Vehicular Communications最新文献

{"title":"An adaptive and multi-path greedy perimeter stateless routing protocol in flying ad hoc networks","authors":"Amir Masoud Rahmani ,&nbsp;Dildar Hussain ,&nbsp;Reem Jafar Ismail ,&nbsp;Faisal Alanazi ,&nbsp;Salem Belhaj ,&nbsp;Mohammad Sadegh Yousefpoor ,&nbsp;Efat Yousefpoor ,&nbsp;Aso Darwesh ,&nbsp;Mehdi Hosseinzadeh","doi":"10.1016/j.vehcom.2024.100838","DOIUrl":"10.1016/j.vehcom.2024.100838","url":null,"abstract":"<div><p>In recent years, flying ad hoc networks (FANET), formed from unmanned aerial vehicles (UAVs), have absorbed the attention of academic and industrial research communities due to their many applications in military and civilian fields. FANETs benefit from unique features, including highly moving UAVs and dynamic topological structure. Therefore, most existing routing protocols, such as the greedy perimeter stateless routing (GPSR), are not compatible with the FANET environment and its specific features. To improve the performance of GPSR in FANET, it is important to address several challenges, namely the selection of the right period for broadcasting hello messages in the network, the selection of the right criteria for selecting the next-hop node, and the improvement of reliability in the data transfer process. In this paper, an adaptive and multi-path greedy perimeter stateless routing (AM-GPSR) protocol is suggested in FANETs. It includes two new strategies, namely adaptive hello strategy and multi-path greedy forwarding strategy. The adaptive hello strategy defines a special hello broadcast period for each UAV according to its speed and error between two estimated and actual positions. Furthermore, the greedy forwarding strategy carries out a filtering operation on candidate nodes and eliminates border UAVs and those that are far from the destination. Then, candidate UAVs are prioritized based on the time to reach the destination and buffer capacity, and UAVs with higher priorities are chosen to send data packets. Finally, AM-GPSR applies a greedy multi-path forwarding strategy to increase reliability in the data transmission process. Lastly, the simulation of AM-GPSR is done via the network simulator version 2 (NS2) to evaluate its performance. This evaluation process includes two different scenarios, i.e. change in the speed of UAVs and change in their communication range. In this process, AM-GPSR is compared with three other methods, namely the aerial greedy geographic routing (AGGR) protocol, the geolocation assisted aeronautical routing protocol (AeroRP), and GPSR. This comparison shows the successful performance of AM-GPSR in terms of delivery success rate, throughput, and delay. Although the control overhead of the proposed method is more than that of AGGR.</p></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":null,"pages":null},"PeriodicalIF":5.8,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142172988","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"Security situation assessment in UAV swarm networks using TransReSE: A Transformer-ResNeXt-SE based approach","authors":"Dongmei Zhao ,&nbsp;Pengcheng Shen ,&nbsp;Xunzhen Han ,&nbsp;Shuiguang Zeng","doi":"10.1016/j.vehcom.2024.100842","DOIUrl":"10.1016/j.vehcom.2024.100842","url":null,"abstract":"<div><p>With the rapid development and extensive application of unmanned aerial vehicles (UAVs), the issue of UAV swarm network security has become prominent. To protect the security of UAV swarm networks, effective network security defense measures are crucial. One key aspect is the assessment and monitoring of the network's security situation. However, most existing research focuses on the security of individual UAVs or detecting specific attacks, which fails to provide proactive protection for the network. To address this issue, we propose a UAV swarm network security situation assessment method, which combines the Transformer network with the optimization of the Aggregated Residual Transformations for Deep Neural Networks (ResNeXt) and squeeze-and-excitation (SE) structure (named TransReSE). By using multiple scale-cross convolution kernels, TransReSE can efficiently extract data features and improve situation assessment accuracy through the Transformer network. Experimental results from four public datasets have shown that TransReSE outperforms other schemes in terms of accuracy, recall, and F1. By assessing the value of the swarm network situation and the threat level, we can make faster, more effective decisions and proactively allocate resources to defend against UAV swarm network attacks.