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The Impact of Domain Name Server(DNS)over Hypertext Transfer Protocol Secure(HTTPS)on Cyber Security:Limitations,Challenges,and Detection Techniques

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computers, Materials & Continua 2024年第9期80卷 4513-4542页

作者： Muhammad Dawood Shanshan Tu Chuangbai Xiao Muhammad Haris Hisham Alasmary Muhammad Waqas Sadaqat Ur Rehman Faculty of Information Technology Beijing University of TechnologyBeijing100124China National Center of Robotics and Automation University of Engineering and TechnologyPeshawar25000Pakistan Department of Computer Science College of Computer ScienceKing Khalid UniversityAbha61421Saudi Arabia School of Computing and Engineering Sciences Faculty of Engineering and ScienceUniversity of GreenwichLondonSE109LSUnited Kingdom School of Engineering Edith Cowan UniversityPerthWA 6027Australia School of Computer Science and Engineering University of SalfordManchesterM54BRUnited Kingdom

The DNS over HTTPS(Hypertext Transfer Protocol Secure)(DoH)is a new technology that encrypts DNS traffic,enhancing the privacy and security of ***,the adoption of DoH is still facing several research challenges,such as ensuring security,compatibility,standardization,performance,privacy,and increasing user *** significantly impacts network security,including better end-user privacy and security,challenges for network security professionals,increasing usage of encrypted malware communication,and difficulty adapting DNS-based security ***,it is important to understand the impact of DoH on network security and develop newprivacy-preserving techniques to allowthe analysis of DoH traffic without compromising user *** paper provides an in-depth analysis of the effects of DoH on *** discuss various techniques for detecting DoH tunneling and identify essential research challenges that need to be addressed in future security ***,this paper highlights the need for continued research and development to ensure the effectiveness of DoH as a tool for improving privacy and security.

关键词： DNS DNS over HTTPS cybersecurity machine learning

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Pricing mechanism for constrained driverless shared buses in a smart city

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Journal of Intelligent and Fuzzy Systems 2025年第1-2期48卷 109-122页

作者： Jin, Yong Yang, Huizhen School of Computer Science and Engineering Changshu Institute of Technology Changshu China Changshu Dawei Transportation Technology Co. Ltd Changshu China

The price of passengers is closely related to the travel cost of passengers and the revenue of driverless shared bus. Therefore, the design of pricing mechanism is important to improve the market efficiency of driverless shared bus scheduling. To address these issues, we formulate the social optimization passenger selection problem to maximize the social welfare such that number of passengers taking each driverless shared bus is no more than its capacity and all the driverless shared buses can arrive at the corresponding destinations before the deadlines of the passengers, and propose the auction-based truthful pricing mechanism, Driverless Shared Bus Pricing (DSBP) mechanism, for deadline tightened pricing problem of driverless shared buses. Through both rigorous theoretical analysis and extensive simulations, we demonstrate that the proposed mechanism achieves computational efficiency, individual rationality, truthfulness, and guaranteed approximation. © 2025 – IOS Press. All rights reserved.

关键词： Smart city driverless shared bus pricing scheduling

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Bioinformatics and Biomedical Computing

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Fundamental Research 2024年第4期4卷 713-714页

作者： Hongmin Cai Jiazhou Chen Fa Zhang Jianxin Wang The School of Computer Science and Engineering South China University of TechnologyGuangzhou 510006China The School of Medical Technology Bejing Institute of TechnologyBejing 100081China The School of Computer Science and Engineering Central South UniversityChangsha 410083China

The rapid advancement of high-throughput sequencing technologies and the explosive growth of biological data have revolutionized the field of bioinformatics and biomedical computing[1-4].The generation of vast amounts of genomic,transcriptomic,proteomic,and metabolomic data has created unprecedented opportunities for understanding the complexities of biological systems and their implications for human health[5-6].Moreover,the emergence of spatial omics technologies,such as spatial transcriptomics and spatial proteomics,has added a new dimension to our understanding of the spatial organization and heterogeneity of biological *** cutting-edge technologies enable the mapping of molecular information at a high spatial resolution,providing valuable insights into the tissue microenvironment and the interplay between cells in various physiological and pathological conditions[7-10].

