Computer Communications最新文献

{"title":"5GMap: Enabling external audits of access security and attach procedures in real-world cellular deployments","authors":"Andrea Paci ,&nbsp;Matteo Chiacchia ,&nbsp;Giuseppe Bianchi","doi":"10.1016/j.comcom.2025.108091","DOIUrl":"10.1016/j.comcom.2025.108091","url":null,"abstract":"<div><div>In cellular networks, security vulnerabilities often arise from misconfigurations and improper implementations of protection mechanisms. Typically, ensuring proper security configurations is the responsibility of network operators. The tool described in this paper, called 5GMap, empowers legitimate subscribers, equipped with software-defined radios (Ettus B210 or X310), with innovative means and methodologies for auditing security configurations of the access networks they are connecting to. Specifically, 5GMap allows to evaluate negotiable ciphers, predictability of temporary identifiers (TMSI), resilience against disclosure of privacy-sensitive identifiers (IMSI, IMEI), and susceptibility to downgrade attacks. 5GMap achieves this by iterating access and attach primitives using either carefully crafted signaling messages requiring specific cryptographic configuration, as well as custom methodologies such as using predictable TMSIs and querying the network with non-standard signaling message sequences to detect potential departures from the expected protocol specification. Extensive testing over four mobile network operators and three virtual network operators reveals significant security and privacy issues: many networks allow unencrypted or even unauthenticated communication, TMSI randomness and IMSI concealment are not consistently ensured across all operators tested, and many other fine-grained concerns emerge among different operators. We believe that our findings highlight the usefulness of tools like 5GMap to assess (and ultimately improve, through responsible disclosure) the security posture of 4G and 5G cellular networks in the wild.</div></div>","PeriodicalId":55224,"journal":{"name":"Computer Communications","volume":"234 ","pages":"Article 108091"},"PeriodicalIF":4.5,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143394626","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficient post-quantum attribute-based access control scheme for blockchain-empowered metaverse data management","authors":"Yuxuan Pan ,&nbsp;Rui Jin ,&nbsp;Yu Liu ,&nbsp;Lin Zhang","doi":"10.1016/j.comcom.2025.108092","DOIUrl":"10.1016/j.comcom.2025.108092","url":null,"abstract":"<div><div>Driven by recent advances in mobile networks and distributed computing, the Metaverse provides photorealistic services where humans can experience different virtual landscapes through avatars derived from abundant personal user data. To address significant concerns about privacy breaches in private digital assets, access control based on cryptography systems has become the focus of common research. However, existing designs have scalability and efficiency issues, appealing to more investigation in real-world implementation. In response to this security challenge using the prevalent cryptography tool, this paper proposes an Attribute-Based Access Control mechanism for Metaverse Data management (ABAC-MD). It provides a flexible and secure data-sharing framework that integrates the ciphertext-policy attribute-based encryption scheme with the polynomial function technique on lattice. Reliable outsourcing decryption based on blockchain facilitates efficient data processing by employing an attribute-associated access tree. It exploits a pragmatic solution to guarantee fine-grained data privacy control and fortify resilience against quantum attacks. Simulated experiment with relevant schemes based on custom-made avatars proves that the proposed scheme reduces ciphertext size by 43.6% and improve efficiency by at least 25.4%. With higher security, lower storage costs, and reduced computational complexity, the ABAC-MD is more practical for privacy preservation in Metaverse services.</div></div>","PeriodicalId":55224,"journal":{"name":"Computer Communications","volume":"234 ","pages":"Article 108092"},"PeriodicalIF":4.5,"publicationDate":"2025-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143394631","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modeling and predicting starlink throughput with fine-grained burst characterization","authors":"Johan Garcia ,&nbsp;Matthias Beckerle ,&nbsp;Simon Sundberg ,&nbsp;Anna Brunstrom","doi":"10.1016/j.comcom.2025.108090","DOIUrl":"10.1016/j.comcom.2025.108090","url":null,"abstract":"<div><div>Leveraging a dataset of almost half a billion packets with high-precision packet times and sizes, we extract characteristics of the bursts emitted over Starlink’s Ethernet interface. The structure of these bursts directly reflects the physical layer reception of OFDMA frames on the satellite link. We study these bursts by analyzing their rates, and thus indirectly also the transition between different physical layer rates. The results highlight that there is definitive structure in the transition behavior, and we note specific behaviors such as particular transition steps associated