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13th International Conference on Communication and Network security, ICCNS 2023

作者： Lyu, Chenxi Yao, Yinan Guo, Xiaodong Huang, Zihong Dong, Chen Zhang, Yuanyuan Chen, Zhenyi College of Computer and Data Science Fuzhou University Fuzhou China College of Computer and Cyber Security Fujian Normal University Fuzhou China Department of Computer Science and Engineering University of South Florida FL United States

ISBN: (纸本)9798400707964

In the present era, the menace of malicious software is growing continuously, posing a significant challenge in the realm of cybersecurity. Currently, traditional machine learning algorithms have been widely applied to the analysis of malicious software and are considered effective methods. However, these approaches often require extensive feature engineering, feature learning, and feature representation, which can be time-consuming and resource-intensive. In this paper, a method for the identification of malicious software, named "AntiMal,"is proposed. This method utilizes the Swin Transformer as the backbone network and combines it with image features for static analysis. It leverages the dataset provided by Microsoft for the Kaggle Microsoft Malware Classification Challenge. Initially, it converts the binary data of malicious code into grayscale images, treating every 8 bits as a pixel. Subsequently, it employs PyTorch to build and train the Swin Transformer, classifying the images in the validation set. The results demonstrate that this approach excels in the problem of malicious software classification, achieving an impressive accuracy of up to 95%, showcasing remarkable precision and generalization capabilities. Furthermore, it exhibits significant advantages when dealing with large datasets, requiring fewer computational resources, thus offering exceptional computational efficiency. © 2023 ACM.

关键词： Malware

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EBAKE-SE: A novel ECC-based authenticated key exchange between industrial IoT devices using secure element

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Digital Communications and Networks 2023年第2期9卷 358-366页

作者： Chintan Patel Ali Kashif Bashir Ahmad Ali AlZubi Rutvij Jhaveri School of Artificial Intelligence Information Technology and Cyber SecurityRashtriya Raksha UniversityGujaratIndia Department of Computing and Mathematics Manchester Metropolitan UniversityUnited Kingdom Woxsen School of Business Woxsen UniversityIndia Department of Computer Science and Mathematics Lebanese American UniversityBeirutLebanon Computer Science Department Community CollegeKing Saud UniversityP.O.Box 28095Riyadh11437Saudi Arabia Department of Computer Science and Engineering School of TechnologyPandit Deendayal Energy UniversityGujaratIndia

Industrial IoT(IIoT)aims to enhance services provided by various industries,such as manufacturing and product *** suffers from various challenges,and security is one of the key challenge among those *** and access control are two notable challenges for any IIoT based industrial *** IoT based Industry 4.0 enterprise designs networks between hundreds of tiny devices such as sensors,actuators,fog devices and ***,articulating a secure authentication protocol between sensing devices or a sensing device and user devices is an essential step in IoT *** this paper,first,we present cryptanalysis for the certificate-based scheme proposed for a similar environment by Das et *** prove that their scheme is vulnerable to various traditional attacks such as device anonymity,MITM,and *** then put forward an interdevice authentication scheme using an ECC(Elliptic Curve Cryptography)that is highly secure and lightweight compared to other existing schemes for a similar ***,we set forth a formal security analysis using the random oracle-based ROR model and informal security analysis over the Doleve-Yao *** this paper,we present comparison of the proposed scheme with existing schemes based on communication cost,computation cost and security index to prove that the proposed EBAKE-SE is highly efficient,reliable,and trustworthy compared to other existing schemes for an inter-device *** long last,we present an implementation for the proposed EBAKE-SE using MQTT protocol.

关键词： Internet of things Authentication Elliptic curve cryptography Secure key exchange Message Queuing telemetry transport

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HCL-Net: A Single Image Rain Removal Algorithm Based on Channel Attention and Multi-scale Feature Fusion 6

HCL-Net: A Single Image Rain Removal Algorithm Based on Chan...

