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39 pages, 2628 KiB  
Article
A Decentralized Multi-Venue Real-Time Video Broadcasting System Integrating Chain Topology and Intelligent Self-Healing Mechanisms
by Tianpei Guo, Ziwen Song, Haotian Xin and Guoyang Liu
Appl. Sci. 2025, 15(14), 8043; https://doi.org/10.3390/app15148043 - 19 Jul 2025
Viewed by 450
Abstract
The rapid growth in large-scale distributed video conferencing, remote education, and real-time broadcasting poses significant challenges to traditional centralized streaming systems, particularly regarding scalability, cost, and reliability under high concurrency. Centralized approaches often encounter bottlenecks, increased bandwidth expenses, and diminished fault tolerance. This [...] Read more.
The rapid growth in large-scale distributed video conferencing, remote education, and real-time broadcasting poses significant challenges to traditional centralized streaming systems, particularly regarding scalability, cost, and reliability under high concurrency. Centralized approaches often encounter bottlenecks, increased bandwidth expenses, and diminished fault tolerance. This paper proposes a novel decentralized real-time broadcasting system employing a peer-to-peer (P2P) chain topology based on IPv6 networking and the Secure Reliable Transport (SRT) protocol. By exploiting the global addressing capability of IPv6, our solution simplifies direct node interconnections, effectively eliminating complexities associated with Network Address Translation (NAT). Furthermore, we introduce an innovative chain-relay transmission method combined with distributed node management strategies, substantially reducing reliance on central servers and minimizing deployment complexity. Leveraging SRT’s low-latency UDP transmission, packet retransmission, congestion control, and AES-128/256 encryption, the proposed system ensures robust security and high video stream quality across wide-area networks. Additionally, a WebSocket-based real-time fault detection algorithm coupled with a rapid fallback self-healing mechanism is developed, enabling millisecond-level fault detection and swift restoration of disrupted links. Extensive performance evaluations using Video Multi-Resolution Fidelity (VMRF) metrics across geographically diverse and heterogeneous environments confirm significant performance gains. Specifically, our approach achieves substantial improvements in latency, video quality stability, and fault tolerance over existing P2P methods, along with over tenfold enhancements in frame rates compared with conventional RTMP-based solutions, thereby demonstrating its efficacy, scalability, and cost-effectiveness for real-time video streaming applications. Full article
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18 pages, 7391 KiB  
Article
Reliable QoE Prediction in IMVCAs Using an LMM-Based Agent
by Michael Sidorov, Tamir Berger, Jonathan Sterenson, Raz Birman and Ofer Hadar
Sensors 2025, 25(14), 4450; https://doi.org/10.3390/s25144450 - 17 Jul 2025
Viewed by 269
Abstract
Face-to-face interaction is one of the most natural forms of human communication. Unsurprisingly, Video Conferencing (VC) Applications have experienced a significant rise in demand over the past decade. With the widespread availability of cellular devices equipped with high-resolution cameras, Instant Messaging Video Call [...] Read more.
Face-to-face interaction is one of the most natural forms of human communication. Unsurprisingly, Video Conferencing (VC) Applications have experienced a significant rise in demand over the past decade. With the widespread availability of cellular devices equipped with high-resolution cameras, Instant Messaging Video Call Applications (IMVCAs) now constitute a substantial portion of VC communications. Given the multitude of IMVCA options, maintaining a high Quality of Experience (QoE) is critical. While content providers can measure QoE directly through end-to-end connections, Internet Service Providers (ISPs) must infer QoE indirectly from network traffic—a non-trivial task, especially when most traffic is encrypted. In this paper, we analyze a large dataset collected from WhatsApp IMVCA, comprising over 25,000 s of VC sessions. We apply four Machine Learning (ML) algorithms and a Large Multimodal Model (LMM)-based agent, achieving mean errors of 4.61%, 5.36%, and 13.24% for three popular QoE metrics: BRISQUE, PIQE, and FPS, respectively. Full article
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24 pages, 76230 KiB  
Article
Secure and Efficient Video Management: A Novel Framework for CCTV Surveillance Systems
by Swarnalatha Camalapuram Subramanyam, Ansuman Bhattacharya and Koushik Sinha
IoT 2025, 6(3), 38; https://doi.org/10.3390/iot6030038 - 4 Jul 2025
Viewed by 334
Abstract
This paper presents a novel video encoding and decoding method aimed at enhancing security and reducing storage requirements, particularly for CCTV systems. The technique merges two video streams of matching frame dimensions into a single stream, optimizing disk space usage without compromising video [...] Read more.
