Protection Sustainable development Optimal matching Optimization Standards Information systems

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6G Enabled Smart IoT in Healthcare System: Prospect, Issues and Study Areas 1

6G Enabled Smart IoT in Healthcare System: Prospect, Issues ...

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1st international conference on Artificial Intelligence for Innovations in Healthcare Industries, ICAIIHI 2023

作者： Matre, Priti Vivek Kumbhare, Ashish Gedam, Ravi Sharma, Animesh Vaishnav, Naveen Kumar Naidu, Dileep Yashwantrao Chavan College of Engineering Dept. of Information Technology Maharashtra Nagpur India The Icfai University Faculty of Science and Technology Chhattisgarh Raipur India G H Raisoni University Department of Computer Science and Engineering Madhya Pradesh Saikheda India

ISBN: (纸本)9798350330915

The Internet of Medical Things, (IoMT) requires extensive and intelligent connection, enormous bandwidth, minimal latency, extremely high data rates, and enhanced healthcare experiences. In contrast to the current 5G wireless systems, the next 6G communication system is anticipated to offer Smart IoMT (SIoMT) solutions all over at any moment to enhance people's quality of life. The conceptual structure of 6G networks, their integration with multifaceted networking technologies like wireless optical networks, cell-free communication systems, and quantum telecommunications, in addition to the decentralised protection framework in the context of SIoMT, are presented in this paper. A novel concept for linking households to hospitals, healthcare personnel, healthcare supplies, healthcare facilities etc. will be enabled by such low latency and ultra-high-speed communication networks. The paper also discusses the obstacles and future research directions of installing SIoMT, as well as the needs of 6G wireless networking along with additional important critical approaches. © 2023 IEEE.

关键词： 5G wireless network 6G communication system distributed security Internet of Everything (IoE) Internet of Healthcare Things machine learning Quantum communication

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Intrusion Detection in Wireless Sensor networks using Machine Learning 4

Intrusion Detection in Wireless Sensor Networks using Machin...

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4th international conference on Evolutionary Computing and Mobile Sustainable networks, ICECMSN 2024

作者： Fares, Hajar Vibhute, Amol D. Mouniane, Yassine Bouijij, Habiba Equipe of Telecommunication and Detection Faculty of Science Abdelmalek Essaadi University Tetouan Morocco MH Pune411016 India Natural Resources and Sustainable Development Laboratory Faculty of Sciences Ibn Tofail University B.P 242 Kenitra Morocco ENSIAS SSLAB Mohammed v University in Rabat Rabat Morocco

Attackers are continuously enhancing their techniques to attack confidential data. Thus, the classical security solutions based on cryptography and older detection systems must be revised, especially for a network dataset. Wireless sensor networks (WSN) consist of several smart devices distributed randomly in hostile areas with many restrictions, such as low operational time, short memory and minimal energy resources, and are susceptible to numerous attacks, such as Denial-of-Service (DoS). Recently, intrusion detection based on artificial intelligence models has provided an alternative and efficient solution with low computational resources. Therefore, the present study provides an innovative approach for detecting DoS attacks in the network using machine learning. Three machine learning methods, such as Support Vector Machine (SVM), K-Nearest Neighbor (KNN) and decision tree, were implemented with a well-known WSN-DS data specialized for DoS attacks. The performance of the models has been evaluated using standard metrics like accuracy, precision, F1-score and recall. The experimental results demonstrated the effectiveness of the KNN model after achieving the highest accuracy of 99.76% in DoS detection. Thus, the present study's approach can be used in real-time intrusion detection. © 2025 The Authors. Published by Elsevier B.V.

关键词： Network intrusion

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4th international conference on Information Science, Parallel and distributed systems, ISPDS 2023

作者： Zhou, Ya Zhao, Ning Huang, Guimin Deng, Nanxiao Guo, Qingkai School of Computer Science and Information Security Guilin University of Electronic Technology Guangxi Key Laboratory of Image and Graphic Intelligent Processing Guilin China

ISBN: (纸本)9798350337181

In sentence similarity research methods, sentence similarity is often calculated from semantic aspects, however, the influence of other features is ignored. For example, the influence of sentence syntactic structure and word order on sentence similarity is not considered. Therefore, This paper proposes a method to measure the degree of similarity between sentences based on a multi-feature fusion of semantics, syntactic similarity and word order similarity, respectively. For the aspect of semantic similarity, in this paper, we first preprocess the sentence and obtain the word vectors, and then obtains sentence vector features through neural networks, so as to calculate the sentence semantic similarity;Finally, for the aspect of word order similarity, word order is considered as the auxiliary feature information to calculate sentence similarity since word order has a smaller effect on sentence similarity compared to the above information. The experimental results show that the proposed model has an accuracy of 77.4 % and an F1 value of 84.3% on the MRPC dataset. © 2023 IEEE.