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6th IEEE International Conference on Pattern Recognition and Artificial Intelligence, PRAI 2023

作者： Huang, Jin He, Pei Guangzhou University School of Cyberspace Security Guangzhou China Guangzhou University School of Computer Science and Cyber Engineering Guangzhou China

ISBN: (纸本)9798350325485

The investigation of rain removal from pictures has always been a pivotal matter in the domain of computer vision. Nevertheless, the majority of existing algorithms employ encoder-decoder structures that have been trained on artificially synthesized datasets, without taking into account the harm that heavy rain can cause to actual images. Batch normalization is unsuitable for low-level computer vision duties, and skip connections in encoder-decoder architectures are not always appropriate for rain removal. This has resulted in setbacks in relevant domains. In this article, we propose a groundbreaking single-image rain removal algorithm that is founded on channel attention and multi-scale feature fusion. Initially, we build a contextualized dilated restoration block to restore the rain-Affected image during the feature extraction phase. Secondly, we create a half-instance normalization residual block to conserve more scale information and to augment the modeling capacity of the model, without sacrificing performance while hastening model convergence. Finally, in response to the view that simple skip connections may not always be advantageous, we have constructed a LeakyReLU channel attention block to aggregate information and enhance the effectiveness of skip connections. Our comprehensive experiments on authentic rain datasets and images provide evidence that our model can more proficiently remove rain streaks and accumulations from pictures, in contrast to the existing methods. © 2023 IEEE.

关键词： Image reconstruction

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Reinforcement learning of non-additive joint steganographic embedding costs with attention mechanism

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science China(Information sciences) 2023年第3期66卷 273-286页

作者： Weixuan TANG Bin LI Weixiang LI Yuangen WANG Jiwu HUANG Institute of Artificial Intelligence and Blockchain Guangzhou University Guangdong Key Laboratory of Intelligent Information Processing Shenzhen Key Laboratory of Media Security Shenzhen University Shenzhen Institute of Artificial Intelligence and Robotics for Society School of Computer Science and Cyber Engineering Guangzhou University

Image steganography is the art and science of secure communication by concealing information within digital images. In recent years, the techniques of steganographic cost learning have developed rapidly. Although the existing methods can learn satisfactory additive costs, the interplay of different pixels' embedding impacts has not been considered, so the potential of learning may not be fully exploited. To overcome this limitation, in this paper, a reinforcement learning paradigm called Jo Po L(joint policy learning) is proposed to extend the idea of additive cost learning to a non-additive situation. Jo Po L aims to capture the interactions within pixel blocks by defining embedding policies and evaluating contributions of embedding impacts on a block level rather than a pixel level. Then, a policy network is utilized to learn optimal joint embedding policies for pixel blocks through interactions with the environment. Afterwards,these policies can be converted into joint embedding costs for practical message embedding. The structure of the policy network is designed with an effective attention mechanism and incorporated with the domain knowledge derived from traditional non-additive steganographic methods. The environment is responsible for assigning rewards according to the impacts of the sampled joint embedding actions, which are evaluated by the gradient information of a neural network-based steganalyzer. Experimental results show that the proposed non-additive method Jo Po L significantly outperforms the existing additive methods against both feature-based and CNN-based steganalzyers over different payloads.

关键词： information hiding non-additive steganography steganalysis cost learning image processing

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Coarse registration of color point clouds by combining color feature and geometric feature 12

Coarse registration of color point clouds by combining color...

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SPIE 12th International Symposium on Multispectral Image Processing and Pattern Recognition, MIPPR 2023

作者： Sun, Peng Jiang, Shuhang Luan, Haiyang Wang, Chen Wang, Wanqi Liu, Yu School of Opto-Electronic Engineering Changchun University of Science and Technology Jilin Changchun130022 China College of Computer Science and Cyber Security Chengdu University of Technology Chengdu Sichuan China

ISBN: (数字)9781510674967

ISBN: (纸本)9781510674950

Coarse registration is the initial step of aligning a point clouds with other clouds, aiming to put two point clouds in the correct position. There are many coarse registration methods, and among them, the SAC-IA (Sample Consensus Initial Alignment) is widely used. It selects corresponding point pairs by matching the geometric features of point clouds. It has high registration accuracy and fast registration speed. However, when the geometric features of the point clouds are relatively simple or not distinctive, its registration performance may not be very effective. With the development of color image sensors, acquiring color point clouds has become increasingly important. The RGB information of point clouds can effectively compensate for the shortcomings of the SAC-IA algorithm. The color characteristics of the interested points are extracted by fusing the color information of feature points and their neighboring points, including the first-order moment of point clouds color and the CFH of the point clouds, based on the traditional SAC-IA algorithm. Experiments have shown that the improved SAC-IA algorithm has better accuracy and robustness. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Color