with rate switching, and that rate switching occurs mainly to neighboring rates. We also study the joint burst rate and burst duration transitions, noting that transitions occur mainly within the same rate, and that changes in burst duration are often performed with an intermediate short burst in-between. Furthermore, we examine the configurations of the three factors burst rate, burst duration, and inter-burst silent time, which together determine the effective throughput of a Starlink connection. We perform pattern mining on these three factors, and we use the patterns to construct a dynamic N-gram model predicting the characteristics of the next upcoming burst, and by extension, the short-term future throughput. We further train a Deep Learning time-series model which shows improved prediction performance.</div></div>","PeriodicalId":55224,"journal":{"name":"Computer Communications","volume":"234 ","pages":"Article 108090"},"PeriodicalIF":4.5,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143402442","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An anomaly-based approach for cyber–physical threat detection using network and sensor data","authors":"Roberto Canonico,&nbsp;Giovanni Esposito,&nbsp;Annalisa Navarro,&nbsp;Simon Pietro Romano,&nbsp;Giancarlo Sperlí,&nbsp;Andrea Vignali","doi":"10.1016/j.comcom.2025.108087","DOIUrl":"10.1016/j.comcom.2025.108087","url":null,"abstract":"<div><div>Integrating physical and cyber realms, Cyber–Physical Systems (CPSs) expand the potential attack surface for intruders. Given their deployment in critical infrastructures like Industrial Control Systems (ICSs), ensuring robust security is imperative. Current research has developed various Intrusion Detection techniques to identify and counter malicious activities. However, traditional methods often encounter challenges in detecting several attack types due to reliance on a single data source such as time series data from sensors and actuators. In this study, we meticulously design advanced Deep Learning (DL) anomaly-based techniques trained on either sensor/actuator data or network traffic statistics in an unsupervised setting. We evaluate these techniques on network and physical data collected concurrently from a real-world CPS. Through meticulous hyperparameter tuning, we identify the optimal parameters for each model and compare their efficiency and effectiveness in detecting different types of attacks. In addition to demonstrating superior performance compared to various baselines, we showcase the best model for each data source. Eventually, we show how utilizing diverse data sources can enhance cyber-threat detection, recognizing different kinds of attacks.</div></div>","PeriodicalId":55224,"journal":{"name":"Computer Communications","volume":"234 ","pages":"Article 108087"},"PeriodicalIF":4.5,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143387701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A deep reinforcement learning-based UAV-smallcell system for mobile terminals geolocalization in disaster scenarios","authors":"Roberta Avanzato,&nbsp;Francesco Beritelli,&nbsp;Raoul Raftopoulos,&nbsp;Giovanni Schembra","doi":"10.1016/j.comcom.2025.108088","DOIUrl":"10.1016/j.comcom.2025.108088","url":null,"abstract":"<div><div>Deep reinforcement learning (DRL) techniques have the potential to significantly improve the ability of Unmanned Aerial Vehicles (UAVs) for mobile device localization in disaster scenarios by optimizing flight paths and enhancing signal detection accuracy using Reference Signal Received Power (RSRP) measurements. DRL allows UAVs to learn optimal navigation strategies autonomously in dynamic and complex environments, leading to more efficient and accurate localization of mobile devices. The integration between UAVs and 4G/5G technology allows for more accurate and timely localization of mobile devices under the rubble, thereby improving the overall effectiveness of the system. Smallcells, low-power cellular base stations, are used to enhance coverage and capacity. In this study, we propose a DRL-based UAV-Smallcell system that can quickly and efficiently localize devices in large disaster areas. The performance of the proposed system is evaluated through an extensive simulation campaign to demonstrate that our approach significantly improves the effectiveness of mobile device localization compared to other state-of-the-art approaches.