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AI-enabled dental caries detection using transfer learning and gradient-based class activation mapping

Journal of Ambient Intelligence and Humanized Computing 2024年第7期15卷 3009-3033页

作者： Inani, Hardik Mehta, Veerangi Bhavsar, Drashti Gupta, Rajeev Kumar Jain, Arti Akhtar, Zahid Department of Computer Science and Engineering Pandit Deendayal Energy University Gujarat Gandhinagar India Department of Computer Science and Engineering and Information Technology Jaypee Institute of Information Technology Uttar Pradesh Noida India Department of Network and Computer Security State University of New York Polytechnic Institute NY United States

Dental caries detection holds the key to unlocking brighter smiles and healthier lives by identifying one of the most common oral health issues early on. This vital topic sheds light on innovative ways to combat tooth decay, empowering individuals to take control of their oral health and maintain radiant smiles. This research paper delves into the realm of transfer learning techniques, aiming to elevate the precision and efficacy of dental caries diagnosis. Utilizing Keras ImageDataGenerator, a rich and balanced dataset is crafted by augmenting teeth images from the Kaggle teeth dataset. Five cutting-edge pre-trained architectures are harnessed in the transfer learning approach: EfficientNetV2B3, VGG19, InceptionResNetV2, Xception, and ResNet50, with each model, initialized using ImageNet weights and tailored top layers. A comprehensive set of evaluation metrics, encompassing accuracy, precision, recall, F1-score, and false negative rates are employed to gauge the performance of these architectures. The findings unveil the unique advantages and drawbacks of each model, illuminating the path to an optimal choice for dental caries detection using Grad-CAM (Gradient-weighted Class Activation Mapping). The testing accuracies achieved by EfficientNetV2B3, VGG19, InceptionResNetV2, Xception, and ResNet50 models stand at 95.89%, 96.58%, 93.15%, 93.15%, and 94.18%, respectively. The Training accuracies stood at 100%, 99.91%, 100%, 100% and 100%, meanwhile on validation we achieved 97.63%, 96.68%, 98.82%, 96.68%, and 100% accuracies for EfficientNetV2B3, VGG19, InceptionResNetV2, Xception, and ResNet50 models respectively. Capitalizing on transfer learning and juxtaposing diverse pre-trained architectures, this research paper paves the way for substantial advancements in dental diagnostic capabilities, culminating in enhanced patient outcomes and superior oral health. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Chemical activation

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Controllab.e False Data Injection Attack 5th

Controllable False Data Injection Attack

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5th International Conference on Data science, Machine Learning and Applications, ICDSMLA 2023

作者： Kokkonda, Jayasree Jahnavi, M. Department of Information Technology G. Narayanamma Institute of Technology and Science Hyderabad India Department of Computer Network and Information Security Narayanamma Institute of Technology and Science Hyderabad India

ISBN: (纸本)9789819780426

Yet the Internet of Things continues to grow significantly. A cyber-physical system faces a variety of security challenges due to the network connections made by the various kinds of devices and large systems that make up national infrastructures like a smart grid. Here, For the forward flow and the feedback path of a control system, respectively, we suggest two fake data injection attacks. Both are made using a variable parameter that determines the degree of deterioration. On the forward path, a linear forward assault is created together with the least squares approach. The Kalman filter is constructed on the feedback route. According to the numerical analysis, the suggested assaults govern how much the performance of the control system declines. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Kalman filters

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network Intrusion Detection in Internet of Blended Environment Using Ensemble of Heterogeneous Autoencoders(E-HAE)

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computer Systems science & Engineering 2023年第9期46卷 3261-3284页

作者： Lelisa Adeba Jilcha Deuk-Hun Kim Julian Jang-Jaccard Jin Kwak ISAA Lab. Department of AI Convergence NetworkAjou UniversitySuwon16499Korea ISAA Lab. Institute for Information and CommunicationAjou UniversitySuwon16499Korea Department of Computer Science and Information Technology Massey UniversityAuckland0745New Zealand Department of Cyber Security Ajou UniversitySuwon16499Korea

Contemporary attackers,mainly motivated by financial gain,consistently devise sophisticated penetration techniques to access important information or *** growing use of Internet of Things(IoT)technology in the contemporary convergence environment to connect to corporate networks and cloud-based applications only worsens this situation,as it facilitates multiple new attack vectors to emerge *** such,existing intrusion detection systems suffer from performance degradation mainly because of insufficient considerations and poorly modeled detection *** address this problem,we designed a blended threat detection approach,considering the possible impact and dimensionality of new attack surfaces due to the aforementioned *** collectively refer to the convergence of different technology sectors as the internet of blended *** proposed approach encompasses an ensemble of heterogeneous probabilistic autoencoders that leverage the corresponding advantages of a convolutional variational autoencoder and long short-term memory variational *** extensive experimental analysis conducted on the TON_IoT dataset demonstrated 96.02%detection ***,performance of the proposed approach was compared with various single model(autoencoder)-based network intrusion detection approaches:autoencoder,variational autoencoder,convolutional variational autoencoder,and long short-term memory variational *** proposed model outperformed all compared models,demonstrating F1-score improvements of 4.99%,2.25%,1.92%,and 3.69%,respectively.

