Computer Science and Information Systems最新文献

{"title":"Inverse halftoning based on sparse representation with boosted dictionary","authors":"Jun Yang, Zihao Liu, Li Chen, Ying Wu, Gang Ke","doi":"10.2298/csis220808022y","DOIUrl":"https://doi.org/10.2298/csis220808022y","url":null,"abstract":"Halftone image is widely used in printing and scanning equipment. It is significant for the halftone image to be preserved and processed. For the different resolution of the display devices, the processing and displaying of halftone image are faced with great challenges, such as Moore pattern and image blur ring. The inverse halftone technique is required to remove the halftone screen. In this paper, we propose an inverse halftone algorithm based on sparse representation with the dictionary learned by two steps: deconvolution and sparse optimization in the transform domain to remove the noise. The main contributions of this paper include three aspects: first, we analysis the denoising effects for different training sets and the dictionary; Then we propose the denoising algorithm through adaptively learning the dictionary, which iteratively remove the noise of the training set and improve the dictionary; Then the inverse halftone algorithm is proposed. Finally, we verify that the noise level in the error diffusion linear model is fixed, and the noise level is only related to the diffusion operator. Experimental results show that the proposed algorithm has better PSNR and visual performance than state-of-the-art methods. The codes and constructed models are available at https://github.com/juneryoung2022/IH-WNNM.","PeriodicalId":50636,"journal":{"name":"Computer Science and Information Systems","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82275490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Secure cloud internet of vehicles based on blockchain and data transmission scheme of map/reduce","authors":"Hua-Yi Lin","doi":"10.2298/csis220921056l","DOIUrl":"https://doi.org/10.2298/csis220921056l","url":null,"abstract":"Over the past few years, because of the popularity of the Internet of vehicles and cloud computing, the exchange of group information between vehicles is no longer out of reach. Through WiFi/5G wireless communication protocol, vehicles can instantly deliver traffic conditions and accidents to the back end or group vehicles traveling together, which can reduce traffic congestion and accidents. In addition, vehicles transmit real-time road conditions to the cloud vehicle management center, which can also share real-time road conditions and improve the road efficiency for pedestrians and drivers. However, the transmission of information in an open environment raises the issue of personal information security. Most of the security mechanisms provided by the existing Internet of vehicles require centralized authentication servers, which increase the burden of certificate management and computing. Moreover, the road side unit as a decentralized authentication center may be open to hacking or modification, but due to personal privacy and security concerns, vehicle-to-vehicle is not willing to share information with each other. Therefore, this study is conducted through blockchain to ensure the security of vehicle-based information transmission. Moreover, the elliptic curve Diffie-Hellman (ECDH) key exchange protocol and a secure conference key mechanism with direct user confirmation combined with the back-end cloud platform Map/Reduce is proposed to ensure the identities of Mappers and Reducers that participate in the cloud operation, avoid malicious participants to modify the transmission information, so as to achieve secure Map/Reduce operations, and improves vehicle and passenger traffic safety.","PeriodicalId":50636,"journal":{"name":"Computer Science and Information Systems","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87857815","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Guest editorial: Machine learning-based decision support systems in IoT systems","authors":"Mu-Yen Chen, J. Rubio, M. Ivanović","doi":"10.2298/csis230200ic","DOIUrl":"https://doi.org/10.2298/csis230200ic","url":null,"abstract":"<jats:p>nema</jats:p>","PeriodicalId":50636,"journal":{"name":"Computer Science and Information Systems","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86526123","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Blockchain-based model for tracking compliance with security requirements","authors":"Jelena Marjanovic, Nikola Dalčeković, G. Sladić","doi":"10.2298/csis210923060m","DOIUrl":"https://doi.org/10.2298/csis210923060m","url":null,"abstract":"The increasing threat landscape in Industrial Control Systems (ICS) brings different risk profiles with comprehensive impacts on society and safety. The complexity of cybersecurity risk assessment increases with a variety of third-party software components that comprise a modern ICS supply chain. A central issue in software supply chain security is the evaluation whether the secure development lifecycle process (SDL) is being methodologically and continuously practiced by all vendors. In this paper, we investigate the possibility of using a decentralized, tamper-proof system that will provide trustworthy visibility of the SDL metrics over a certain period, to any authorized auditing party. Results of the research provide a model for creating a blockchain-based approach that allows inclusion of auditors through a consortium decision