</p></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":null,"pages":null},"PeriodicalIF":5.8,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142162622","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"LB-CLAS: Lattice-based conditional privacy-preserving certificateless aggregate signature scheme for VANET","authors":"Sheng-wei Xu ,&nbsp;Shu-han Yu ,&nbsp;Yi-Jie Bai ,&nbsp;Zi-Yan Yue ,&nbsp;Yi-Long Liu","doi":"10.1016/j.vehcom.2024.100843","DOIUrl":"10.1016/j.vehcom.2024.100843","url":null,"abstract":"<div><p>The rapid development of vehicular ad-hoc networks (VANETs) has brought great convenience to intelligent transportation, and the secure transmission of information in VANETs has become a serious problem. In addition, the protection of private information of vehicles is also a key issue. Aiming at the problem of how to guarantee the secure transmission of information in VANETs under the condition of satisfying security and privacy, we propose a lattice-based conditional privacy-preserving certificateless aggregate signature scheme (LB-CLAS) for VANETs. Instead of using Number Theory Research Unit (NTRU) lattices and discrete Gaussian sampling, the proposed LB-CLAS scheme is based on algebraic lattice. In addition, based on the module version of Small Integer Solution (MSIS) and module version of Learning With Error (MLWE) hard problems, we prove that the LB-CLAS scheme is existential unforgeability under adaptively chosen message attacks (EUF-CMA). Our LB-CLAS scheme employs individual signature verification in vehicle-to-vehicle (V2V) mode, while utilizing aggregate signatures and batch verification in vehicle-to-infrastructure (V2I) mode, with slightly differing transmission parameters between the two modes. Based on Dilithium, our LB-CLAS scheme solves the problem of high storage overhead and computational cost of existing schemes. The performance analysis shows that our LB-CLAS scheme is more efficient in terms of computation cost, storage overhead, and power consumption compared to existing schemes. Compared with existing schemes, our LB-CLAS scheme reduces the signature and verification overheads by more than 17.6% and 43.4%, respectively. Our LB-CLAS program also has significant advantages in batch verification. As the number of vehicles increases, our batch certification time cost is reduced by more than 90%. In addition, our LB-CLAS scheme has the smallest signature length, with a signature size that is 1X smaller than the most efficient existing scheme for the same level of security.</p></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":null,"pages":null},"PeriodicalIF":5.8,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2214209624001189/pdfft?md5=d16493d6df4ea967cee7aafc78f227fc&pid=1-s2.0-S2214209624001189-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142172987","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"URLLC-aware and energy-efficient data offloading strategy in high-mobility vehicular mobile edge computing environments","authors":"Hong Min ,&nbsp;Jawad Tanveer ,&nbsp;Amir Masoud Rahmani ,&nbsp;Abdullah Alqahtani ,&nbsp;Abed Alanazi ,&nbsp;Shtwai Alsubai ,&nbsp;Mehdi Hosseinzadeh","doi":"10.1016/j.vehcom.2024.100839","DOIUrl":"10.1016/j.vehcom.2024.100839","url":null,"abstract":"<div><p>The integration of Internet of Things (IoT) technologies into the vehicular industry has initiated a new era of connected and autonomous vehicles, revolutionizing transportation systems. However, this transformation introduces significant challenges, especially in 5 G networks, such as achieving Ultra-Reliable Low-Latency Communications (URLLC) and maintaining energy efficiency within the high mobility of vehicular environments. These are essential for supporting sustainable and environmentally friendly computing practices. To address these challenges, this paper introduces a URLLC-aware and energy-efficient data offloading strategy, utilizing the Asynchronous Advantage Actor-Critic (A3C) algorithm to navigate the complex dynamics of vehicular Mobile Edge Computing (MEC) environments. Our proposed method balances latency and energy consumption trade-offs while ensuring robust communication reliability. Technical evaluations reveal that our approach significantly outperforms other algorithms, achieving up to 8.2 % energy savings and a reduction of over 29 % in latency.