Pub Date : 2023-09-28DOI: 10.5121/jgraphoc.2023.15301
Basma Mohamed, Mohamed Amin
The complexity of a graph can be determined using a network-theoretic method, which is given. This strategy is based on the connection between graph theory and the theory of determinants in linear algebra. In this article, we provide a unique algebraic method that makes use of linear algebra to derive simple formulas for the complexity of diverse novel networks. We can derive the explicit formulas for the globe network and its subdivision using this method. In the final least, we also determine their spanning trees entropy and compare it to each other
{"title":"Enumeration of the Number of Spanning Trees of the Globe Network and its Subdivision","authors":"Basma Mohamed, Mohamed Amin","doi":"10.5121/jgraphoc.2023.15301","DOIUrl":"https://doi.org/10.5121/jgraphoc.2023.15301","url":null,"abstract":"The complexity of a graph can be determined using a network-theoretic method, which is given. This strategy is based on the connection between graph theory and the theory of determinants in linear algebra. In this article, we provide a unique algebraic method that makes use of linear algebra to derive simple formulas for the complexity of diverse novel networks. We can derive the explicit formulas for the globe network and its subdivision using this method. In the final least, we also determine their spanning trees entropy and compare it to each other","PeriodicalId":55557,"journal":{"name":"Ad Hoc & Sensor Wireless Networks","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135470322","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-27DOI: 10.5121/jgraphoc.2023.15201
Basma Mohamed, Mohamed Amin
In this paper, we consider the NP-hard problem of finding the minimum resolving set of graphs. A vertex set B of a connected graph G resolves G if every vertex of G is uniquely identified by its vector of distances to the vertices in B. The cardinality of the minimal resolving set is the metric dimension of G. The metric dimension appears in various fields such as network discovery and verification, robot navigation, combinatorial optimization and pharmaceutical chemistry, etc. In this study, we introduce a hybrid approach (WCA_WOA) for computing the metric dimension of graphs that combines the water cycle algorithm and a whale optimisation algorithm. The WOA algorithm hybridises the WCA in order to obtain the optimal result and manage the optimization process. The results of the experiments show that the WCA_WOA hybrid algorithm outperforms the WCA, WOA, and particle swarm optimization methods
{"title":"A HYBRID OPTIMIZATION ALGORITHMS FOR SOLVING METRIC DIMENSION PROBLEM","authors":"Basma Mohamed, Mohamed Amin","doi":"10.5121/jgraphoc.2023.15201","DOIUrl":"https://doi.org/10.5121/jgraphoc.2023.15201","url":null,"abstract":"In this paper, we consider the NP-hard problem of finding the minimum resolving set of graphs. A vertex set B of a connected graph G resolves G if every vertex of G is uniquely identified by its vector of distances to the vertices in B. The cardinality of the minimal resolving set is the metric dimension of G. The metric dimension appears in various fields such as network discovery and verification, robot navigation, combinatorial optimization and pharmaceutical chemistry, etc. In this study, we introduce a hybrid approach (WCA_WOA) for computing the metric dimension of graphs that combines the water cycle algorithm and a whale optimisation algorithm. The WOA algorithm hybridises the WCA in order to obtain the optimal result and manage the optimization process. The results of the experiments show that the WCA_WOA hybrid algorithm outperforms the WCA, WOA, and particle swarm optimization methods","PeriodicalId":55557,"journal":{"name":"Ad Hoc & Sensor Wireless Networks","volume":"10 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2023-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90157081","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The real-time traffic characteristics on the road network highly affect the safety conditions and the driving behaviors there. Early detection of crowded areas or hazardous conditions on the road network should affect the drivers' decisions and behavior to guarantee smooth and comfortable trips. Machine learning mechanisms have been mainly used for general prediction after extensive training processes. Over the road networks, trained machines could be really helpful to obtain instant predictions that assist drivers and autonomous vehicles there. However, the quality and efficiency of these machines are affected by several criteria including the quality of the used dataset and the tuning of the parameters of the regression algorithm. In this work, we investigate the performance of the most popular regression algorithms in terms of temporal prediction of the traffic characteristics in a real road scenario. Moreover, we optimize the regression algorithm by tuning the parameters using the grid search technique. From the experimental results, we can clearly notice the enhancements in predicting the traffic characteristics for different periods of time. We have observed that the number of neighbors, the distance, and the metric parameters' values are best tuned with the values of 4, 'Manhattan', and 'Distance', respectively, for the K-Nearest Neighbor (KNN) regression algorithm.
