{"title":"Enabling Attribute-Based Access Control in NoSQL Databases","authors":"Eeshan Gupta;Shamik Sural;Jaideep Vaidya;Vijayalakshmi Atluri","doi":"10.1109/TETC.2022.3193577","DOIUrl":"10.1109/TETC.2022.3193577","url":null,"abstract":"NoSQL databases are being increasingly used for efficient management of high volumes of unstructured data in applications like information retrieval, natural language processing, social computing, etc. However, unlike traditional databases, data protection measures such as access control for these databases are still in their infancy, which could lead to significant vulnerabilities and security/privacy issues as their adoption increases. Attribute-based Access Control (ABAC), which provides a flexible and dynamic solution to access control, can be effective for mediating accesses in typical usage scenarios for NoSQL databases. In this paper, we propose a novel methodology for enabling ABAC in NoSQL databases. Specifically we consider MongoDB, which is one of the most popular NoSQL databases in use today. We present an approach to both specify ABAC access control policies and to enforce them when an actual access request has been made. MongoDB Wire Protocol is used for extracting and processing appropriate information from the requests. We also present a method for supporting dynamic access decisions using environmental attributes and handling of ad-hoc access requests through digitally signed user attributes. Results from an extensive set of experiments on the Enron corpus as well as on synthetically generated data demonstrate the scalability of our approach. Finally, we provide details of our implementation on MongoDB and share a Github repository so that any organization can download and deploy the same for enabling ABAC in their own MongoDB installations.","PeriodicalId":13156,"journal":{"name":"IEEE Transactions on Emerging Topics in Computing","volume":"11 1","pages":"208-223"},"PeriodicalIF":5.9,"publicationDate":"2022-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9844984","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9583559","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":"The Indoor Predictability of Human Mobility: Estimating Mobility With Smart Home Sensors","authors":"Tinghui Wang;Diane J. Cook;Thomas R. Fischer","doi":"10.1109/TETC.2022.3188939","DOIUrl":"10.1109/TETC.2022.3188939","url":null,"abstract":"Analyzing human mobility patterns is valuable for understanding human behavior and providing location-anticipating services. In this work, we theoretically estimate the predictability of human movement for indoor settings, a problem that has not yet been tackled by the community. To validate the model, we utilize location data collected by ambient sensors in residential settings. The data support the model and allow us to contrast the predictability of various groups, including single-resident homes, homes with multiple residents, and homes with pets.","PeriodicalId":13156,"journal":{"name":"IEEE Transactions on Emerging Topics in Computing","volume":"11 1","pages":"182-193"},"PeriodicalIF":5.9,"publicationDate":"2022-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10348693/pdf/nihms-1862053.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10207801","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":"Interference Mitigation for Cyber-Physical Wireless Body Area Network System Using Social Networks","authors":"Zhaoyang Zhang;Honggang Wang;Chonggang Wang;Hua Fang","doi":"10.1109/TETC.2013.2274430","DOIUrl":"10.1109/TETC.2013.2274430","url":null,"abstract":"Wireless body area networks (WBANs) are cyber-physical systems that emerged as a key technology to provide real-time health monitoring and ubiquitous healthcare services. WBANs could operate in dense environments such as in a hospital and lead to a high mutual communication interference in many application scenarios. The excessive interferences will significantly degrade the network performance, including depleting the energy of WBAN nodes more quickly and even eventually jeopardize people's lives because of unreliable (caused by the interference) healthcare data collections. Therefore, it is critical to mitigate the interference among WBANs to increase the reliability of the WBAN system while minimizing the system power consumption. Many existing approaches can deal with communication interference mitigation in general wireless networks but are not suitable for WBANs because of ignoring the social nature of WBANs by them. Unlike the previous research, we for the first time propose a power game based approach to mitigate the communication interferences for WBANs based on the people's social interaction information. Our major contributions include: 1) modeling the inter-WBANs interference and determine the distance distribution of the interference through both theoretical analysis and Monte Carlo simulations; 2) developing social interaction detection and prediction algorithms for people carrying WBANs; and 3) developing a power control game based on the social interaction information to maximize the system's utility while minimize the energy consumption of WBANs system. The extensive simulation results show the effectiveness of the power control game for inter-WBAN interference mitigation using social interaction information. Our research opens a new research vista of WBANs using social networks.","PeriodicalId":13156,"journal":{"name":"IEEE Transactions on Emerging Topics in Computing","volume":"1 1","pages":"121-132"},"PeriodicalIF":5.9,"publicationDate":"2013-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TETC.2013.2274430","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"32848485","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}