</div></div>","PeriodicalId":55224,"journal":{"name":"Computer Communications","volume":"234 ","pages":"Article 108088"},"PeriodicalIF":4.5,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143387595","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Heterogeneous multi-agent deep reinforcement learning based low carbon emission task offloading in mobile edge computing","authors":"Xiongjie Zhou ,&nbsp;Xin Guan ,&nbsp;Di Sun ,&nbsp;Xiaoguang Zhang ,&nbsp;Zhaogong Zhang ,&nbsp;Tomoaki Ohtsuki","doi":"10.1016/j.comcom.2025.108089","DOIUrl":"10.1016/j.comcom.2025.108089","url":null,"abstract":"<div><div>Mobile edge computing is an emerging computing paradigm in the Internet of Things. Task offloading is a critical method in mobile edge computing to alleviate computational resource constraints. Nowadays, the rising number of tasks is placing greater demands on computing resources. The increasing consumption of computing resources leads to high carbon emission. Achieving environmentally friendly mobile edge computing while effectively managing low-carbon task offloading poses a significant challenge. Recently, deep reinforcement learning has made certain progress in many research fields. However, there are few deep reinforcement learning methods that consider the carbon emission in task offloading. In this paper, we propose a deep reinforcement learning based low carbon emission task offloading algorithm for minimizing carbon emission in mobile edge computing. Firstly, since different base stations exist in the mobile edge computing environment, we consider the mobile edge computing environment with multiple heterogeneous agents. Secondly, to minimize carbon emission, we consider the carbon intensity of the base station as an optimization factor. We conclude the task offloading strategy to minimize carbon emission, consequently achieving the minimization of carbon emission. Moreover, our proposed algorithm allows user devices to decide their own preference for task offloading. Based on the specific requirements and preferences of user devices, our proposed algorithm can dynamically adjust the weights of delay, energy consumption, and carbon emission, respectively. Experiments indicate that the proposed algorithm can accurately and quickly conclude the task offloading strategy to minimize carbon emission.</div></div>","PeriodicalId":55224,"journal":{"name":"Computer Communications","volume":"234 ","pages":"Article 108089"},"PeriodicalIF":4.5,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143350874","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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":"Prioritization of smart meters based on data monitoring for enhanced grid resilience","authors":"Asma Farooq ,&nbsp;Kamal Shahid ,&nbsp;Rasmus Løvenstein Olsen","doi":"10.1016/j.comcom.2025.108082","DOIUrl":"10.1016/j.comcom.2025.108082","url":null,"abstract":"<div><div>Smart meters (SM) generate critical data that provides real-time insights into energy consumption, grid performance, and load management, which are essential for improving grid reliability, energy efficiency, and renewable energy integration. However, achieving effective communication between smart meters and the control center remains a challenge due to limitations in Advanced Metering Infrastructure (AMI), including communication delays, metering technology constraints, and restricted data storage and processing capabilities. These limitations hinder the precision and timeliness of real-time data delivery, negatively impacting the efficiency of energy management and grid operations. While existing research predominantly focuses on optimizing communication network algorithms, the critical issue of comprehensive SM data scheduling has received limited attention. Moreover, current methods often fail to account for the complexity of communication networks and the dynamic nature of information flow. To address this gap, this paper introduces a novel method for scheduling SM data access by leveraging real-time data assessment and analysis. A quality metric termed mismatch probability evaluates data quality, and the Hungarian algorithm is employed to optimize meter scheduling. The proposed method is validated using real-world data from a Danish grid, demonstrating significant improvements in information quality for real-time monitoring compared to heuristic-based scheduling approaches.</div></div>","PeriodicalId":55224,"journal":{"name":"Computer Communications","volume":"234 ","pages":"Article 108082"},"PeriodicalIF":4.5,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143349673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 multi-objective task allocation scheme with privacy-preserving and regional heat in mobile crowdsensing","authors":"Yanming Fu ,&nbsp;Jiayuan Chen ,&nbsp;Haodong Lu ,&nbsp;Bocheng Huang ,&nbsp;Weigeng Han","doi":"10.1016/j.comcom.2025.108085","DOIUrl":"10.1016/j.comcom.2025.108085","url":null,"abstract":"<div><div>In Mobile Crowdsensing, platforms typically require all users to upload their location information during the user recruitment phase, then select a subset of users to perform tasks based on location and reputation. However, this approach results in users who upload their location information but do not participate in tasks essentially providing their location data without compensation, posing a risk of location data leakage. If users repeatedly upload location information without receiving compensation for tasks, they may lose confidence in the platform and consequently leave it. Therefore, this paper proposes a multi-objective task allocation scheme based on differential privacy and regional heat, named MTADPRH. During the user recruitment phase, the MTADPRH scheme uses the Optimized Unary Encoding (OUE) mechanism to statistically analyze the distribution of all users, providing privacy protection that meets local differential privacy. In the location upload phase, the scheme adds planar Laplace noise to the location coordinates of participating users to achieve geo-indistinguishability. During the task allocation phase, MTADPRH employs the multi-objective evolutionary algorithm C3M to find Pareto optimal solutions, aiming to maximize the reward per unit distance for users and the revenue for the platform. The experimental results show that, with privacy protect, the MTADPRH scheme achieves the best results in terms of platform revenue, task completion rate, and per-unit distance compensation for users, and it provides a superior Pareto solution.