关键词： enable dimension insight

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Joint Watermarking and Encryption for Social Image Sharing

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computers, Materials & Continua 2025年第5期83卷 2927-2946页

作者： Conghuan Ye Shenglong Tan Shi Li Jun Wang Qiankun Zuo Bing Xiong School of Information Engineering Hubei University of EconomicsWuhan430205China School of Computer and Communication Engineering Changsha University of Science&TechnologyChangsha410114China

With the fast development of multimedia social platforms,content dissemination on social media platforms is becomingmore *** image sharing can also raise privacy *** encryption can protect social ***,most existing image protection methods cannot be applied to multimedia social platforms because of encryption in the spatial *** this work,the authors propose a secure social image-sharing method with watermarking/fingerprinting and ***,the fingerprint code with a hierarchical community structure is designed based on social network ***,discrete wavelet transform(DWT)from block discrete cosine transform(DCT)directly is *** that,all codeword segments are embedded into the LL,LH,and HL subbands,*** selected subbands are confused based on Game of Life(GoL),and then all subbands are diffused with singular value decomposition(SVD).Experimental results and security analysis demonstrate the security,invisibility,and robustness of our ***,the superiority of the technique is elaborated through comparison with some related image security *** solution not only performs the fast transformation from block DCT to one-level DWT but also protects users’privacy in multimedia social *** the proposed method,JPEG image secure sharing in multimedia social platforms can be ensured.

关键词： Multimedia security digital watermarking image encryption image sharing privacy protection

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A General Linguistic Steganalysis Framework Using Multi-Task Learning

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computer Systems science & engineering 2023年第8期46卷 2383-2399页

作者： Lingyun Xiang Rong Wang Yuhang Liu Yangfan Liu Lina Tan School of Computer and Communication Engineering Changsha University of Science and TechnologyChangsha410114China School of Computer Science and Electronic Engineering University of EssexColchesterCO43SQUK School of Computer Science Hunan University of Technology and BusinessChangsha410205China

Prevailing linguistic steganalysis approaches focus on learning sensitive features to distinguish a particular category of steganographic texts from non-steganographic texts,by performing binary *** it remains an unsolved problem and poses a significant threat to the security of cyberspace when various categories of non-steganographic or steganographic texts *** this paper,we propose a general linguistic steganalysis framework named LS-MTL,which introduces the idea of multi-task learning to deal with the classification of various categories of steganographic and non-steganographic ***-MTL captures sensitive linguistic features from multiple related linguistic steganalysis tasks and can concurrently handle diverse tasks with a constructed *** the proposed framework,convolutional neural networks(CNNs)are utilized as private base models to extract sensitive features for each steganalysis ***,a shared CNN is built to capture potential interaction information and share linguistic features among all ***,LS-MTL incorporates the private and shared sensitive features to identify the detected text as steganographic or *** results demonstrate that the proposed framework LS-MTL outperforms the baseline in the multi-category linguistic steganalysis task,while average Acc,Pre,and Rec are increased by 0.5%,1.4%,and 0.4%,*** ablation experimental results show that LS-MTL with the shared module has robust generalization capability and achieves good detection performance even in the case of spare data.

关键词： Linguistic steganalysis multi-task learning convolutional neural network(CNN) feature extraction detection performance

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Hybrid approach for the detection of epileptic seizure using electroencephalography input

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International Journal of Information technology (Singapore) 2024年第1期16卷 569-575页

作者： Basha, Niha Kamal Surendiran, B. Benzikar, Amutha Joyal, S. School of Computer Science and Engineering Vellore Institute of Technology (VIT) Vellore India Department of Computer Science and Engineering National Institute of Technology (NIT) Puducherry Karaikal India School of Computer Science and Engineering Vellore Institute of Technology (VIT) Chennai India Saveetha Engineering College Chennai India

