{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T03:55:45Z","timestamp":1760241345242,"version":"build-2065373602"},"reference-count":36,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2018,2,5]],"date-time":"2018-02-05T00:00:00Z","timestamp":1517788800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Indoor localization based on WiFi has attracted a lot of research effort because of the widespread application of WiFi. Fingerprinting techniques have received much attention due to their simplicity and compatibility with existing hardware. However, existing fingerprinting localization algorithms may not resist abnormal received signal strength indication (RSSI), such as unexpected environmental changes, impaired access points (APs) or the introduction of new APs. Traditional fingerprinting algorithms do not consider the problem of new APs and impaired APs in the environment when using RSSI. In this paper, we propose a secure fingerprinting localization (SFL) method that is robust to variable environments, impaired APs and the introduction of new APs. In the offline phase, a voting mechanism and a fingerprint database update method are proposed. We use the mutual cooperation between reference anchor nodes to update the fingerprint database, which can reduce the interference caused by the user measurement data. We analyze the standard deviation of RSSI, mobilize the reference points in the database to vote on APs and then calculate the trust factors of APs based on the voting results. In the online phase, we first make a judgment about the new APs and the broken APs, then extract the secure fingerprints according to the trusted factors of APs and obtain the localization results by using the trusted fingerprints. In the experiment section, we demonstrate the proposed method and find that the proposed strategy can resist abnormal RSSI and can improve the localization accuracy effectively compared with the existing fingerprinting localization algorithms.<\/jats:p>","DOI":"10.3390\/s18020469","type":"journal-article","created":{"date-parts":[[2018,2,5]],"date-time":"2018-02-05T10:12:49Z","timestamp":1517825569000},"page":"469","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["Secure Indoor Localization Based on Extracting Trusted Fingerprint"],"prefix":"10.3390","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0858-427X","authenticated-orcid":false,"given":"Juan","family":"Luo","sequence":"first","affiliation":[{"name":"School of Information Science and Engineering, Hunan University, Changsha 410012, China"}]},{"given":"Xixi","family":"Yin","sequence":"additional","affiliation":[{"name":"School of Information Science and Engineering, Hunan University, Changsha 410012, China"}]},{"given":"Yanliu","family":"Zheng","sequence":"additional","affiliation":[{"name":"School of Information Science and Engineering, Hunan University, Changsha 410012, China"}]},{"given":"Chun","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Information Science and Engineering, Hunan University, Changsha 410012, China"}]}],"member":"1968","published-online":{"date-parts":[[2018,2,5]]},"reference":[{"key":"ref_1","first-page":"274","article-title":"Indoor location based services challenges, requirements and usability of current solutions","volume":"84","author":"Basiri","year":"2017","journal-title":"Comput. Sci. Rev."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Torres-Sospedra, J., and Moreira, A. (2017). Analysis of Sources of Large Localization Errors in Deterministic Fingerprinting. Sensors, 17.","DOI":"10.3390\/s17122736"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1016\/j.eswa.2014.07.042","article-title":"Indoor localization in a hospital environment using Random Forest classifiers","volume":"42","author":"Calderoni","year":"2015","journal-title":"Expert Syst. Appl."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"2026","DOI":"10.3390\/s120202026","article-title":"Localization Algorithms of Underwater Wireless Sensor Networks: A Survey","volume":"12","author":"Han","year":"2012","journal-title":"Sensors"},{"key":"ref_5","first-page":"89","article-title":"Position, Location, Place and Area: An Indoor Perspective","volume":"3","author":"Sithole","year":"2016","journal-title":"Isprs Ann. Photogrammetry Remote Sens. Spat. Inf."},{"key":"ref_6","unstructured":"Chen, Y., Chen, L., and Shu, L. (2013). GPS-Free Indoor positioning for Mobile Sensor Networks. Wirel. Sensor Netw., Available online: https:\/\/www.researchgate.net\/publication\/300299125_GPS-Free_Indoor_Localization_for_Mobile_Sensor_Networks."