</p></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":null,"pages":null},"PeriodicalIF":5.8,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142167873","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 robust multi-stage intrusion detection system for in-vehicle network security using hierarchical federated learning","authors":"Muzun Althunayyan ,&nbsp;Amir Javed ,&nbsp;Omer Rana","doi":"10.1016/j.vehcom.2024.100837","DOIUrl":"10.1016/j.vehcom.2024.100837","url":null,"abstract":"<div><p>As connected and autonomous vehicles proliferate, the Controller Area Network (CAN) bus has become the predominant communication standard for in-vehicle networks due to its speed and efficiency. However, the CAN bus lacks basic security measures such as authentication and encryption, making it highly vulnerable to cyberattacks. To ensure in-vehicle security, intrusion detection systems (IDSs) must detect seen attacks and provide a robust defense against new, unseen attacks while remaining lightweight for practical deployment. Previous work has relied solely on the CAN ID feature or has used traditional machine learning (ML) approaches with manual feature extraction. These approaches overlook other exploitable features, making it challenging to adapt to new unseen attack variants and compromising security. This paper introduces a cutting-edge, novel, lightweight, in-vehicle, IDS-leveraging, deep learning (DL) algorithm to address these limitations. The proposed IDS employs a multi-stage approach: an artificial neural network (ANN) in the first stage to detect seen attacks, and a Long Short-Term Memory (LSTM) autoencoder in the second stage to detect new, unseen attacks. To understand and analyze diverse driving behaviors, update the model with the latest attack patterns, and preserve data privacy, we propose a theoretical framework to deploy our IDS in a hierarchical federated learning (H-FL) environment. Experimental results demonstrate that our IDS achieves an F1-score exceeding 0.99 for seen attacks and exceeding 0.95 for novel attacks, with a detection rate of 99.99%. Additionally, the false alarm rate (FAR) is exceptionally low at 0.016%, minimizing false alarms. Despite using DL algorithms known for their effectiveness in identifying sophisticated and zero-day attacks, the IDS remains lightweight, ensuring its feasibility for real-world deployment. This makes our model robust against seen and unseen attacks.</p></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":null,"pages":null},"PeriodicalIF":5.8,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2214209624001128/pdfft?md5=5c13cb7ede7ac0fd94530908e6c0a393&pid=1-s2.0-S2214209624001128-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142122918","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 secure authentication framework for IoV based on blockchain and ensemble learning","authors":"Wenxian Jiang ,&nbsp;Xianglong Lv ,&nbsp;Jun Tao","doi":"10.1016/j.vehcom.2024.100836","DOIUrl":"10.1016/j.vehcom.2024.100836","url":null,"abstract":"<div><p>A secure authentication framework based on blockchain and ensemble learning is proposed to address the problem that vehicle identity privacy data in Internet of Vehicles (IoV) is vulnerable to theft and tampering. First, a secure and efficient authentication method based on blockchain and Physical Unclonable Function (PUF) is implemented, which ensures the identity privacy of the vehicle when accessing IoV, and improves the problem of high resource overhead of the traditional IoV authentication scheme while guaranteeing security, and the computational overhead is about 2.424 ms at the first level of security framework. Secondly, an intrusion detection method based on Whale Optimization Algorithm (WOA) and Extreme Gradient Boosting (XGBoost) is proposed, and the detection model trained based on this method can effectively detect various attacks against IoV. As a security method at the second level of secure framework, the method outperforms related works in detecting malicious attacks with a detection accuracy of 98.41% for ToN-IoT and 99.99% for BoT-IoT.