{"title":"Machine Learning Based Prediction with Parameters Tuning of Multi-Label Real Road Vehicles Characteristics","authors":"R. Qaddoura, Maram Bani Younes, A. Boukerche","doi":"10.1145/3551663.3558606","DOIUrl":"https://doi.org/10.1145/3551663.3558606","url":null,"abstract":"The real-time traffic characteristics on the road network highly affect the safety conditions and the driving behaviors there. Early detection of crowded areas or hazardous conditions on the road network should affect the drivers' decisions and behavior to guarantee smooth and comfortable trips. Machine learning mechanisms have been mainly used for general prediction after extensive training processes. Over the road networks, trained machines could be really helpful to obtain instant predictions that assist drivers and autonomous vehicles there. However, the quality and efficiency of these machines are affected by several criteria including the quality of the used dataset and the tuning of the parameters of the regression algorithm. In this work, we investigate the performance of the most popular regression algorithms in terms of temporal prediction of the traffic characteristics in a real road scenario. Moreover, we optimize the regression algorithm by tuning the parameters using the grid search technique. From the experimental results, we can clearly notice the enhancements in predicting the traffic characteristics for different periods of time. We have observed that the number of neighbors, the distance, and the metric parameters' values are best tuned with the values of 4, 'Manhattan', and 'Distance', respectively, for the K-Nearest Neighbor (KNN) regression algorithm.","PeriodicalId":55557,"journal":{"name":"Ad Hoc & Sensor Wireless Networks","volume":"2 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90545504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
J. M. Batalla, Sławomir Sujecki, Jacek Oko, J. Kelner
The Regulatory Authority monitors and regulates the telecom market at a national-wide range. One of its main tasks is to put spectrum at disposal of the Mobile Network Operators (MNO) for serving the increase number of users and services. For this scope, the Regulator needs to have an independent estimation of the usage of the radio resources by the operators, so that it may anticipate future needs and to initiate actions (e.g., liberation of frequency bands) directed to fulfill the demands of the market. This paper presents a methodology for Regulator-triggered monitoring of 5G radio resources allocation. The requirements of the methodology are: (1) monitoring measurements must be external to the network, (2) information from the MNO is limited to the data of the radio infrastructure, such as localization and technical data of the antennas, and (3) any measurements need to be cost-effective since it is supposed that the Regulator will make extended test campaigns through the whole national territory. Our results of 5G measurements validate the methodology and show the limitations of the estimation of radio resource allocation.