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Belief Combination of Classifiers for Incomplete Data

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IEEE/CAA Journal of Automatica Sinica 2022年第4期9卷 652-667页

作者： Zuowei Zhang Songtao Ye Yiru Zhang Weiping Ding Hao Wang IEEE the Research Center for Optical Fiber Sensing Zhejiang Laboratory the School of Automation Northwestern Polytechnical University the School of Cyber Engineering Xidian University the Department of Computer Science CY Cergy Paris Université the School of Information Science and Technology Nantong University the School with of Cyber Engineering Xidian University the Department of Computer Science Norwegian University of Science and Technology

Data with missing values,or incomplete information,brings some challenges to the development of classification,as the incompleteness may significantly affect the performance of *** this paper,we handle missing values in both training and test sets with uncertainty and imprecision reasoning by proposing a new belief combination of classifier(BCC)method based on the evidence *** proposed BCC method aims to improve the classification performance of incomplete data by characterizing the uncertainty and imprecision brought by *** BCC,different attributes are regarded as independent sources,and the collection of each attribute is considered as a ***,multiple classifiers are trained with each subset independently and allow each observed attribute to provide a sub-classification result for the query ***,these sub-classification results with different weights(discounting factors)are used to provide supplementary information to jointly determine the final classes of query *** weights consist of two aspects:global and *** global weight calculated by an optimization function is employed to represent the reliability of each classifier,and the local weight obtained by mining attribute distribution characteristics is used to quantify the importance of observed attributes to the pattern *** comparative experiments including seven methods on twelve datasets are executed,demonstrating the out-performance of BCC over all baseline methods in terms of accuracy,precision,recall,F1 measure,with pertinent computational costs.

关键词： Classifier fusion classification evidence theory incomplete data missing values

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A Pricing-Based Cooperative Relay Selection Scheme for Reliable Communications

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China Communications 2024年第8期21卷 30-44页

作者： Xiao Yulong Wu Yu Amr Tolba Chen Ziqiang Li Tengfei School of Communications and Information Engineering Chongqing University of Posts and TelecommunicationsChongqing 400065China School of Cyber Security and Information Law Chongqing University of Posts and TelecommunicationsChongqing 400065China Department of Computer Science Community CollegeKing Saud UniversityRiyadh 11437Saudi Arabia

With the rapid development and application of energy harvesting technology,it has become a prominent research area due to its significant benefits in terms of green environmental protection,convenience,and high safety and ***,the uneven energy collection and consumption among IoT devices at varying distances may lead to resource imbalance within energy harvesting networks,thereby resulting in low energy transmission *** enhance the energy transmission efficiency of IoT devices in energy harvesting,this paper focuses on the utilization of collaborative communication,along with pricing-based incentive mechanisms and auction *** propose a dynamic relay selection scheme,including a ladder pricing mechanism based on energy level and a Kuhn-Munkre Algorithm based on an auction theory employing a negotiation mechanism,to encourage more IoT devices to participate in the collaboration *** results demonstrate that the proposed algorithm outperforms traditional algorithms in terms of improving the energy efficiency of the system.

关键词： cooperative communication edge net-work energy harvesting relay selection

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Advance Public Bus Transport Management System: An Innovative Smart Bus Concept

Advance Public Bus Transport Management System: An Innovativ...

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2024 IEEE International Conference on Consumer Electronics, ICCE 2024

作者： Patel, Keyurkumar Patel, Divya Chaudhary, Nishit Thakkar, Darsh Savaliya, Pratham Mistry, Armaan Rashtriya Raksha University Artificial Intelligence and Cyber Security Department of IT Gujarat Gandhinagar382305 India Karnavati University Unitedworld School of Computational Intelligence Department of Computer Science and Engineering Gujarat Gandhinagar382422 India

