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35th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2024

作者： Kim, Jihye Park, Jaehyoung Lee, Jong-Hyouk Sejong University Dept. of Computer and Information Security Seoul Korea Republic of Sejong University Dept. of Computer and Information Security & Convergence Engineering for Intelligent Drone Seoul Korea Republic of

ISBN: (纸本)9798350362244

In anticipation of the 5G-Advanced and 6G era, this paper explores Open RAN as an innovative solution to enhance the existing Radio Access Network (RAN) capabilities, particularly in managing the surge in mobile traffic. The O-RAN Alliance has made significant strides in this domain, particularly by releasing a comprehensive standard document addressing potential security threats and necessary countermeasures within Open RAN frameworks. A critical aspect of these standards is the emphasis on safeguarding the E2 interface-linking the NearRT RIC and RAN nodes-against Man-in-the-Middle (MitM) attacks, with IPsec proposed as a key defensive mechanism. Our study, however, reveals a vulnerability: the E2 interface remains susceptible to ARP spoofing, a variant of MitM attacks. This paper presents detailed simulation results to demonstrate this security flaw and delves into the potential ramifications on the E2 interface's functionality and integrity. Our findings underscore the need for revisiting and reinforcing security protocols in the evolving landscape of Open RAN networks. © 2024 IEEE.

关键词： Radio access networks

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A Self-Adaptive Access Control Framework Based on User Attributes Among Heterogeneous Internet of Things Platforms 9

A Self-Adaptive Access Control Framework Based on User Attri...

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Joint 9th International Conference on Digital Arts, Media and Technology with 7th ECTI Northern Section Conference on Electrical, Electronics, computer and Telecommunications engineering, ECTI DAMT and NCON 2024

作者： Park, Jihoon Koo, Jahoon Kim, Young-Gab Sejong University Dept. of Computer and Information Security and Convergence Engineering for Intelligent Drone Seoul Korea Republic of Sejong University Dept. of Computer and Information Security Seoul Korea Republic of

ISBN: (纸本)9798350318241

Internet of Things (IoT) platforms are being actively designed to provide various services to users. However, most IoT platforms are developed in independent environments, causing difficulties in their interoperability. Even though heterogeneous IoT platforms employ the same attribute-based access control (ABAC) model to protect their resources, the attribute representation methods used by these platforms differ. Consequently, a semantic interoperability problem arises, wherein users of one platform cannot access the resources from other platforms, even though these users possess valid attributes. Therefore, this paper proposes a framework that can interoperate by understanding different attribute representation methods among heterogeneous IoT platforms that employ the same ABAC model. Our framework uses self-adaptive modules monitor-analyze-plan-execute over a shared knowledge (MAPE-K) to solve semantic interoperability problems arising from differences in attribute representations, even with valid attributes, enabling access to resources between heterogeneous IoT platforms. © 2024 IEEE.

关键词： Internet of things

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A Novel Identity Authentication Mechanism forUnmanned Maritime Vessels Communication Based on MITRE ATT&CK Framework

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Journal of Marine Science and Technology (Taiwan) 2024年第2期32卷 170-180页

作者： He, Jun-Xian Chang, Shih-Hao Dept. of Computer Science and Information Engineering Tamkang University New Taipei City Taiwan Dept. of Computer Science and Information Engineering National Taipei University of Technology Taipei City Taiwan

With the development of the smart shipping industry, unmanned vessel technology is rapidly evolving, accompanied by a demand for robust Internet of Things (IoT) communication security practices. Key communication technologies for the operation of unmanned vessels include external vessel communication. One crucial aspect is the verification of the identities of the parties involved in these communication systems, as this ensures secure and trusted interactions between unmanned vessels and port management authorities. Identity authentication plays a vital role in ensuring the secure communication of unmanned vessels. This paper aims to analyze potential risks related to identity authentication technology in unmanned vessel communication systems. To effectively address these risks, we propose leveraging digital certificates and blockchain technology to achieve device non-repudiation and substitution. Based on this technology, we organize and implement defense strategies using the MITRE ATT&CK framework. This framework provides a comprehensive and systematic approach to understanding potential threats and designing appropriate defense measures. By utilizing this framework, security teams can better comprehend vulnerabilities and formulate effective countermeasures. To validate the effectiveness of the proposed defense framework, we conducted simulation experiments. These experiments helped us evaluate the efficiency and reliability of the strategies in real-world scenarios. Through these experiments, we could ascertain whether the countermeasures effectively mitigated the identified risks and ensured the secure communication of unmanned vessels. © 2024 National Taiwan Ocean University

关键词： Risk assessment

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Experimental Approach to Internal security Threats for 5G-Advanced Core Networks 35

Experimental Approach to Internal Security Threats for 5G-Ad...