This paper presents a novel video encoding and decoding method aimed at enhancing security and reducing storage requirements, particularly for CCTV systems. The technique merges two video streams of matching frame dimensions into a single stream, optimizing disk space usage without compromising video quality. The combined video is secured using an advanced encryption standard (AES)-based shift algorithm that rearranges pixel positions, preventing unauthorized access. During decoding, the AES shift is reversed, enabling precise reconstruction of the original videos. This approach provides a space-efficient and secure solution for managing multiple video feeds while ensuring accurate recovery of the original content. The experimental results demonstrate that the transmission time for the encoded video is consistently shorter compared to transmitting the video streams separately. This, in turn, leads to about 54% reduction in energy consumption across diverse outdoor and indoor video datasets, highlighting significant improvements in both transmission efficiency and energy savings by our proposed scheme. Full article
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26 pages, 5350 KiB  
Article
Secure Image Transmission Using Multilevel Chaotic Encryption and Video Steganography
by Suhad Naji Alrekaby, Maisa’a Abid Ali Khodher, Layth Kamil Adday and Reem Aljuaidi
Algorithms 2025, 18(7), 406; https://doi.org/10.3390/a18070406 - 1 Jul 2025
Viewed by 408
Abstract
The swift advancement of information and communication technology has made it increasingly difficult to guarantee the security of transmitted data. Traditional encryption techniques, particularly in multimedia applications, frequently fail to defend against sophisticated attacks, such as chosen-plaintext, differential, and statistical analysis attacks. More [...] Read more.
The swift advancement of information and communication technology has made it increasingly difficult to guarantee the security of transmitted data. Traditional encryption techniques, particularly in multimedia applications, frequently fail to defend against sophisticated attacks, such as chosen-plaintext, differential, and statistical analysis attacks. More often than not, traditional cryptographic methods lack proper diffusion and sufficient randomness, which is why they are vulnerable to these types of attacks. By combining multi-level chaotic maps with Least Significant Bit (LSB) steganography and Advanced Encryption Standard (AES) encryption, this study proposes an improved security approach for picture transmission. A hybrid chaotic system dynamically creates the encryption keys, guaranteeing high unpredictability and resistance to brute-force attacks. Next, it incorporates the encrypted images into video frames, making it challenging to find the secret data. The suggested method demonstrates its resilience to statistical attacks by achieving entropy values over 7.99 and number of pixels change rate (NPCR) values above 99.63% in contrast to traditional encryption techniques, showing how resilient it is to statistical attacks. Our hybrid approach improves data secrecy and resistance to various cryptographic attacks. Experimental results confirm the efficiency of the suggested technique by achieving entropy values around 7.99, number of pixels change rate (NPCR) values above 99.63%, and unified average changing intensity (UACI) values over 31.98%, ensuring the secure transmission of sensitive images while maintaining video imperceptibility. Full article
(This article belongs to the Section Parallel and Distributed Algorithms)
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34 pages, 7040 KiB  
Article
A Practical Implementation of Post-Quantum Cryptography for Secure Wireless Communication
by Babatunde Ojetunde, Takuya Kurihara, Kazuto Yano, Toshikazu Sakano and Hiroyuki Yokoyama
Network 2025, 5(2), 20; https://doi.org/10.3390/network5020020 - 10 Jun 2025
Viewed by 691
Abstract
Recent advances in quantum computing have prompted urgent consideration of the migration of classical cryptographic systems to post-quantum alternatives. However, it is impossible to fully understand the impact that migrating to current Post-Quantum Cryptography (PQC) algorithms will have on various applications without the [...] Read more.