关键词： network intrusion detection anomaly detection TON_IoT dataset smart grid smart city smart factory digital healthcare autoencoder variational autoencoder LSTM convolutional variational autoencoder ensemble learning

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Provably Secure Efficient Key-Exchange Protocol for Intelligent Supply Line Surveillance in Smart Grids

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IEEE Internet of Things Journal 2025年第12期12卷 21784-21792页

作者： Ayub, Muhammad Faizan Li, Xiong Mahmood, Khalid Alenazi, Mohammed J.F. Das, Ashok Kumar Wang, Guijuan University of Electronic Science and Technology of China School of Computer Science and Engineering Sichuan Chengdu12599 China National Yunlin University of Science and Technology Graduate School of Intelligent Data Science Yunlin Douliu64002 Taiwan Department of Computer Engineering Riyadh11451 Saudi Arabia International Institute of Information Technology Center for Security Theory and Algorithmic Research Hyderabad500 032 India Korea University College of Informatics Department of Computer Science and Engineering Anam-ro Seoul145 Korea Republic of Ministry of Education Shandong Computer Science Center Qilu University of Technology Shandong Academy of Sciences Key Laboratory of Computing Power Network and Information Security Jinan250353 China Shandong Provincial Key Laboratory of Industrial Network and Information System Security China Shandong Fundamental Research Center for Computer Science Jinan 250353 China

Intelligent supply line surveillance is critical for modern smart grids. Smart sensors and gateway nodes are strategically deployed along supply lines to achieve intelligent surveillance. They collect data continuously and transmit it to the control centre in real-time. It enables real-time monitoring, fault detection, and efficient energy management across distribution networks. This advanced surveillance system ensures continuous monitoring of supply lines, detecting anomalies, and optimizing operations to maintain the stability and reliability of the smart grid. However, the reliance of all participating nodes on public communication channels to transmit supply line surveillance data exposes these systems to critical cyber attacks. These cyber attacks include impersonation, physical tampering, ephemeral secret leakage, and desynchronization attacks. To address these issues, existing key-exchange protocols often fail to ensure robust security while imposing high computation and communication overheads, limiting their practicality for resource-constrained environments. Therefore, we propose a secure and efficient key exchange and tamper-resistant authentication protocol using Elliptic Curve Cryptography (ECC) and Physical Unclonable Functions (PUFs). The PUF mechanism provides robust resistance against physical tampering and cloning attacks, ensuring enhanced physical security for supply line devices. We validate the security robustness of the devised protocol using the Random or Real (ROR) model. Furthermore, informal security analysis demonstrates the protocol's robustness in rigorously resisting various attacks, including physical tampering, impersonation, ephemeral secret leakage and desynchronization. Moreover, we determine the performance evaluation that reveals the protocol's superior efficiency compared to competing protocols, achieving significant reductions of 28.64% in computation overhead and 9.96% in communication overhead. © 2014 IEEE.

关键词： Authentication Protocol

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Endogenous security of FQn networks: Adaptive System-Level Fault Self-Diagnosis

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IEEE Transactions on Reliability 2024年第3期73卷 1659-1668页

作者： Lin, Yuhang Lin, Limei Huang, Yanze Xu, Li Hsieh, Sun-Yuan Fujian Normal University College of Computer and Cyber Security Fujian Provincial Key Laboratory of Network Security and Cryptology Fuzhou350117 China Fujian University of Technology School of Computer Science and Mathematics Fuzhou350118 China National Cheng Kung University Department of Computer Science and Information Engineering Tainan701 Taiwan

Endogenous security has the ability to discover, eliminate, and solve internal security problems and hidden dangers within the network, and is a superior technology to ensure future network security. The t/k-diagnosis strategy, as a strong and adaptive self-diagnosis strategy, is an important part for ensuring endogenous security. Moreover, the folded hypercube (FQn) as a data transmission network (e.g., optical network) topology offers new potential for the construction of large-scale, high data throughput, and low-latency systems, such as computing network, human-cyber-physical systems, and smart grid. However, there are few studies on endogenous security based on FQn networks. Therefore, this article designs an adaptive system-level fault self-diagnosis strategy, namely Fast t/k-Diagnosis Under Maeng-Malek Model (Ftk-DIAG-MM*) to diagnosis the faulty vertices in FQn network under the Maeng-Malek model (MM∗ mod). Then, we provide a proof of the algorithm correctness theoretically by the fault tolerance of FQn network. It is derived by theoretical derivation that the t/k-diagnosability inherent to the FQn network is (n+1)(k+1)-k(k+3)/2. The simulation experiments demonstrate that the designed Ftk-DIAG-MM∗ strategy can correctly diagnose all vertices within the range allowed by the diagnosability, and still has a great performance when it exceeds the range allowed by the diagnosability. It greatly enhances the fault diagnosis capability of FQn network in the circumstance of misdiagnosing a few vertices, which provides an important theoretical basis for the reliability and endogenous security of FQn networks. © 1963-2012 IEEE.