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35th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2024

作者： Park, Jaehyoung Kim, Jihye Woo, Seungchan Park, Kyungmin Kim, Jonghyun Lee, Jong-Hyouk Sejong University Dept. of Computer and Information Security & Convergence Engineering for Intelligent Drone Seoul Korea Republic of Sejong University Dept. of Computer and Information Security Seoul Korea Republic of Sejong University Dept. of Computer and Information Security & Convergence Engineering for Metaverse Seoul Korea Republic of Electronics and Telecommunications Research Institute Daejeon Korea Republic of

ISBN: (纸本)9798350362244

As we embrace the dawn of the 5G era, the fusion of Software Defined Network (SDN) and Network Function Virtualization (NFV) technologies has heralded a new epoch in network architecture. This provides indispensable capabilities and virtualized infrastructure to meet the burgeoning demands of modern networks. Yet, with each stride forward in mobile communication technology, security threats loom larger, casting a shadow over the very fabric of our networks. In this context, identifying and addressing these threats is crucial as it plays a key role in enhancing the security of a 5G-Advanced and a next 6G mobile communication technologies. Therefore, this paper undertakes an investigative journey to explore security threats introduced by SDN/NFV technologies in the 5G-Advanced core networks. Through our simulations, we unveil a need for fortified security technologies within the 5G-Advanced core networks, illuminating a path towards the creation of bespoke datasets tailored for the trends of 5G-Advanced security research. © 2024 IEEE.

关键词： 5G mobile communication systems

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Hybrid CNN-ViT architecture to exploit spatio-temporal feature for fire recognition trained through transfer learning

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Multimedia Tools and Applications 2025年第8期84卷 4703-4732页

作者： Shahid, Mohammad Wang, Hong-Cyuan Chen, Yung-Yao Hua, Kai-Lung Dept. of Computer Science and Information Engineering National Taiwan University of Science and Technology Taipei Taiwan Dept. of Electronic and Computer Engineering National Taiwan University of Science and Technology Taipei Taiwan

Fires are becoming one of the major natural hazards that threaten the ecology, economy, human life and even more worldwide. Therefore, early fire detection systems are crucial to prevent fires from spreading out of control and causing destruction. Based on vision sensors, many fire detection techniques have evolved with the recent surge of curiosity in deep learning, which exploits the spatial features of individual images. However, fire can take different forms, scales, and combustion materials can produce different colors, making accurate fire detection from an image challenging. Small fires captured from long-distance cameras lack salient features, further complicating detection. This paper proposes a hybrid structure that uses attention-enhanced convolutional neural networks and vision transformers (CNN-ViT) to detect fire. The proposed CNN-ViT first pays spatial attention to every frame and then aggregates temporal contextual information from neighboring frames to improve detection performance. Due to the limited availability of training fire datasets, the study employs deep transfer learning for feature extraction using pre-trained CNN. We used various metrics to examine the efficacy of the proposed approach. The results showed that the CNN-ViT method outperformed previous models based on spatial-temporal characteristics by achieving a relative improvement in accuracy and F1 score. The satisfactory results on images contaminated with different intensities of noise confirm the robustness of the approach. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Fires

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A Novel Music Recommendation System Using Filtering Techniques

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Informatica (Slovenia) 2024年第4期48卷 595-610页

作者： Vashishtha, Srishti Varshney, Deepika Sarin, Eva Kaur, Simran Computer Science and Engineering Dept. Bharati Vidyapeeth’s College of Engineering GGSIPU New Delhi India Computer Science and Engineering Dept. Jaypee Institute of Information Technology Noida India

With the growth of the World Wide Web, a large amount of music data is available on the Internet. A large number of people listen to music online rather than downloading and listening offline. But only some sites provide personalized and accurately recommended songs while they listen to an auto-playing playlist. Hence the need for recommendation systems arises. Two approaches can be applied to the recommendation system: content based filtering and collaborative filtering. While in content-based filtering approach, analysis on the songs’ content which has been preferred by the user in history is done and the songs with relative similarity are recommended. While latter suggests songs that certain users of similar listening pattern have preferred. But collaborative filtering-based recommendation systems not only requires time to attain stability but also might recommend unsuitable music because it is not personalized to each user’s preference. Also, the latter requires the songs to be listened by a few users already to recommend it any other user. Hence for overall analysis, answers to few questions need to be implemented in recommendation systems: the very first one is how the properties should be analyzed, next one is how the analysis should be done and last is how the songs related to the user’s preference should be chosen. So, for suggesting the better system which solves these three questions as well as provides better and personalized recommendations, In this paper we build a collaborative filtering as well as content based filtering recommendation system, where various factors determine the essence of the songs, i.e. liveliness, keys used, loudness, pitch, valence, etc., are analyzed for comparison. From the experimental analysis in has been identified that content-based filtering technique performed best on KNN machine learning classifier with accuracy of 85%. © 2024 Slovene Society Informatika. All rights reserved.