},{"key":"ref_7","unstructured":"Bahl, P., and Padmanabhan, V.N. (2000, January 26\u201330). RADAR: An in-building RF-based user location and tracking system. Proceedings of the Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies, Tel Aviv, Israel."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"832","DOI":"10.1109\/LAWP.2014.2316973","article-title":"A Trainingless WiFi Fingerprint Positioning Approach Over Mobile Devices","volume":"13","author":"Bisio","year":"2014","journal-title":"IEEE Antennas Wirel. Propag. Lett."},{"key":"ref_9","first-page":"145","article-title":"Location determination using WiFi fingerprinting versus WiFi trilateration","volume":"1","author":"Mok","year":"2007","journal-title":"J. Locat. Serv."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"311","DOI":"10.1016\/j.ifacol.2016.12.055","article-title":"Summary of available indoor location techniques","volume":"49","author":"Streit","year":"2016","journal-title":"IFAC-PapersOnLine"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"715","DOI":"10.3390\/s150100715","article-title":"Fusion of WiFi, Smartphone Sensors and Landmarks Using the Kalman Filter for Indoor Localization","volume":"15","author":"Chen","year":"2015","journal-title":"Sensors"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1016\/j.pmcj.2016.02.001","article-title":"Smart, probabilistic fingerprinting for WiFi-based indoor positioning with mobile devices","volume":"31","author":"Bisio","year":"2016","journal-title":"Pervasive Mob. Comput."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1897","DOI":"10.1109\/TMC.2016.2608946","article-title":"Indoor localization and automatic fingerprint update with altered AP signals","volume":"16","author":"He","year":"2017","journal-title":"IEEE Transact. Mob. Comput."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Kim, S., Ha, S., and Saad, A. (2015, January 21\u201323). Indoor positioning system techniques and security. Proceedings of the 2015 Forth International Conference on e-Technologies and Networks for Development, Lodz, Poland.","DOI":"10.1109\/ICeND.2015.7328540"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Meng, W., Xiao, W., and Ni, W. (2011, January 21\u201323). Secure and robust Wi-Fi fingerprinting indoor localization. Proceedings of the 2011 International Conference on Indoor Positioning and Indoor Navigation, Guimaraes, Portugal.","DOI":"10.1109\/IPIN.2011.6071908"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"406","DOI":"10.1016\/j.pmcj.2012.12.003","article-title":"Smartphone-based Wi-Fi tracking system exploiting the RSS peak to overcome the RSS variance problem","volume":"9","author":"Kim","year":"2013","journal-title":"Pervasive Mob. Comput."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"292","DOI":"10.1016\/j.pmcj.2011.09.003","article-title":"Analysis of WLAN\u2019s received signal strength indication for indoor location fingerprinting","volume":"8","author":"Kaemarungsi","year":"2012","journal-title":"Pervasive Mob. Comput."},{"key":"ref_18","unstructured":"Bisio, I., Lavagetto, F., Marchese, M., and Sciarrone, A. (2013). Performance comparison of a probabilistic fingerprint-based indoor positioning system over different smartphones. SPECTS, 161\u2013166."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Li, L., Shen, G., Zhao, C., Moscibroda, T., Lin, J., and Zhao, F. (2014, January 7\u201311). Experiencing and handling the diversity in data density and environmental locality in an indoor positioning service. Proceedings of the 20th Annual International Conference on Mobile Computing and Networking, Hawaii, HI, USA.","DOI":"10.1145\/2639108.2639118"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"329","DOI":"10.1016\/j.comnet.2015.08.032","article-title":"Improving indoor positioning precision by using received signal strength fingerprint and footprint based on weighted ambient Wi-Fi signals","volume":"91","author":"Leu","year":"2015","journal-title":"Comput. Netw."},{"key":"ref_21","unstructured":"Luo, Y.F., and Chen, Y.F. (2017). Simulation Research on Person Security Monitoring and Localization Algorithm in Coal Mine. Measurement Control Technol., Available online: http:\/\/en.cnki.com.cn\/Article_en\/CJFDTotal-IKJS201703033.htm."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"877","DOI":"10.1109\/TKDE.2006.112","article-title":"Power-efficient access-point selection for indoor location estimation","volume":"18","author":"Chen","year":"2006","journal-title":"IEEE Transact. Knowl. Data Eng."