关键词： Topology

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A Robust Key Exchange and Tamper-Resistant Protocol for HAN and NAN networks in Smart Grids

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IEEE Internet of Things Journal 2025年第12期12卷 21394-21403页

作者： Ayub, Muhammad Faizan Li, Xiong Mahmood, Khalid Shamshad, Salman Das, Ashok Kumar Wang, Guijuan University of Electronic Science and Technology of China School of Computer Science and Engineering Sichuan Chengdu611731 China National Yunlin University of Science and Technology Graduate School of Intelligent Data Science Yunlin Douliu64002 Taiwan The University of Lahore Department of Software Engineering Lahore54590 Pakistan International Institute of Information Technology Center for Security Theory and Algorithmic Research Hyderabad500 032 India Korea University College of Informatics Department of Computer Science and Engineering Anam-ro Seoul145 Korea Republic of Qilu University of Technology Shandong Academy of Sciences Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Jinan250353 China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Industrial Network and Information System Security Jinan250353 China

Smart Grids (SG) rely on Home Area networks (HAN) and Neighborhood Area networks (NAN) to ensure efficient power distribution, real-time monitoring, and seamless communication between smart devices. Despite these advantages, the use of public communication channels in HAN and NAN networks introduces critical challenges, such as vulnerability to impersonation, physical tampering, and scalab.lity issues in resource-constrained environments. These issues compromise the stability, reliability, and security of SG environments. Existing protocols often fail to adequately address these challenges, particularly in ensuring resistance to physical tampering of supply lines and impersonation attacks. Additionally, they struggle to minimize the computation, communication, and energy costs associated with securing a resource-constrained SG environment. Therefore, we propose a robust key exchange and tamper-resistant protocol for HAN and NAN networks to address these limitations. The proposed protocol leverages the Physical Unclonable Function (PUF) mechanism to offer physical tampering resistance to smart meters. We validate our protocol formally using the Random or Real (RoR) model, which confirms its security robustness. Additionally, our informal security analysis highlights the protocol's resilience against impersonation, physical tampering attacks, etc. We analyze and compare the performance of the proposed protocol, which further demonstrates our protocol's effectiveness and security compared to competing protocols. Moreover, the proposed protocol achieves resource efficiency with 45.99% and 58.85% substantial reductions in computation overhead and energy overhead, respectively, compared to competing protocols. These results showcase the protocol's enhanced security and practicality for resource-constrained SG environments. © 2014 IEEE.

关键词： Authentication Protocol

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Forward Legal Anonymous Group Pairing-Onion Routing for Mobile Opportunistic networks

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IEEE Transactions on Mobile Computing 2025年第7期24卷 6595-6612页

作者： Zhu, Xiuzhen Lin, Limei Huang, Yanze Wang, Xiaoding Hsieh, Sun-Yuan Wu, Jie Fujian Normal University College of Computer and Cyber Security Fujian Provincial Key Laboratory of Network Security and Cryptology Fujian Fuzhou350117 China Fujian University of Technology School of Computer Science and Mathematics Fujian Fuzhou350118 China National Cheng Kung University Department of Computer Science and Information Engineering Tainan701 Taiwan Temple University Department of Computer and Information Science 1925 N. 12th St PhiladelphiaPA19122 United States

Mobile Opportunistic networks (MONs) often experience frequent interruptions in end-to-end connections, which increases the likelihood of message loss during delivery and makes users more susceptible to various cyber attacks. However, most currently proposed anonymous routing protocols are primarily designed for networks with stable connections, making it challenging to protect user identities in MONs. To address these challenges, we propose FLAG-POR (Forward Legal Anonymous Group Pairing-Onion Routing), a novel anonymous routing protocol specifically tailored to enhance message delivery anonymity and security in MONs. Specifically, we abstract the mobile opportunistic network as a contact graph. By introducing the concept of "groups» into the pairing-onion routing protocol, which encrypts messages and relay nodes layer by layer, we develop a novel group-based pairing-onion routing protocol. This protocol ensures message confidentiality and relay node anonymity, while also improving message forwarding rates, as any node within a group can potentially act as a relay. To ensure message authenticity, we employ the efficient SM2 signing algorithm to generate signatures for the message source. Furthermore, by incorporating parameters such as the public key validity period and master key validity period into the group pairing-onion routing protocol, we achieve forward security in message delivery. We conduct a thorough theoretical analysis of the protocol's security and performance. The experimental results demonstrate that our FLAG-POR protocol outperforms baseline anonymous protocols in terms of delivery success rate, traceability rate, path anonymity, and node anonymity. Additionally, the FLAG-POR scheme effectively resists three potential threats to the routing system: collusion attack threat, node identification threat, and path identification threat, in any situation. © 2002-2012 IEEE.