while responding to SDL use cases defined by this paper. The resulting blockchain architecture successfully responded to requirements mandated by the security management practice as defined by IEC 62443-4-1 standard.","PeriodicalId":50636,"journal":{"name":"Computer Science and Information Systems","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87180384","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"SBEO: Smart Building Evacuation Ontology","authors":"Qasim Khalid, Alberto Fernández, Marin Lujak, Arnaud Doniec","doi":"10.2298/csis220118046k","DOIUrl":"https://doi.org/10.2298/csis220118046k","url":null,"abstract":"Semantically rich depiction of the concepts for context-aware indoor routing brings appealing benefits for the safety of occupants of smart spaces in emergency evacuation. In this paper, we propose Smart Building Evacuation Ontology (SBEO3), a reusable ontology for indoor spaces, based on three different data models: user, building, and context. We provide a common representation of indoor routing and navigation, describe users? characteristics and preferences, grouping of individuals and their role in a specific context, hazards, and emergency evacuation. Among other characteristics, we consider abilities of individuals, safety and accessibility of spaces related to each person, intensity, impact, and severity of an emergency event or activity. SBEO is flexible and compatible with other ontologies of its domain, including SEAS, SSN/SOSA, SEMA4A, and empathi. We evaluate SBEO based on several metrics demonstrating that it addresses the information needs for the context-aware route recommendation system for emergency evacuation in indoor spaces. In the end, a simulation-based application example exploits SBEO using Context-Aware Emergency Evacuation Software (CAREE).","PeriodicalId":50636,"journal":{"name":"Computer Science and Information Systems","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84719257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Probabilistic reasoning for diagnosis prediction of Coronavirus disease based on probabilistic ontology","authors":"Messaouda Fareh, Ishak Riali, Hafsa Kherbache, Marwa Guemmouz","doi":"10.2298/csis220829035f","DOIUrl":"https://doi.org/10.2298/csis220829035f","url":null,"abstract":"The novel Coronavirus has been declared a pandemic by the World Health Organization (WHO). Predicting the diagnosis of COVID-19 is essential for disease cure and control. The paper?s main aim is to predict the COVID-19 diagnosis using probabilistic ontologies to address the randomness and incomplete ness of knowledge. Our approach begins with constructing the entities, attributes, and relationships of COVID-19 ontology, by extracting symptoms and risk factors. The probabilistic components of COVID-19 ontology are developed by creating a Multi-Entity Bayesian Network, then determining its components, with the different nodes, as probability distribution linked to various nodes. We use probabilistic in ference for predicting COVID-19 diagnosis, using the Situation-Specific Bayesian Network (SSBN). To validate the solution, an experimental study is conducted on real cases, comparing the results of existing machine learning methods, our solution presents an encouraging result and, therefore enables fast medical assistance.","PeriodicalId":50636,"journal":{"name":"Computer Science and Information Systems","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91076399","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A study of identity authentication using blockchain technology in a 5G multi-type network environment","authors":"Jui-Hung Kao, Yu-Yu Yen, Wei-Chen Wu, Horng-Twu Liaw, Shiou-Wei Fan, Yi-Chen Kao","doi":"10.2298/csis221115070k","DOIUrl":"https://doi.org/10.2298/csis221115070k","url":null,"abstract":"The 5G technology, known for its large bandwidth, high speed, low latency, and multi-connection capabilities, significantly accelerates digital transformation in enterprises, especially in addressing factory automation challenges. It facilitates efficient machine-to-machine (M2M) and device-to-device (D2D) connectivity, ensuring rapid data transfer and seamless process convergence under 5G standards. Although 5G offers substantial communication and low latency benefits, its limited indoor coverage requires the deployment of decentralized antennas or small base stations. In contrast, Wi-Fi 6 seamlessly complements 5G, providing superior indoor mobile connectivity. This integration is crucial for businesses looking to accelerate digital transformation. To optimize 5G, the deployment of devices such as bypass switches, SDN switches, and MEC in the 5G Local Breakout network enables user access control and fast authentication. Real-world validation confirms the effectiveness of these measures, which are expected to lead to the future of 5G mobile networks.","PeriodicalId":50636,"journal":{"name":"Computer Science and Information Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135446193","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Applying spin checker on 5G EAP-TLS authentication protocol analysis","authors":"Qianli Wang","doi":"10.2298/csis230611068w","DOIUrl":"https://doi.org/10.2298/csis230611068w","url":null,"abstract":"Currently, there is relatively little formal analysis and verification work on the 5G EAP-TLS authentication protocol. In this paper, we use the model checker SPIN to perform a formal analysis of the 5G