In the early days, it was difficult to study bio-electric signals, but now a days these problems have been solved by many hardware devices which are available at low cost. Even then there is a need for technical improvements to process bio-electric signals. Enormous effort has been taken for the detection of epileptic seizure from EEG signal. Considerable evidence available on Bonn university EEG dataset for epileptic seizure detection. However, deep learning algorithms have not applied often on Bonn university data like other machine learning algorithms for the detection of epileptic seizure due to the less availability of data. This work adopted machine learning and deep learning models for the detection of epileptic seizure. The data consists of a hundred subjects with sampling rate as 173.61 Hz of ‘S’ (ictal) and ‘Z’ (normal) dataset. The results show how the choice of healthy and ictic subjects through high order functional math decision like variance (STD), Power, Skewness, and Kurtosis values are analyzed to extract epileptic features. The performance of classifiers has been evaluated based on the evaluation metrics within which CGRU-SVM outperforms all other models with 97.54% accuracy. The features are extracted based on the statistical measures to detect epileptic seizure. Further, the proposed work provides more evidence on the epileptic seizure features, and it shows the new possibility for using deep learning models for epileptic seizure detection. In future, an analysis must be performed with dynamic sets of input and different analysis techniques. © 2023, The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of computer Applications and Management.

关键词： Confusion matrix Deep learning model Electroencephalography Epilepsy Ictal subject Rhythmic frequency Statistical feature

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A novel method for indian vehicle registration number plate detection and recognition using CNN

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Journal of Intelligent and Fuzzy Systems 2024年第4期46卷 8563-8585页

作者： Pandey, Vibha Choubey, Siddhartha Patra, Jyotiprakash Mall, Shachi Choubey, Abha Department of Computer Science Engineering Shri Shankaracharya Technical Campus Chhattisgarh Bhilai India Department of Computer Science Engineering Shri Shankaracharya Institute of Professional Management and Technology Chhattisgarh Raipur India School of Computer Science and Engineering Galgotias University Greater Noida India

Automated reading of license plate and its detection is a crucial component of the competent transportation system. Toll payment and parking management e-payment systems may benefit from this software’s features. License plate detection and identification algorithms abound, and each has its own set of strengths and weaknesses. computer vision has advanced rapidly in terms of new breakthroughs and techniques thanks to the emergence and proliferation of deep learning principles across several branches of AI. The practice of automating the monitoring process in traffic management, parking management, and police surveillance has become much more effective thanks to the development of Automatic License Plate Recognition (ALPR). Even though license plate recognition (LPR) is a technology that is extensively utilized and has been developed, there is still a significant amount of work to be done before it can achieve its full potential. In the last several years, there have been substantial advancements in both the scientific community’s methodology and its level of efficiency. In this era of deep learning, there have been numerous developments and techniques established for LPR, and the purpose of this research is to review and examine those developments and approaches. In light of this, the authors of this study suggest a four-stage technique to automated license plate detection and identification (ALPDR), which includes, image pre-processing, license plate extraction, character segmentation, and character recognition. And the first three phases are known as "extraction," "preprocessing," and "segmentation," and each of these processes has been shown to benefit from its own unique technique. In light of the fact that character recognition is an essential component of license plate identification and detection, the Convolution Neural Network (CNN), MobileNet, Inception V3, and ResNet 50 have all been put through their paces in this regard. © 2024 – IOS Press. All rights re

关键词： Image classification

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Digital twin empowered cooperative trajectory planning of platoon vehicles for collision avoidance with unexpected obstacles

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Digital Communications and Networks 2024年第6期10卷 1666-1676页

作者： Hao Du Supeng Leng Jianhua He Kai Xiong Longyu Zhou School of Information&Communication Engineering University of Electronic Science and Technology of ChinaChengdu 611731China School of Computer Science and Electronic Engineering University of EssexColchester CO43SQUnited Kingdom Shenzhen Institute for Advanced Study University of Electronic Science and Technology of ChinaShenzhen 518110China