</p></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":null,"pages":null},"PeriodicalIF":5.8,"publicationDate":"2024-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142128414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"Physical layer security in SWIPT-based cooperative vehicular relaying networks","authors":"Patrick Odong ,&nbsp;Ahmed H. Abd El-Malek ,&nbsp;Ahmed Allam ,&nbsp;Adel B. Abdel-Rahman","doi":"10.1016/j.vehcom.2024.100835","DOIUrl":"10.1016/j.vehcom.2024.100835","url":null,"abstract":"<div><p>The future of autonomous transportation systems depends on energy sustainability and secure information exchange from low-power vehicular sensors, hence the increased interest in vehicular sensor charging using simultaneous wireless information and power transfer (SWIPT). This study investigates the physical layer security of a SWIPT-based radio frequency energy harvesting cooperative vehicular relaying network subjected to cascade Nakagami-<em>m</em> and double Nakagami-<em>m</em> (DN) fading channels. In the considered system model, a stationary source communicates with a mobile destination through a power-splitting-based decode-and-forward relay in the presence of a mobile passive eavesdropper. Based on the Gamma-distributed first term of the Laguerre series, new statistical probability density function (PDF) and cumulative distribution function (CDF) expressions for the DN are derived to accurately model the complex cascaded fading scenario. The secrecy performance metrics analyzed are the secrecy outage probability (SOP), the probability of non-zero secrecy capacity (PNZSC), and the intercept probability (IP). In addition, the asymptotic SOP (ASOP) is investigated in the high signal-to-noise ratio (SNR) to enhance the comprehension of the secrecy performance. Based on the derived ASOP, the secrecy diversity order (SDO) of the proposed system is determined and examined. Particularly, we present analytical closed-form expressions for the secrecy performance metrics and provide a detailed understanding of the impact of the system parameters under the cascade fading scenario. Then, a power splitting (PS) optimization problem is formulated to minimize the SOP. The results demonstrate a reduction in the SOP with the proposed PS scheme compared to the equal PS scheme. The obtained analytical findings are validated using Monte Carlo simulations.</p></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":null,"pages":null},"PeriodicalIF":5.8,"publicationDate":"2024-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142021225","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"Assessing the impact of communication delays for Autonomous Intersection Management systems","authors":"Michael I.-C. Wang ,&nbsp;Charles H.-P. Wen ,&nbsp;H. Jonathan Chao","doi":"10.1016/j.vehcom.2024.100829","DOIUrl":"10.1016/j.vehcom.2024.100829","url":null,"abstract":"<div><p>Communication is essential for Cooperative Intelligent Transportation Systems (C-ITS) to achieve better road efficiency, especially for Autonomous Intersection Management (AIM) which coordinates vehicles to pass the intersection safely and efficiently. Communication delays cause severe safety crises (i.e., collisions) and vehicular-performance degradation regarding intersection capacities and vehicular delays. Targeting the delays, network researchers have been working on low-latency communication technologies, and C-ITS researchers have proposed delay-tolerant AIM systems to avoid collisions in intersections. The impacts of communication delays are observed and discussed in the literature; however, models and assessments of the delay requirements for AIM are needed to provide insights for future network and C-ITS research. Here, we model the impact of communication delays on vehicular performance at an autonomous intersection and validate the models with the simulation results from over two million experiments, two types of multi-lane intersections (a typical 4-legged intersection and a roundabout), and four AIM systems. The simulations are conducted with SUMO simulator and AIM systems, where communication delays are inserted into the message exchanges during the simulation. The models are represented in linear, quintic, and cubic polynomials, showing that communication delay between 0 to 100 milliseconds is linearly related to vehicular performance in terms of intersection capacity and vehicular delay. According to the models, we show that by reducing communication delay from 100 to 10 milliseconds, the capacity degradation can be reduced from 7-10% to 0.7-1.0%. Moreover, communication delays must be less than 247 milliseconds to allow AIM systems to outperform traditional traffic lights.