Recent advances in quantum computing have prompted urgent consideration of the migration of classical cryptographic systems to post-quantum alternatives. However, it is impossible to fully understand the impact that migrating to current Post-Quantum Cryptography (PQC) algorithms will have on various applications without the actual implementation of quantum-resistant cryptography. On the other hand, PQC algorithms come with complexity and long processing times, which may impact the quality of service (QoS) of many applications. Therefore, PQC-based protocols with practical implementations across various applications are essential. This paper introduces a new framework for PQC standalone and PQC–AES (Advanced Encryption Standard) hybrid public-key encryption (PKE) protocols. Building on prior results, we focus on securing applications such as file transfer, video streaming, and chat-based communication using enhanced PQC-based protocols. The extended PQC-based protocols use a sequence number-based mechanism to effectively counter replay and man-in-the-middle attacks and mitigate standard cybersecurity attack vectors. Experimental evaluations examined encryption/decryption speeds, throughput, and processing overhead for the standalone PQC and the PQC–AES hybrid schemes, benchmarking them against traditional AES-256 in an existing client–server environment. The results demonstrate that the new approaches achieve a significant balance between security and system performance compared to conventional deployments. Furthermore, a comprehensive security analysis confirms the robustness and effectiveness of the proposed PQC-based protocols across diverse attack scenarios. Notably, the PQC–AES hybrid protocol demonstrates greater efficiency for applications handling larger data volumes (e.g., 10–100 KB) with reduced latency, underscoring the practical necessity of carefully balancing security and operational efficiency in the post-quantum migration process. Full article
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29 pages, 6716 KiB  
Article
Mitigating Transmission Errors: A Forward Error Correction-Based Framework for Enhancing Objective Video Quality
by Muhammad Babar Imtiaz and Rabia Kamran
Sensors 2025, 25(11), 3503; https://doi.org/10.3390/s25113503 - 1 Jun 2025
Viewed by 762
Abstract
In video transmission, maintaining high visual quality under variable network conditions, including bandwidth and efficiency, is essential for optimal viewer experience. Channel errors or malicious attacks during transmission can cause degradation in video quality, affecting its secure transmission and putting its confidentiality and [...] Read more.
In video transmission, maintaining high visual quality under variable network conditions, including bandwidth and efficiency, is essential for optimal viewer experience. Channel errors or malicious attacks during transmission can cause degradation in video quality, affecting its secure transmission and putting its confidentiality and integrity at risk. This paper presents a novel approach to enhancing objective video quality by integrating an energy-efficient forward error correction (FEC) technique into video encoding and transmission processes. Moreover, it ensures that the video contents remain secure and unintelligible to unauthorized parties. This is achieved by combining H.264/AVC syntax-based encryption and decryption algorithms with error correction during the video coding process to provide end-to-end confidentiality. Unlike traditional error correction strategies, our approach dynamically adjusts redundancy levels based on real-time network conditions, optimizing bandwidth utilization without compromising quality. The proposed framework is evaluated across full reference objective video quality metrics, demonstrating significant improvements in the peak signal-to-noise ratio (PSNR) and PSNR611 of the recovered videos. Experiments are carried out on multiple test video sequences with different video resolutions having various characteristics, i.e., colors, motions, and structures, and confirm that the FEC-based solution effectively detects and corrects packet loss and transmission errors without the need for retransmission, reducing the impact of channel noise and accidental disruptions on visual quality in challenging network environments. This study contributes to the development of resilient video transmission systems with reduced computational complexity of the codec and provides insights into the role of FEC in addressing quality degradation in modern multimedia applications where low latency is crucial. Full article
(This article belongs to the Section Sensor Networks)
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15 pages, 671 KiB  
Article
A Simultaneous Decomposition for a Quaternion Tensor Quaternity with Applications
by Jia-Wei Huo, Yun-Ze Xu and Zhuo-Heng He
Mathematics 2025, 13(10), 1679; https://doi.org/10.3390/math13101679 - 20 May 2025
Viewed by 302
Abstract
Quaternion tensor decompositions have recently been the center of focus due to their wide potential applications in color data processing. In this paper, we establish a simultaneous decomposition for a quaternion tensor quaternity under Einstein product. The decomposition brings the quaternity of four [...] Read more.