EAP-TLS authentication protocol. Firstly, we analyze the process of the 5G EAP-TLS authentication protocol and abstract it to obtain a formal model of the protocol. Then, we describe the construction of the protocol model based on the Promela language. The unique feature of this paper is the replacement of the hash value of the 5G EAP-TLS authentication protocol with the message content field encrypted by an unknown subject public key. This is because the Promela language in SPIN has an eval function that can check the value of each field. This can replace the function of the hash function and make the Promela model construction more portable. The paper analyzes the attack paths of the protocol and reveals design flaws that undermine the expected identity authentication attributes and secret consistency of the protocol. The results not only provide a comprehensive understanding of the security properties of the 5G EAP-TLS authentication protocol but also offer valuable insights and guidance for the verification of the protocol's security properties, security design, and optimization of protocol implementation and interoperability.","PeriodicalId":50636,"journal":{"name":"Computer Science and Information Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135446441","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"3D convolutional long short-term encoder-decoder network for moving object segmentation","authors":"Anil Turker, Ender Eksioglu","doi":"10.2298/csis230129044t","DOIUrl":"https://doi.org/10.2298/csis230129044t","url":null,"abstract":"Moving object segmentation (MOS) is one of the important and well studied computer vision tasks that is used in a variety of applications, such as video surveillance systems, human tracking, self-driving cars, and video compression. While traditional approaches to MOS rely on hand-crafted features or background modeling, deep learning methods using Convolution Neural Networks (CNNs) have been shown to be more effective in extracting features and achieving better accuracy. However, most deep learning-based methods for MOS offer scene-dependent solutions, leading to reduced performance when tested on previously unseen video content. Because spatial features are insufficient to represent the motion information, the spatial and temporal features should be used together to succeed in un seen videos. To address this issue, we propose the MOS-Net deep framework, an encoder-decoder network that combines spatial and temporal features using the flux tensor algorithm, 3D CNNs, and ConvLSTM in its different variants. MOS-Net 2.0 is an enhanced version of the base MOS-Net structure, where additional ConvL STM modules are added to 3D CNNs for extracting long-term spatiotemporal features. In the final stage of the framework the output of the encoder-decoder network, the foreground probability map, is thresholded for producing a binary mask where moving objects are in the foreground and the rest forms the background. In addition, an ablation study has been conducted to evaluate different combinations as inputs to the proposed network, using the ChangeDetection2014 (CDnet2014) which in cludes challenging videos such as those with dynamic backgrounds, bad weather, and illumination changes. In most approaches, the training and test strategy are not announced, making it difficult to compare the algorithm results. In addition, the pro posed method can be evaluated differently as video-optimized or video-agnostic. In video-optimized approaches, the training and test set is obtained randomly and sep arated from the overall dataset. The results of the proposed method are compared with competitive methods from the literature using the same evaluation strategy. It has been observed that the introduced MOS networks give highly competitive re sults on the CDnet2014 dataset. The source code for the simulations provided in this work is available online.","PeriodicalId":50636,"journal":{"name":"Computer Science and Information Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136206823","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Towards addressing item cold-start problem in collaborative filtering by embedding agglomerative clustering and FP-growth into the recommendation system","authors":"Eyad Kannout, Michał Grodzki, Marek Grzegorowski","doi":"10.2298/csis221116052k","DOIUrl":"https://doi.org/10.2298/csis221116052k","url":null,"abstract":"This paper introduces a frequent pattern mining framework for recommender systems (FPRS) - a novel approach to address the items? cold-start problem. This difficulty occurs when a new item hits the system, and properly handling such a situation is one of the key success factors of any deployment. The article proposes several strategies to combine collaborative and content-based filtering methods with frequent items mining and agglomerative clustering techniques to mitigate the cold-start problem in recommender systems. The experiments evaluated the developed methods against several quality metrics on three benchmark datasets. The conducted study confirmed usefulness of FPRS in providing apt outcomes even for cold items. The presented solution can be integrated with many different approaches and further extended to make up a complete and standalone RS.","PeriodicalId":50636,"journal":{"name":"Computer Science and Information Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136208670","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}