</p></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":null,"pages":null},"PeriodicalIF":5.8,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141909457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"HCFAIUN: A novel hyperelliptic curve and fuzzy extractor-based authentication for secure data transmission in IoT-based UAV networks","authors":"Jatin Sharma,&nbsp;Pawan Singh Mehra","doi":"10.1016/j.vehcom.2024.100834","DOIUrl":"10.1016/j.vehcom.2024.100834","url":null,"abstract":"<div><p>IoT-based UAV networks comprise interconnected UAVs outfitted with sensors and microcontrollers to simplify data exchange in environments such as smart cities. In light of open-access communication landscapes, IoT-based UAV networks could pose security challenges, encompassing authentication vulnerabilities and the inadvertent disclosure of location and other confidential information to unauthorised parties. Henceforth, we have proposed a lightweight and secure authentication protocol: Hyperelliptic Curve and Fuzzy Extractor based Authentication in IoT-based UAV networks (HCFAIUN) leveraging Hyperelliptic Curve Cryptography(HCC), Fuzzy Extractor (FE), XOR operations and hash functions. HCC's maximum key size is 80 bits, differing from the 160-bit requirement of the elliptic curve, making it apt for UAVs with limited resources. The proposed scheme utilises biometrics traits of users to avoid exposing data from stealing smart devices using FE. This protocol facilitates the mutual authentication of users and UAVs, allowing them to exchange a session key for secure communication. The Hyperelliptic Curve (HC) scalar multiplication protects the user's private key from attackers, even in public channels. The obfuscation identity of the user and UAVs generated through the hash function and timestamp makes the external user and UAV anonymous. The efficacy of this proposed framework is examined using the Scyther verification tool and Random oracle model-based formal analysis, and informal analysis is also discussed, which validates its robustness against well-known potential physical and logical attacks. The performance analysis shows that the HCFAIUN scheme has lower computation, communication, and storage costs, i.e., 3.832 ms and 1456 bits and 1128 bits, respectively, compared to existing schemes.</p></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":null,"pages":null},"PeriodicalIF":5.8,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141846723","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"Evaluating energy harvesting UAV-NOMA network with random user pairing in the finite blocklength regime","authors":"Shardul Thapliyal,&nbsp;Rajoo Pandey,&nbsp;Chhagan Charan","doi":"10.1016/j.vehcom.2024.100831","DOIUrl":"10.1016/j.vehcom.2024.100831","url":null,"abstract":"<div><p>This study proposes an integrated system that combines energy harvesting (EH) enabled unmanned aerial vehicles (UAVs) with non-orthogonal multiple access (NOMA) to enhance communication system performance within a cellular network. Addressing the limitations of existing analyses that often assume an infinite blocklength scenario, we explore EH-enabled UAV-NOMA systems within a cellular framework under a finite blocklength (FBL) scenario. The study investigates the complex interactions and advantages resulting from the integration of EH, NOMA, and UAV technologies, aiming to assess whether EH can sustain communication within this framework. The network model considers base stations (BSs), UAVs, and terrestrial devices distributed with independent Poisson point processes (PPPs) over a large area. In this network, BSs employ NOMA to serve cell center devices directly, while cell edge devices, which are nor in direct contact with BS, are served via simultaneous wireless information and power transfer (SWIPT) enabled UAVs. The study derives metrics including joint harvesting and decoding probability for a randomly selected UAV, coverage probability (CP) for cell devices, and end-to-end block error rate (BLER) probabilities for typical device pairs. The findings demonstrate that the proposed scheme effectively supplies all the necessary transmit power for communication purposes through EH, achieving reasonable reliability. Additionally, the study highlights the importance of considering a combination of blocklengths from different phases to achieve optimal performance, rather than solely relying on an increment in blocklength. Finally, the effects of parameter variations on network performance are examined.</p></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":null,"pages":null},"PeriodicalIF":5.8,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141853674","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}