Road obstacles that unexpectedly appear due to vehicle breakdowns and accidents are major causes of fatal road *** Autonomous Vehicles(CAVs)can be used to avoid collisions to ensure road safety through cooperative sensing and ***,the collision avoidance performance of CAVs with unexpected obstacles has not been studied in the existing *** this paper,we first design a platoon-based collision avoidance framework for *** this framework,we deploy a Digital Twin(DT)system at the head vehicle in a platoon to reduce communication overhead and decision-making delay based on a proposed trajectory planning *** addition,a DT-assistant system is deployed on the assistant vehicle to monitor vehicles out of the sensing range of the head vehicle for the maintenance of the DT *** this case,the transmission frequency of kinetic states of platoon members can be reduced to ensure low-overhead ***,we design a variable resource reservation interval that can ensure DT synchronization between DT and the assistant system with high *** further improve road safety,an urgency level-based trajectory planning algorithm is proposed to avoid unexpected obstacles considering different levels of emergency *** results show that our DT system-based scheme can achieve significant performance gains in unexpected obstacle *** to the existing schemes,it can reduce collisions by 95%and is faster by about 10%passing by the unexpected obstacle.

关键词： Platoon driving Cooperative trajectory planning Digital twin Obstacle avoidance

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AR assistance for efficient dynamic target search

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Computational Visual Media 2023年第1期9卷 177-194页

作者： Zixiang Zhao Jian Wu Lili Wang State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and EngineeringBeihang UniversityBeijingChina

When searching for a dynamic target in an unknown real world scene,search efficiency is greatly reduced if users lack information about the spatial structure of the *** target search studies,especially in robotics,focus on determining either the shortest path when the target’s position is known,or a strategy to find the target as quickly as possible when the target’s position is ***,the target’s position is often known intermittently in the real world,e.g.,in the case of using surveillance *** goal is to help user find a dynamic target efficiently in the real world when the target’s position is intermittently *** order to achieve this purpose,we have designed an AR guidance assistance system to provide optimal current directional guidance to users,based on searching a prediction *** assume that a certain number of depth cameras are fixed in a real scene to obtain dynamic target’s *** system automatically analyzes all possible meetings between the user and the target,and generates optimal directional guidance to help the user catch up with the target.A user study was used to evaluate our method,and its results showed that compared to free search and a top-view method,our method significantly improves target search efficiency.

关键词： augmented reality(AR) search guidance

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Privacy-Preserving Publishing Mechanism for Real-Time Vehicle Trajectory in Vehicle-to-Grid Networks 5

Privacy-Preserving Publishing Mechanism for Real-Time Vehicl...

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5th IEEE International Conference on Power, Electronics and computer Applications, ICPECA 2025

作者： Wang, Yulong Xu, Jianbo Gong, Bo School of Computer Science and Engineering Hunan University of Science and Technology Xiangtan China

ISBN: (纸本)9798331533694

The Vehicle-to-Grid (V2G) network is a smart grid technology generated under the background of the rapid development of new energy technology, which allows mobile energy storage vehicles (MESVs) to realize bidirectional energy exchange with the grid system. As distributed energy storage units within the V2G network, MESVs help meet the grid's load-balancing demands. To accurately schedule grid loads, V2G networks rely on MESVs' real-time trajectory data. After collecting this data, the central authority (CA) publishes it to the grid enterprise (GM) for load-balancing decisions. However, before publication, the CA must process the data to protect the location privacy of MESVs and prevent GM from extracting sensitive information. To address this privacy protection challenge during data publication, we propose a differential privacy-based mechanism. Our mechanism uses the unscented Kalman filter to predict and correct the published data at the sampling point and intelligently adjusts the sampling interval. Additionally, we introduce a privacy budget allocation method based on regional access frequency and travel time, enhancing privacy protection of trajectory in high-access areas and peak hours. Through security analysis and experimental validation, our mechanism effectively preserves the privacy of real-time vehicle trajectory data while ensuring data validity. © 2025 IEEE.

关键词： Vehicle-to-grid

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