Quaternion tensor decompositions have recently been the center of focus due to their wide potential applications in color data processing. In this paper, we establish a simultaneous decomposition for a quaternion tensor quaternity under Einstein product. The decomposition brings the quaternity of four quaternion tensors into a canonical form, which only has 0 and 1 entries. The structure of the canonical form is discussed in detail. Moreover, the proposed decomposition is applied to a new framework of color video encryption and decryption based on discrete wavelet transform. This new approach can realize simultaneous encryption and compression with high security. Full article
(This article belongs to the Special Issue Advanced Numerical Linear Algebra)
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21 pages, 732 KiB  
Article
Efficient Access Control for Video Anomaly Detection Using ABE-Based User-Level Revocation with Ciphertext and Index Updates
by Lu Jiang, Jielu Yan, Weizhi Xian, Xuekai Wei and Xiaofeng Liao
Appl. Sci. 2025, 15(9), 5128; https://doi.org/10.3390/app15095128 - 5 May 2025
Cited by 1 | Viewed by 484
Abstract
With the widespread deployment of video surveillance systems, effective access control is essential to enhance the accuracy and security of video anomaly detection. This paper proposes a Searchable and Revocable Attribute-Based Encryption scheme (ABE-RS) that is specifically designed for dynamic video anomaly detection [...] Read more.
With the widespread deployment of video surveillance systems, effective access control is essential to enhance the accuracy and security of video anomaly detection. This paper proposes a Searchable and Revocable Attribute-Based Encryption scheme (ABE-RS) that is specifically designed for dynamic video anomaly detection scenarios. By integrating a user management tree structure, attribute-based key distribution, and keyword grouping techniques, the proposed scheme enables efficient user-level revocation along with dynamic updates to ciphertexts and keyword indexes. Furthermore, an inverted index structure is introduced to accelerate keyword search, facilitating the rapid detection and retrieval of anomalous video events. Formal security analysis demonstrates that the scheme is secure against chosen plaintext attacks (CPAs) and chosen keyword attacks (CKAs). The experimental results demonstrate that the scheme maintains millisecond-level revocation efficiency in methodology involving 512 users and either 50 attributes or a thousand keywords. Full article
(This article belongs to the Special Issue Pattern Recognition in Video Processing)
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21 pages, 19569 KiB  
Article
The General Solution to a System of Tensor Equations over the Split Quaternion Algebra with Applications
by Zong-Ru Jia and Qing-Wen Wang
Mathematics 2025, 13(4), 644; https://doi.org/10.3390/math13040644 - 16 Feb 2025
Cited by 4 | Viewed by 478
Abstract
This paper presents a systematic investigation into the solvability and the general solution of a tensor equation system within the split quaternion algebra framework. As an extension of classical quaternions with distinctive pseudo-Euclidean properties, split quaternions offer unique advantages in multidimensional signal processing [...] Read more.
This paper presents a systematic investigation into the solvability and the general solution of a tensor equation system within the split quaternion algebra framework. As an extension of classical quaternions with distinctive pseudo-Euclidean properties, split quaternions offer unique advantages in multidimensional signal processing applications. We establish rigorous necessary and sufficient conditions for the existence of solutions to the proposed tensor equation system, accompanied by explicit formulations for general solutions when solvability criteria are satisfied. The theoretical framework is further strengthened by the development of computational algorithms and numerical validations through concrete examples. Notably, we demonstrate the practical implementation of our theoretical findings through encryption/decryption algorithms for color video data. Full article
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28 pages, 10234 KiB  
Article
Estimating QoE from Encrypted Video Conferencing Traffic
by Michael Sidorov, Raz Birman, Ofer Hadar and Amit Dvir
Sensors 2025, 25(4), 1009; https://doi.org/10.3390/s25041009 - 8 Feb 2025
Cited by 1 | Viewed by 996
Abstract
Traffic encryption is vital for internet security but complicates analytical applications like video delivery optimization or quality of experience (QoE) estimation, which often rely on clear text data. While many models address the problem of QoE prediction in video streaming, the video conferencing [...] Read more.
Traffic encryption is vital for internet security but complicates analytical applications like video delivery optimization or quality of experience (QoE) estimation, which often rely on clear text data. While many models address the problem of QoE prediction in video streaming, the video conferencing (VC) domain remains underexplored despite rising demand for these applications. Existing models often provide low-resolution predictions, categorizing QoE into broad classes such as “high” or “low”, rather than providing precise, continuous predictions. Moreover, most models focus on clear-text rather than encrypted traffic. This paper addresses these challenges by analyzing a large dataset of Zoom sessions and training five classical machine learning (ML) models and two custom deep neural networks (DNNs) to predict three QoE indicators: frames per second (FPS), resolution (R), and the naturalness image quality evaluator (NIQE). The models achieve mean error rates of 8.27%, 7.56%, and 2.08% for FPS, R, and NIQE, respectively, using a 10-fold cross-validation technique. This approach advances QoE assessment for encrypted traffic in VC applications. Full article
(This article belongs to the Special Issue Machine Learning in Image/Video Processing and Sensing)
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27 pages, 5786 KiB  
Article
Drone-Captured Wildlife Data Encryption: A Hybrid 1D–2D Memory Cellular Automata Scheme with Chaotic Mapping and SHA-256
by Akram Belazi and Héctor Migallón
Mathematics 2024, 12(22), 3602; https://doi.org/10.3390/math12223602 - 18 Nov 2024
Viewed by 1129
Abstract
In contemporary wildlife conservation, drones have become essential for the non-invasive monitoring of animal populations and habitats. However, the sensitive data captured by drones, including images and videos, require robust encryption to prevent unauthorized access and exploitation. This paper presents a novel encryption [...] Read more.