关键词： Collaborative filtering

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A Method for De-Identification Analysis of Encrypted Video 9

A Method for De-Identification Analysis of Encrypted Video

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作者： Kim, Deok-Han Kim, Young-Gab Sejong University Dept. of Computer and Information Security and Convergence Engineering for Intelligent Drone Seoul Korea Republic of

ISBN: (纸本)9798350318241

As the variety of video content increases, so does the likelihood of data breaches of sensitive personal information. Consequently, several video de-identification techniques have been developed to protect personal data, alongside ongoing research into video encryption technology, which offers the advantage of decryption to obtain the original video without storing a separate video copy. While it is possible to visually evaluate whether individual encrypted frames have been correctly de-identified, human interpretation makes this method vulnerable to subjective bias. Many video encryption studies employ traditional image quality evaluation metrics, such as peak signal-to-noise ratio and structural similarity index measure (SSIM), to objectively demonstrate the de-identification of encrypted videos. However, these metrics prove to be insufficiently effective for this purpose. These image metrics can measure the de-identification rate of a single frame in encrypted videos, but not the entire video. This study introduces a quantitative analysis method to confirm de-identification in fully encrypted videos. In this study, we measured the de-identification rates of all frames of encrypted videos using a weighted sum of SSIM and edge differential ratio. We also measured the de-identification rate of a fully encrypted video. Finally, we graphically analyzed these data using line charts. This objective methodology enabled the identification of portions of the encrypted video where de-identification techniques may not have been appropriately applied. © 2024 IEEE.

关键词： Quality control

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Framework for Cloud-Based Data Management in Autonomous Vehicles

Framework for Cloud-Based Data Management in Autonomous Vehi...

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2025 IEEE International Students' Conference on Electrical, Electronics and computer Science, SCEECS 2025

作者： Pallapothu, Harshith Gopi Krishna, G. Sunil, Digvijay Teja Yadav, S. Nagasundari, S. Pes University Dept. of Computer Science & Engineering Bengaluru India Research Center for Information Security Forensics and Cyber Resilience Pes University Dept. of Computer Science & Engineering Bengaluru India

ISBN: (纸本)9798331529833

The increasing adoption of autonomous vehicles has driven the need for robust data management solutions that support real-time operations and ensure vehicle safety and efficiency. This work introduces a cloud-based framework for management of sensor data from autonomous vehicles, focusing on optimizing payload transmission rates. The framework leverages AWS IoT Core and AWS IoT Analytics to ensure efficient data flow from vehicle sensors to cloud storage. This framework demonstrates its potential for scalable deployment in real-world autonomous vehicle networks, contributing to the evolution of connected vehicle technologies and intelligent transport systems. This framework ensures reliable data transmission up to 250 payloads per second, beyond which data loss occurs. © 2025 IEEE.

关键词： Cloud platforms

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Copyright and License Agreement History Management Framework for Outsourced Software

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2023 IEEE International Conference on Metaverse Computing, Networking and Applications, MetaCom 2023

作者： Lee, Taeyang Lee, Jinsue Woo, Seungchan Lee, Jong-Hyouk Sejong University Dept. of Computer and Information Security and Convergence Engineering for Intelligent Drone Seoul Korea Republic of Sejong University Dept. of Computer and Information Security Seoul Korea Republic of

ISBN: (纸本)9798350333336

The practice of transitioning software development tasks to outsourcing has become increasingly prevalent. However, this approach presents challenges in systematically managing the historical records of copyright and license agreements associated with outsourced software. To address potential conflicts between clients and vendors in outsourced software transactions, this paper introduces a framework for effectively managing the history of copyright and license agreements pertaining to outsourced software. © 2023 IEEE.

关键词： Smart contract

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Decentralized Identifier System for Software Copyright Transfer and License Management

Decentralized Identifier System for Software Copyright Trans...

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2023 IEEE International Conference on Metaverse Computing, Networking and Applications, MetaCom 2023

作者： Woo, Seungchan Lee, Taeyang Lee, Jong-Hyouk Sejong University Dept. of Computer and Information Security Seoul Korea Republic of Sejong University Dept. of Computer and Information Security and Convergence Engineering for Intelligent Drone Seoul Korea Republic of

ISBN: (纸本)9798350333336

This paper presents a distributed identifier (DID) system that offers transparent and traceable outsourcing support platform for software development. The proposed system is designed to ensure the privacy of contracting parties during the copyright transfer and license contract process, thereby creating a fair and transparent outsourcing market. By leveraging a DID system, our approach ensures that no single entity controls the information, which increases the overall security and reliability of the system. Also, it reduces corporate losses due to noncompliance with copyright and license contracts. © 2023 IEEE.

关键词： Outsourcing

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