ISBN: (纸本)9798350324136

In the present era, public bus transportation services often lag behind in adopting modern technologies, resulting in numerous operational complexities. These issues encompass challenges such as poor passenger density control, operational inefficiencies, inadequate live tracking, limited real-Time capabilities, suboptimal resource management, route ambiguities, safety concerns, and more. This research paper introduces a comprehensive solution an Advance Public Bus Transport Management System (APBTMS) that aims to address these challenges for the benefit of both passengers and transport management authority. Our proposed system leverages various sensors and IoT (Internet of Things) modules deployed within buses to monitor various onboard activities and physical environmental factors. These enable the making of data-driven decisions in real-Time, Facilitating improved operational control. Key components of the system include GPS (Global Positioning System) tracking for real-Time bus location updates, passenger density/count through CV (computer Vision), and continuous monitoring of physical environmental factors such as temperature, humidity, sound magnitude, and vibration magnitude which facilitate accident/abnormalities detection, Fire detection and helps in continuously monitoring road quality. The application of CV technology, along with passenger count, can detect harm-causing objects inside a bus and can compare the faces of passengers with black-listed passengers (involved in previously reported crimes such as theft, and nuisance). Passengers benefit from these advancements through a dedicated mobile application. A User-friendly website is also offered to public bus transport management authority providing various useful functionalities. With the addition of safety features like real-Time speed detection and many other capabilities in the future, our proposed system can expand its benefits to school bus services and other public transportation services. © 2024

关键词： API (Application Programming Interface) AWS (Amazon Web Services) Cloud Computing CV (computer Vision) GPS (Global Positioning System) GSM (Global System for Mobile communication) IoT (Internet of Things) ML (Machine Learning)

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FESR - Framework to evaluate Software Reliability based on software metrics 24

FESR - Framework to evaluate Software Reliability based on s...

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8th International Conference on High Performance Compilation, Computing and Communications, HP3C 2024

作者： Fahad, Hurriya Ahmed, Irfan Mahmood, Jabar Saman Batool, Khadija Ali, Qasim Department of Computer Science University of Sialkot Sialkot Pakistan State Key Laboratory of Blockchain and Data Security School of Cyber Science and Technology College of Computer Science and Technology Zhejiang University Zhejiang Hangzhou310007 China

ISBN: (纸本)9798400716904

Evaluating reliability of software is hot concern for decision makers and software engineers seeing as if we assess, it cannot be mastered. It is common that reliability of system stratum could be employed for evaluating growth of testing of system with help of comparison of failure of currently implemented software with required system. It is also generic that reliability of system echelon assures improved utilization by the user consequently enhanced contentment of customers. In this paper, our goal is to put forward a meticulously analysis of reliability measurement process. As the existing approaches still lack software reliability, quality and its growth, successful generation of test cases, scalability with large software systems, cost and customer satisfaction. we have projected a new framework of software reliability measurement process based on software metrics. Our model is evaluated by comparing it with an existing model and a published case study. The control experiment is used to evaluate FESR Framework. © 2024 ACM.

关键词： Software quality

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Deep Learning based Intelligent System for Skin Disease Detection 10

Deep Learning based Intelligent System for Skin Disease Dete...

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10th International Conference on Communication and Signal Processing, ICCSP 2024

作者： Dhanush, K.B. Arul Xavier, V.M. Shyni, S.S. Karunya Institute of Technology and Sciences Division of Computer Science and Engineering Tamilnadu Coimbatore India Karunya Institute of Technology and Sciences Division of Data Science and Cyber Security Tamilnadu Coimbatore India

ISBN: (纸本)9798350353068

Malignant and benign skin diseases significantly impact public health and personal well-being. Traditional machine learning models encounter difficulties in processing image datasets, which is crucial for early and accurate diagnosis. This work employed two pre-trained deep learning models, ResNet50 and VGG19, known for their precise and swift image processing capabilities. These models underwent training utilizing an extensive dataset of images from patients battling benign keratosis, Melanoma, and Melanocytic nevus (Mole). The models were then tasked to distinguish between these three conditions. The results were remarkable, with the models achieving accuracies of 91.3 % and 95.6 %, respectively. A comparative analysis revealed that the VGG19 model outperformed in accurately identifying these three diseases, surpassing traditional AI and machine learning methods. The trained VGG19 model was subsequently incorporated into an Android application to enhance user experience. © 2024 IEEE.

关键词： Diagnosis

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