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/JSEN.2017.2660522","article-title":"Improved Wi-Fi RSSI Measurement for Indoor Localization","volume":"17","author":"Xue","year":"2017","journal-title":"J. IEEE Sensors"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Liu, Y., Luo, J., Yang, Q., and Hu, J. (2015, January 18\u201320). Feedback Mechanism Based Dynamic Fingerprint Indoor Localization Algorithm in Wireless Sensor Networks. Proceedings of the International Conference on Algorithms and Architectures for Parallel Processing, Zhangjiajie, China.","DOI":"10.1007\/978-3-319-27119-4_47"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1016\/j.pmcj.2015.10.005","article-title":"Wi-Fi fingerprinting based on collaborative confidence level training","volume":"30","author":"Jing","year":"2016","journal-title":"Pervasive Mob. Comput."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"118","DOI":"10.1016\/j.pmcj.2015.02.001","article-title":"Autonomous smartphone-based WiFi positioning system by using access points localization and crowdsourcing","volume":"18","author":"Zhuang","year":"2015","journal-title":"Pervasive Mob. Comput."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Zhuang, Y., Shen, Z., and Syed, Z. (2014, January 5\u20138). Autonomous WLAN heading and position for smartphones. Proceedings of the Position, Location and Navigation Symposium\u2014PLANS 2014, Monterey, CA, USA.","DOI":"10.1109\/PLANS.2014.6851481"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Park, J., Charrow, B., and Curtis, D. (2010, January 15\u201318). Growing an organic indoor location system. Proceedings of the 8th International Conference on Mobile Systems, Applications, and Services, San Francisco, CA, USA.","DOI":"10.1145\/1814433.1814461"},{"key":"ref_29","unstructured":"Krishnakumar, A., and Krishnan, P. (2005, January 13\u201317). On the accuracy of signal strength-based estimation techniques. Proceedings of the IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies, Florida, FL, USA."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"560","DOI":"10.1016\/j.pmcj.2007.02.002","article-title":"A priori error estimates for wireless local area network positioning systems","volume":"3","author":"Wallbaum","year":"2007","journal-title":"Pervasive Mob. Comput."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Dempster, A.G., Li, B., and Quader, I. (2008, January 7\u20139). Errors in determinstic wireless fingerprinting systems for localisation. Proceedings of the International Symposium on Wireless Pervasive Computing. IEEE, Santorini, Greece.","DOI":"10.1109\/ISWPC.2008.4556177"},{"key":"ref_32","first-page":"789","article-title":"Underground target location method based on distance constraint","volume":"39","author":"Liu","year":"2014","journal-title":"J. China Coal Soc."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Fang, W., Wang, H., and Hu, Z. (2017, January 21\u201324). Filter Anchor Node Localization Algorithm Based on Rssi for Underground Mine Wireless Sensor Networks. Proceedings of the IEEE International Conference on Computational Science and Engineering IEEE, Guangzhou, China.","DOI":"10.1109\/CSE-EUC.2017.127"},{"key":"ref_34","unstructured":"Haeberlen, A., Flannery, E., and Ladd, A.M. (October, January 26). Practical robust localization over large-scale 802.11 wireless networks. Proceedings of the 10th Annual International Conference on Mobile Computing and Networking, Philadelphia, PA, USA."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"357","DOI":"10.1007\/s11276-006-0725-7","article-title":"The Horus location determination system","volume":"14","author":"Youssef","year":"2008","journal-title":"Wirel. Netw."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"2657","DOI":"10.1016\/j.neucom.2007.11.045","article-title":"A modular classification model for received signal strength based location systems","volume":"71","author":"Ahmad","year":"2008","journal-title":"Neurocomputing"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/18\/2\/469\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T14:53:51Z","timestamp":1760194431000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/18\/2\/469"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,2,5]]},"references-count":36,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2018,2]]}},"alternative-id":["s18020469"],"URL":"https:\/\/doi.org\/10.3390\/s18020469","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2018,2,5]]}}}