关键词： Semantics

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A Robust Remote User Authentication Scheme for Supply Chain Management Using Blockchain Technology

A Robust Remote User Authentication Scheme for Supply Chain ...

引用

international conference on Data Science and Network Engineering, ICDSNE 2023

作者： Singh, Inderpal Singh, Balraj Rana, Arun Kumar School of Computer Science and Engineering Phagwara India Lovely Professional University Punjab Phagwara India Galgotia College of Engineering Uttar Pradesh Greater Noida India

ISBN: (纸本)9789819967544

For a company’s product life cycle to be faster, more efficient, and more effective, supply chain management (SCM) is critical. Nevertheless, present SCM systems must be improved to ensure genuine products and transactions are private and secure. As a result, this study proposes a safe SCM system depending upon blockchain and the Internet of Things to ensure that the products are genuine. All SCM stakeholders can initiate an encrypted, secure transaction for their goods or services due to the Quick Response (QR) scanner that works with the Internet of Things (IoT) and the blockchain-integrated distributed system. Finally, a genuine product from the manufacturer will be sent to the customer. To make authentication quicker and easier for scattered IoT devices, a lightweight asymmetric key encryption mechanism known as Diffie-Hellman key exchange and Hyperledger Fabric-based blockchain technology with on-chain smart contracts are deployed. The service provider registers each SCM stakeholder and provides them with their own public and private keys, which will be used to authenticate participants and IoT devices. Examining security and scalability shows that the recommended solution is more trustworthy and secure than existing methods. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Blockchain

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Decentralized Road Conditions Assessment for Smart Mobility Management in Abu Dhabi 19

Decentralized Road Conditions Assessment for Smart Mobility ...

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19th IEEE international Wireless Communications and Mobile Computing (IEEE IWCMC)

作者： Albasir, A. Ben-Othman, J. Zayed Univ Coll Technol Innovat CTI Dubai U Arab Emirates Univ Paris Saclay CNRS Cent Supelec Paris France Univ Sorbonne Paris Nord Villetaneuse France

ISBN: (纸本)9798350333398

Mobility management is crucial for urban planning, and accurate road condition information is necessary for safe and efficient transportation. In the context of this study, mobility refers to the quality of the road and the level of service provided to road users. To this end and to advance the state-of-the-art in improving mobility management strategies, we propose a new capability for our ongoing work on the Decentralized Road Traffic Monitoring (DRTM) system: road conditions assessment, aimed at enhancing mobility management for Abu Dhabi city. Our DRTM system uses smartphone cameras, Vehicular Ad-hoc networks (VANETs) on vehicle-to-vehicle (V2V) mode, and federated learning to extract and classify road features, such as potholes, cracks, and accidents, impacting overall mobility. The system comprises a smartphone app and a decentralized network of participants, providing real-time insights about road conditions. Our experimental results demonstrate the system's effectiveness in providing precise and up-to-date information about road conditions, with increased scalability and efficiency compared to centralized methods. By utilizing federated learning, the system ensures data security and privacy.

关键词： Mobility Management Intelligent Transportation systems distributed Traffic Monitoring computer Vision Federated Learning Object Detection

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Protecting Bitcoins Frequency Count Against Double-Spend Attacks 5

Protecting Bitcoins Frequency Count Against Double-Spend Att...

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5th international conference on Smart systems and Inventive Technology, ICSSIT 2023

作者： Nisha, M. Sharon Rajakumar, G. Jenifer, P. Benita, B. Department of Computer Science and Engineering Francis Xavier Engineering College Tamil Nadu Tirunelveli India Department of Electronics and Communication Engineering Francis Xavier Engineering College Tamil Nadu Tirunelveli India

ISBN: (纸本)9781665474672

Bitcoin is a distributed cryptocurrency that verifies transactions using the Proof-of-Work system. It is now being accepted as payment by an increasing number of establishments, particularly quick-service restaurants and vending that must quickly satisfy orders. Unfortunately, given the correct circumstances, such as quick payments, a Bitcoin double expenditure scam may occur. Finding scalable and simple to-install defenses against such assaults is essential since consumers shouldn't be responsible for paying the price for cyberattacks. In an earlier study, some potential countermeasures were published without enough thought. In this study, they use the Shadow framework to predict the outcomes of deploying these security measures in a sizable Bitcoin P2P network. Our model shows that if an upgraded observer combines these countermeasures, a vendor may be informed of a double-spend assault in much less than 28 milliseconds on average. © 2023 IEEE.

关键词： Peer to peer networks

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