In contemporary wildlife conservation, drones have become essential for the non-invasive monitoring of animal populations and habitats. However, the sensitive data captured by drones, including images and videos, require robust encryption to prevent unauthorized access and exploitation. This paper presents a novel encryption algorithm designed specifically for safeguarding wildlife data. The proposed approach integrates one-dimensional and two-dimensional memory cellular automata (1D MCA and 2D MCA) with a bitwise XOR operation as an intermediate confusion layer. The 2D MCA, guided by chaotic rules from the sine-exponential (SE) map, utilizes varying neighbor configurations to enhance both diffusion and confusion, making the encryption more resilient to attacks. A final layer of 1D MCA, controlled by pseudo-random number generators, ensures comprehensive diffusion and confusion across the image. The SHA-256 hash of the input image is used to derive encryption parameters, providing resistance against plaintext attacks. Extensive performance evaluations demonstrate the effectiveness of the proposed scheme, which balances security and complexity while outperforming existing algorithms. Full article
(This article belongs to the Special Issue Chaos-Based Secure Communication and Cryptography, 2nd Edition)
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23 pages, 619 KiB  
Article
A System of Tensor Equations over the Dual Split Quaternion Algebra with an Application
by Liuqing Yang, Qing-Wen Wang and Zuliang Kou
Mathematics 2024, 12(22), 3571; https://doi.org/10.3390/math12223571 - 15 Nov 2024
Cited by 4 | Viewed by 911
Abstract
In this paper, we propose a definition of block tensors and the real representation of tensors. Equipped with the simplification method, i.e., the real representation along with the M-P inverse, we demonstrate the conditions that are necessary and sufficient for the system of [...] Read more.
In this paper, we propose a definition of block tensors and the real representation of tensors. Equipped with the simplification method, i.e., the real representation along with the M-P inverse, we demonstrate the conditions that are necessary and sufficient for the system of dual split quaternion tensor equations (ANX,XSC)=(B,D), when its solution exists. Furthermore, the general expression of the solution is also provided when the solution of the system exists, and we use a numerical example to validate it in the last section. To the best of our knowledge, this is the first time that the aforementioned tensor system has been examined on dual split quaternion algebra. Additionally, we provide its equivalent conditions when its Hermitian solution X=X and η-Hermitian solutions X=Xη exist. Subsequently, we discuss two special dual split quaternion tensor equations. Last but not least, we propose an application for encrypting and decrypting two color videos, and we validate this algorithm through a specific example. Full article
(This article belongs to the Special Issue Advances of Linear and Multilinear Algebra)
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21 pages, 34834 KiB  
Article
A Multilayer Nonlinear Permutation Framework and Its Demonstration in Lightweight Image Encryption
by Cemile İnce, Kenan İnce and Davut Hanbay
Entropy 2024, 26(10), 885; https://doi.org/10.3390/e26100885 - 21 Oct 2024
Cited by 1 | Viewed by 1163
Abstract
As information systems become more widespread, data security becomes increasingly important. While traditional encryption methods provide effective protection against unauthorized access, they often struggle with multimedia data like images and videos. This necessitates specialized image encryption approaches. With the rise of mobile and [...] Read more.