{"title":"Cost-effective Measurements of 5G Radio Resources Allocation for Telecom Market Regulator's Monitoring","authors":"J. M. Batalla, Sławomir Sujecki, Jacek Oko, J. Kelner","doi":"10.1145/3551663.3558684","DOIUrl":"https://doi.org/10.1145/3551663.3558684","url":null,"abstract":"The Regulatory Authority monitors and regulates the telecom market at a national-wide range. One of its main tasks is to put spectrum at disposal of the Mobile Network Operators (MNO) for serving the increase number of users and services. For this scope, the Regulator needs to have an independent estimation of the usage of the radio resources by the operators, so that it may anticipate future needs and to initiate actions (e.g., liberation of frequency bands) directed to fulfill the demands of the market. This paper presents a methodology for Regulator-triggered monitoring of 5G radio resources allocation. The requirements of the methodology are: (1) monitoring measurements must be external to the network, (2) information from the MNO is limited to the data of the radio infrastructure, such as localization and technical data of the antennas, and (3) any measurements need to be cost-effective since it is supposed that the Regulator will make extended test campaigns through the whole national territory. Our results of 5G measurements validate the methodology and show the limitations of the estimation of radio resource allocation.","PeriodicalId":55557,"journal":{"name":"Ad Hoc & Sensor Wireless Networks","volume":"28 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86667358","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pablo Andrés Barbecho Bautista, L. Urquiza-Aguiar, M. Aguilar-Igartua
This paper proposes a privacy-aware reinforcement learning (RL) framework to reduce carbon emissions of vehicles approaching light traffic intersections. Taking advantage of vehicular communications, traffic lights disseminate their state (i.e., traffic light cycle) among vehicles in their proximity. Then, the RL model is trained using public traffic lights data while preserving private car information locally (i.e., at the vehicle premises). Vehicles act as the agents of the model, and traffic infrastructure serves as the environment where the agent lives. Each time, the RL model decides if the vehicle should accelerate or decelerate (i.e., the model action) based on received traffic light observations. The optimal RL model strategy, dictating vehicles' driving speed, is learned following the proximal policy optimization algorithm. Results show that by moderating vehicles' speed when approximating traffic light intersections, gas emissions are reduced by 25% CO2 and 38% NOx emissions. The same happens for EVs that reduce energy consumption by 20W/h compared to not using the model. at intersections. The final impact of using the model refers to a negligible increment of 20s in the trip duration.
{"title":"Privacy-Aware Vehicle Emissions Control System for Traffic Light Intersections","authors":"Pablo Andrés Barbecho Bautista, L. Urquiza-Aguiar, M. Aguilar-Igartua","doi":"10.1145/3551663.3558686","DOIUrl":"https://doi.org/10.1145/3551663.3558686","url":null,"abstract":"This paper proposes a privacy-aware reinforcement learning (RL) framework to reduce carbon emissions of vehicles approaching light traffic intersections. Taking advantage of vehicular communications, traffic lights disseminate their state (i.e., traffic light cycle) among vehicles in their proximity. Then, the RL model is trained using public traffic lights data while preserving private car information locally (i.e., at the vehicle premises). Vehicles act as the agents of the model, and traffic infrastructure serves as the environment where the agent lives. Each time, the RL model decides if the vehicle should accelerate or decelerate (i.e., the model action) based on received traffic light observations. The optimal RL model strategy, dictating vehicles' driving speed, is learned following the proximal policy optimization algorithm. Results show that by moderating vehicles' speed when approximating traffic light intersections, gas emissions are reduced by 25% CO2 and 38% NOx emissions. The same happens for EVs that reduce energy consumption by 20W/h compared to not using the model. at intersections. The final impact of using the model refers to a negligible increment of 20s in the trip duration.","PeriodicalId":55557,"journal":{"name":"Ad Hoc & Sensor Wireless Networks","volume":"7 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81691584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Carlos Lester Dueñas Santos, J. León, A. M. Mezher, J. Cardenas-Barrera, J. Meng, Eduardo Castillo Guerra
Routing protocols play an important role in a Wireless Smart Grid Network (WSGN). The implementation of efficient routing strategies becomes paramount to guarantee the necessary interaction between utilities smart devices like smart meters, and the control centers. This research is focused on improving one of the well known routing protocols for WSGN, the Routing Protocol for Low-Power and Lossy Networks (RPL). More specifically, this paper presents a new parent selection strategy designed to choose the best parent when two or more candidates have the same ranking. The goal is to make better forwarding decisions on the best next-hop node to transmit packets to the destination. The proposed method takes into account the most important routing metrics in this type of network determined by applying Machine Learning (ML) feature importance analysis using Random Forest. The performance evaluation of the proposed strategy shows a significant improvement in terms of Packet Delivery Ratio when comparing to RPL standard implementations.