</div></div>","PeriodicalId":55224,"journal":{"name":"Computer Communications","volume":"234 ","pages":"Article 108085"},"PeriodicalIF":4.5,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143341154","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 review on machine learning based user-centric multimedia streaming techniques","authors":"Monalisa Ghosh ,&nbsp;Chetna Singhal","doi":"10.1016/j.comcom.2024.108011","DOIUrl":"10.1016/j.comcom.2024.108011","url":null,"abstract":"<div><div>The multimedia content and streaming are a major means of information exchange in the modern era and there is an increasing demand for such services. This coupled with the advancement of future wireless networks B5G/6G and the proliferation of intelligent handheld mobile devices, has facilitated the availability of multimedia content to heterogeneous mobile users. Apart from the conventional video, the 360<span><math><mo>°</mo></math></span> videos have gained significant attention and are quickly emerging as the popular multimedia format for virtual reality experiences. All formats of videos (conventional and 360<span><math><mo>°</mo></math></span>) undergo processing, compression, and transmission across dynamic wireless channels with restricted bandwidth to facilitate the streaming services. This causes video impairments, leading to quality degradation and poses challenges for the content providers in delivering good Quality-of-Experience (QoE) to the viewers. The QoE is a prominent subjective measure of quality, which has become a crucial component in assessing multimedia services and operations. So, there has been a growing preference for QoE-aware multimedia services over heterogeneous networks with a need to address design issues like how to evaluate and quantify end-to-end QoE. Efficient multimedia streaming techniques can improve the service quality while dealing with dynamic network and end-user challenges. A paradigm shift in user-centric multimedia services is envisioned with a focus on Machine Learning (ML) based QoE modeling and streaming strategies. This survey paper presents a comprehensive overview of the overall and continuous, time varying QoE modeling for the purpose of QoE management in multimedia services. It also examines the recent research on intelligent and adaptive multimedia streaming strategies, with a special emphasis on ML based techniques for video (conventional and 360<span><math><mo>°</mo></math></span>) streaming. This paper discusses the overall and continuous QoE modeling to optimize the end-user viewing experience, efficient video streaming with a focus on user-centric strategies, associated datasets for modeling and streaming, along with existing shortcoming and open challenges.</div></div>","PeriodicalId":55224,"journal":{"name":"Computer Communications","volume":"231 ","pages":"Article 108011"},"PeriodicalIF":4.5,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143100393","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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":"DCP and VarDis: An ad-hoc protocol stack for dynamic swarms and formations of drones","authors":"Samuel Pell,&nbsp;Andreas Willig","doi":"10.1016/j.comcom.2024.108021","DOIUrl":"10.1016/j.comcom.2024.108021","url":null,"abstract":"<div><div>Recently, swarms or formations of drones have received increased interest both in the literature and in applications. To dynamically adapt to their operating environment, swarm members need to communicate wirelessly for control and coordination tasks. One fundamental communication pattern required for basic safety purposes, such as collision avoidance, is beaconing, where drones frequently transmit information about their position, speed, heading, and other operational data to a local neighbourhood, using a local broadcast service. In this paper, we propose and analyse a protocol stack which allows to use the recurring-beaconing primitive for additional purposes. In particular, we propose the VarDis (Variable Dissemination) protocol, which creates the abstraction of variables to which all members of a drone swarm have (read) access, and which can naturally be used for centralized control of a swarm, amongst other applications. We describe the involved protocols and provide a performance analysis of VarDis.</div></div>","PeriodicalId":55224,"journal":{"name":"Computer Communications","volume":"231 ","pages":"Article 108021"},"PeriodicalIF":4.5,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143100396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}