As information systems become more widespread, data security becomes increasingly important. While traditional encryption methods provide effective protection against unauthorized access, they often struggle with multimedia data like images and videos. This necessitates specialized image encryption approaches. With the rise of mobile and Internet of Things (IoT) devices, lightweight image encryption algorithms are crucial for resource-constrained environments. These algorithms have applications in various domains, including medical imaging and surveillance systems. However, the biggest challenge of lightweight algorithms is balancing strong security with limited hardware resources. This work introduces a novel nonlinear matrix permutation approach applicable to both confusion and diffusion phases in lightweight image encryption. The proposed method utilizes three different chaotic maps in harmony, namely a 2D Zaslavsky map, 1D Chebyshev map, and 1D logistic map, to generate number sequences for permutation and diffusion. Evaluation using various metrics confirms the method’s efficiency and its potential as a robust encryption framework. The proposed scheme was tested with 14 color images in the SIPI dataset. This approach achieves high performance by processing each image in just one iteration. The developed scheme offers a significant advantage over its alternatives, with an average NPCR of 99.6122, UACI of 33.4690, and information entropy of 7.9993 for 14 test images, with an average correlation value as low as 0.0006 and a vast key space of 2800. The evaluation results demonstrated that the proposed approach is a viable and effective alternative for lightweight image encryption. Full article
(This article belongs to the Section Complexity)
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22 pages, 9693 KiB  
Article
A Trusted Supervision Paradigm for Autonomous Driving Based on Multimodal Data Authentication
by Tianyi Shi, Ruixiao Wu, Chuantian Zhou, Siyang Zheng, Zhu Meng, Zhe Cui, Jin Huang, Changrui Ren and Zhicheng Zhao
Big Data Cogn. Comput. 2024, 8(9), 100; https://doi.org/10.3390/bdcc8090100 - 2 Sep 2024
Viewed by 1750
Abstract
At the current stage of autonomous driving, monitoring the behavior of safety stewards (drivers) is crucial to establishing liability in the event of an accident. However, there is currently no method for the quantitative assessment of safety steward behavior that is trusted by [...] Read more.
At the current stage of autonomous driving, monitoring the behavior of safety stewards (drivers) is crucial to establishing liability in the event of an accident. However, there is currently no method for the quantitative assessment of safety steward behavior that is trusted by multiple stakeholders. In recent years, deep-learning-based methods can automatically detect abnormal behaviors with surveillance video, and blockchain as a decentralized and tamper-resistant distributed ledger technology is very suitable as a tool for providing evidence when determining liability. In this paper, a trusted supervision paradigm for autonomous driving (TSPAD) based on multimodal data authentication is proposed. Specifically, this paradigm consists of a deep learning model for driving abnormal behavior detection based on key frames adaptive selection and a blockchain system for multimodal data on-chaining and certificate storage. First, the deep-learning-based detection model enables the quantification of abnormal driving behavior and the selection of key frames. Second, the key frame selection and image compression coding balance the trade-off between the amount of information and efficiency in multiparty data sharing. Third, the blockchain-based data encryption sharing strategy ensures supervision and mutual trust among the regulatory authority, the logistic platform, and the enterprise in the driving process. Full article
(This article belongs to the Special Issue Big Data Analytics and Edge Computing: Recent Trends and Future)
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15 pages, 8609 KiB  
Article
Performance Evaluation of Lightweight Stream Ciphers for Real-Time Video Feed Encryption on ARM Processor
by Mohsin Khan, Håvard Dagenborg and Dag Johansen
Future Internet 2024, 16(8), 261; https://doi.org/10.3390/fi16080261 - 25 Jul 2024
Viewed by 1604
Abstract
In resource-intensive Internet of Things applications, Lightweight Stream Ciphers (LWSCs) play a vital role in influencing both the security and performance of the system. Numerous LWSCs have been proposed, each offering certain properties and trade-offs that carefully balance security and performance requirements. This [...] Read more.
In resource-intensive Internet of Things applications, Lightweight Stream Ciphers (LWSCs) play a vital role in influencing both the security and performance of the system. Numerous LWSCs have been proposed, each offering certain properties and trade-offs that carefully balance security and performance requirements. This paper presents a comprehensive evaluation of prominent LWSCs, with a focus on their performance and resource consumption, providing insights into efficiency, efficacy, and suitability in the real-world application of resource-intensive live video feed encryption on an ARM processor. The study involves the development of a benchmarking tool designed to evaluate key metrics, including encryption frame rate, throughput, processing cycles, memory footprint, ROM utilization, and energy consumption. In addition, we apply the E−Rank metric, which combines key performance and resource metrics to derive a unified comparative measure for overall software performance. Full article
(This article belongs to the Special Issue Cyber Security in the New "Edge Computing + IoT" World)
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