{"title":"RPL+: An Improved Parent Selection Strategy for RPL in Wireless Smart Grid Networks","authors":"Carlos Lester Dueñas Santos, J. León, A. M. Mezher, J. Cardenas-Barrera, J. Meng, Eduardo Castillo Guerra","doi":"10.1145/3551663.3558677","DOIUrl":"https://doi.org/10.1145/3551663.3558677","url":null,"abstract":"Routing protocols play an important role in a Wireless Smart Grid Network (WSGN). The implementation of efficient routing strategies becomes paramount to guarantee the necessary interaction between utilities smart devices like smart meters, and the control centers. This research is focused on improving one of the well known routing protocols for WSGN, the Routing Protocol for Low-Power and Lossy Networks (RPL). More specifically, this paper presents a new parent selection strategy designed to choose the best parent when two or more candidates have the same ranking. The goal is to make better forwarding decisions on the best next-hop node to transmit packets to the destination. The proposed method takes into account the most important routing metrics in this type of network determined by applying Machine Learning (ML) feature importance analysis using Random Forest. The performance evaluation of the proposed strategy shows a significant improvement in terms of Packet Delivery Ratio when comparing to RPL standard implementations.","PeriodicalId":55557,"journal":{"name":"Ad Hoc & Sensor Wireless Networks","volume":"25 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78660039","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Marta Moure-Garrido, Celeste Campo, C. García-Rubio
DNS plays a fundamental role in the operation of ubiquitous networks. All devices connected to these networks need DNS to work, both for traditional domain name to IP address translation, and for more advanced services such as resource discovery. At first, the DNS communication protocol presented certain security problems: integrity, authenticity and confidentiality. DNSSEC provides security but still does not guarantee confidentiality. To solve this problem, DNS over TLS (DoT) and DNS over HTTPS (DoH) were defined. In recent years, DNS tunneling, a covert form of encapsulating data transmission, has been used to encapsulate malicious traffic in a DNS connection. DoT and DoH versions complicate the detection of these tunnels because the encrypted data prevents performing an analysis of the content of the DNS traffic. Previous work has used machine learning techniques to identify DoH tunnels, but these have limitations. In this study, we identify the most significant features that singularize malicious traffic from benign traffic by statistical analysis. Based on the selected features, we obtain satisfactory results in the classification between benign and malicious DoH traffic. The study reveals that it is possible to differentiate traffic based on certain statistical parameters.
DNS在泛在网络的运行中起着基础性的作用。所有连接到这些网络的设备都需要DNS工作，无论是传统的域名到IP地址的转换，还是更高级的服务，如资源发现。首先，DNS通信协议存在一定的安全性问题:完整性、真实性和保密性。DNSSEC提供了安全性，但仍然不能保证机密性。为了解决这个问题，定义了DNS over TLS (DoT)和DNS over HTTPS (DoH)。近年来，DNS隧道作为一种隐蔽的数据传输封装形式，被用于在DNS连接中封装恶意流量。DoT和DoH版本使这些隧道的检测变得复杂，因为加密的数据阻止对DNS流量的内容进行分析。以前的工作使用机器学习技术来识别DoH隧道，但这些技术有局限性。在本研究中，我们通过统计分析确定了将恶意流量与良性流量区分开来的最重要特征。根据选取的特征，对良性和恶意DoH流量进行分类，得到了满意的结果。研究表明，基于一定的统计参数区分流量是可能的。
{"title":"Detecting Malicious Use of DoH Tunnels Using Statistical Traffic Analysis","authors":"Marta Moure-Garrido, Celeste Campo, C. García-Rubio","doi":"10.1145/3551663.3558605","DOIUrl":"https://doi.org/10.1145/3551663.3558605","url":null,"abstract":"DNS plays a fundamental role in the operation of ubiquitous networks. All devices connected to these networks need DNS to work, both for traditional domain name to IP address translation, and for more advanced services such as resource discovery. At first, the DNS communication protocol presented certain security problems: integrity, authenticity and confidentiality. DNSSEC provides security but still does not guarantee confidentiality. To solve this problem, DNS over TLS (DoT) and DNS over HTTPS (DoH) were defined. In recent years, DNS tunneling, a covert form of