关键词： Anonymity

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Enhancing TrUStAPIS Methodology in the Web of Things with LLM-Generated IoT Trust Semantics 26th

Enhancing TrUStAPIS Methodology in the Web of Things with LL...

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26th International Conference on information and Communications security, ICICS 2024

作者： Ferraris, Davide Kotis, Konstantinos Kalloniatis, Christos Network Information and Computer Security Lab University of Malaga Malaga Spain Department of Cultural Technology and Communication University of the Aegean Mytilene Greece

ISBN: (纸本)9789819787975

In the Internet of Things (IoT) there are ecosystems where their physical’smart’ entities virtually interact with each other. Often, this interaction occurs among unknown entities, making trust an essential requirement to overcome uncertainty in several aspects of this interaction. However, trust is a complex concept, and incorporating it in IoT is still a challenging topic. For this reason, it is highly significant to specify and model trust in early stages of the System Development Life Cycle (SDLC) of IoT-integrated systems, thus enhancing the aforementioned task. TrUStAPIS is a requirements engineering methodology recently introduced for incorporating trust requirements during IoT-based system design. The scope of this paper is to provide an extension of TrUStAPIS by introducing IoT trust semantics compatible with the W3C Web of Things (WoT) recommendations generated with the assistance of Large Language Models (LLMs). Taking advantage of LLMs as a tool for integrating and refining existing methodologies, in this paper we present our work towards a revision of the TrUStAPIS methodology. In this work, we contribute a new conceptual model and a refined JSON-LD ontology that takes into account IoT trust semantics, providing eventually a valuable tool for software engineers to design and model IoT-based systems and services. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Requirements engineering

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A study on the Application of Multilevel Secure Hash Function in Blockchain 2

A study on the Application of Multilevel Secure Hash Functio...

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2022 2nd Conference on High Performance Computing and Communication Engineering, HPCCE 2022

作者： Jin, Shi-Mei Wang, Yi-Han Li, Yongzhen Yanbian University Information Technology Education Yanji133000 China Yanbian University Network Communication and Information Security Lab. Dept. of Computer Science and Technology Yanji133000 China

ISBN: (纸本)9781510663374

With the rapid development and upgrade of the social network and IT, information security has become increasingly significant. Hash function has become a research key-point in the field of information security. To meeting the requirements of various circumstances, this dissertation puts forward Multilevel security Hash Function (MSHF) and conduct a comparison experiment between MSHF and traditional methods to generate Merkle trees. The experimental results show that the Merkle tree generated based on MSHF has smaller depth, shorter path length, and shorter time used to find the wrong data. © 2023 SPIE.

关键词： Hash functions

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New results on quantum boomerang attacks

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Quantum information Processing 2023年第4期22卷 1-27页

作者： Zou, Hongkai Zou, Jian Luo, Yiyuan College of Computer and Data Science Fuzhou University Fuzhou China Key Lab of Information Security of Network Systems Fuzhou University Fuzhou China School of Information Sciences and Technology Huizhou University Huizhou China

At SAC 2021, Frixons et al. proposed quantum boomerang attacks that can effectively recover the keys of block ciphers in the quantum setting. Based on their work, we further consider how to quantize the generic boomerang attacks proposed by Biham et al. at FSE 2002, so as to obtain more generic quantum boomerang attacks. Similar to Frixons et al.’s work, we only consider quantum key recovery attacks in the single-key setting. With the help of some famous quantum algorithms, this paper presents two methods to convert the attacks of Biham et al. into some new quantum key recovery attacks. In order to proof our methods, we apply our new ideas to attack Serpent-256 and ARIA-196. To sum up, for Serpent-256, we give valid 9-round and 10-round quantum key recovery attacks respectively. The quantum time complexity of 9-round and 10-round of Serpent-256 is 2 115.43 and 2 126.6 respectively. Furthermore, we show a valid quantum key attack on 6-round ARIA-196 which has a time complexity of 2 89.8 with negligible memory. The time complexity of the above quantum attacks are better than the corresponding classical attacks and quantum generic key recovery attack via Grover’s algorithm. © 2023, The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature.

关键词： Quantum theory

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