encapsulating data transmission, has been used to encapsulate malicious traffic in a DNS connection. DoT and DoH versions complicate the detection of these tunnels because the encrypted data prevents performing an analysis of the content of the DNS traffic. Previous work has used machine learning techniques to identify DoH tunnels, but these have limitations. In this study, we identify the most significant features that singularize malicious traffic from benign traffic by statistical analysis. Based on the selected features, we obtain satisfactory results in the classification between benign and malicious DoH traffic. The study reveals that it is possible to differentiate traffic based on certain statistical parameters.","PeriodicalId":55557,"journal":{"name":"Ad Hoc & Sensor Wireless Networks","volume":"104 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75992092","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The work presented in this paper focuses on the implementation of a testbed for the evaluation of content distribution systems using LL-DASH (Low Latency DASH -Dynamic Adaptive Streaming over HTTP-) and devices that provide real-time sources or servers using real-time protocols, such as RTSP (Real Time Streaming Protocol) or SRT (Secure Reliable Transport). These protocols are widely used by IP (Internet Protocol) cameras or by production and transmission systems, such as OBS Studio or vMix. The objective is to show the necessary processes in detail (so they can be reproduced in future works related to low latency services) and to minimize the end-to-end delay, obtaining values in the order of 2 seconds or less. The implementation has been done using FFmpeg software, players like Dash.js or Shaka-Player and implementing a Python web server with LL-DASH support to optimize the transmission delay.
{"title":"Performance Evaluation and Testbed for Delivering SRT Live Content using DASH Low Latency Streaming Systems","authors":"R. Belda, P. Arce, I. D. Fez, J. C. Guerri","doi":"10.1145/3551663.3558674","DOIUrl":"https://doi.org/10.1145/3551663.3558674","url":null,"abstract":"The work presented in this paper focuses on the implementation of a testbed for the evaluation of content distribution systems using LL-DASH (Low Latency DASH -Dynamic Adaptive Streaming over HTTP-) and devices that provide real-time sources or servers using real-time protocols, such as RTSP (Real Time Streaming Protocol) or SRT (Secure Reliable Transport). These protocols are widely used by IP (Internet Protocol) cameras or by production and transmission systems, such as OBS Studio or vMix. The objective is to show the necessary processes in detail (so they can be reproduced in future works related to low latency services) and to minimize the end-to-end delay, obtaining values in the order of 2 seconds or less. The implementation has been done using FFmpeg software, players like Dash.js or Shaka-Player and implementing a Python web server with LL-DASH support to optimize the transmission delay.","PeriodicalId":55557,"journal":{"name":"Ad Hoc & Sensor Wireless Networks","volume":"74 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79609528","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Long-range wireless technologies are at the core of Internet of Things (IoT) and smart city applications. While they offer many advantages in terms of ease of deployment, flexibility, mobility, and ubiquity, to name but a few, they are not equally suitable for smart city applications. Since 'one size fits all' does not hold in this context, finding out which long-range wireless technology is the best requires a thorough performance evaluation of these technologies in specific context and scenarios. In this paper, we focus on performance evaluation of three prominent long-range wireless communications, namely LoRa and Wi-Fi HaLow in the ISM band and NB-IoT in the licensed band, to better understand their benefits and limitations in the context of four smart city application scenarios. These scenarios cover both under and above ground applications in areas with different propagation properties.
{"title":"Performance Evaluation of Wi-Fi HaLow, NB-IoT and LoRa for Smart City Applications","authors":"R. Verhoeven, Stash Kempinski, N. Meratnia","doi":"10.1145/3551663.3558596","DOIUrl":"https://doi.org/10.1145/3551663.3558596","url":null,"abstract":"Long-range wireless technologies are at the core of Internet of Things (IoT) and smart city applications. While they offer many advantages in terms of ease of deployment, flexibility, mobility, and ubiquity, to name but a few, they are not equally suitable for smart city applications. Since 'one size fits all' does not hold in this context, finding out which long-range wireless technology is the best requires a thorough performance evaluation of these technologies in specific context and scenarios. In this paper, we focus on performance evaluation of three prominent long-range wireless communications, namely LoRa and Wi-Fi HaLow in the ISM band and NB-IoT in the licensed band, to better understand their benefits and limitations in the context of four smart city application scenarios. These scenarios cover both under and above ground applications in areas with different propagation properties.","PeriodicalId":55557,"journal":{"name":"Ad Hoc & Sensor Wireless Networks","volume":"1 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89911969","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ekler Paulino de Mattos, A. C. Domingues, Fabrício A. Silva, Heitor S. Ramos, A. Loureiro
In the flowering of ubiquitous computing, networks like the Internet of Things and the Internet of Vehicles have contributed to connecting objects and sharing location services in broad environments like smart cities bringing many benefits to citizens. However, these services yield massive and unrestricted mobility data of citizens that pose privacy concerns, among them recovering the identity of citizens with linking attacks. Although several privacy mechanisms have been proposed to solve anonymization problems, there are few studies about their behavior and analysis of the data quality anonymized by these techniques. In this paper, we introduce the anonymization quality. For this, we propose analyzing the mix-zones metrics Amount of Cars on Mix-zone (ACM), Interval of Arrival Time between Cars on Mix-zones (ITM), and Activation Time of the Mix-zone (ATM) for characterizing and evaluating the impacts of anonymization quality over time and space in mobility data. The results showed that mix-zone metrics reflect anonymization behavior and can measure the anonymization quality over time. This insight can contribute significantly to building privacy proposes based on anonymization more effectively than based only on traffic flow. To our knowledge, this is the first work that uses mix-zones metrics analysis to observe the anonymization behavior in quality terms.
{"title":"Behind the Mix-Zones Scenes: On the Evaluation of the Anonymization Quality","authors":"Ekler Paulino de Mattos, A. C. Domingues, Fabrício A. Silva, Heitor S. Ramos, A. Loureiro","doi":"10.1145/3551663.3558601","DOIUrl":"https://doi.org/10.1145/3551663.3558601","url":null,"abstract":"In the flowering of ubiquitous computing, networks like the Internet of Things and the Internet of Vehicles have contributed to connecting objects and sharing location services in broad environments like smart cities bringing many benefits to citizens. However, these services yield massive and unrestricted mobility data of citizens that pose privacy concerns, among them recovering the identity of citizens with linking attacks. Although several privacy mechanisms have been proposed to solve anonymization problems, there are few studies about their behavior and analysis of the data quality anonymized by these techniques. In this paper, we introduce the anonymization quality. For this, we propose analyzing the mix-zones metrics Amount of Cars on Mix-zone (ACM), Interval of Arrival Time between Cars on Mix-zones (ITM), and Activation Time of the Mix-zone (ATM) for characterizing and evaluating the impacts of anonymization quality over time and space in mobility data. The results showed that mix-zone metrics reflect anonymization behavior and can measure the anonymization quality over time. This insight can contribute significantly to building privacy proposes based on anonymization more effectively than based only on traffic flow. To our knowledge, this is the first work that uses mix-zones metrics analysis to observe the anonymization behavior in quality terms.","PeriodicalId":55557,"journal":{"name":"Ad Hoc & Sensor Wireless Networks","volume":"34 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82773475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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