A survey on indoor positioning security and privacy
References
[1]
F. Abdel-Fattah, K.A. Farhan, F.H. Al-Tarawneh, F. AlTamimi, Security challenges and attacks in dynamic mobile ad hoc networks MANETs, 2019 IEEE Jordan International Joint Conference on Electrical Engineering and Information Technology (JEEIT), 2019, pp. 28–33,.
[2]
A. Abdelaziz, C.E. Koksal, H. El Gamal, On the security of angle of arrival estimation, 2016 IEEE Conference on Communications and Network Security (CNS), 2016, pp. 109–117,.
[3]
M.A. Al-Garadi, A. Mohamed, A.K. Al-Ali, X. Du, I. Ali, M. Guizani, A survey of machine and deep learning methods for Internet of Things (IoT) security, IEEE Commun. Surv. Tutor. 22 (3) (2020) 1646–1685,.
[4]
A. Alanwar, Y. Shoukry, S. Chakraborty, P. Martin, P. Tabuada, M. Srivastava, PrOLoc: resilient localization with private observers using partial homomorphic encryption, Proceedings of the 16th ACM/IEEE International Conference on Information Processing in Sensor Networks, Association for Computing Machinery, New York, NY, USA, 2017, pp. 41–52,.
[5]
F. Alhomayani, M.H. Mahoor, Deep learning methods for fingerprint-based indoor positioning: a review, J. Locat. Based Serv. 14 (3) (2020) 129–200,.
[6]
D. Alrababah, E. Al-Shammari, A. Alsuht, A survey: authentication protocols for wireless sensor network in the Internet of Things; keys and attacks, 2017 International Conference on New Trends in Computing Sciences (ICTCS), 2017, pp. 270–276,.
[7]
S. Anandhi, R. Anitha, V. Sureshkumar, IoT enabled RFID authentication and secure object tracking system for smart logistics. Wirel. Pers, Commun 104 (2) (2019) 543–560,.
[8]
Y. Arjoune, F. Salahdine, M.S. Islam, E. Ghribi, N. Kaabouch, A novel jamming attacks detection approach based on machine learning for wireless communication, 2020 International Conference on Information Networking (ICOIN), 2020, pp. 459–464,.
[9]
F. Armknecht, C. Boyd, C. Carr, K. Gjøsteen, A. Jäschke, C.A. Reuter, M. Strand, A guide to fully homomorphic encryption, IACR Cryptol. ePrint Arch. 2015 (2015) 1192.
[10]
M. Arul Selvan, S. Selvakumar, Malicious node identification using quantitative intrusion detection techniques in MANET, Cluster Comput. 22 (3) (2019) 7069–7077,.
[11]
G. Avoine, M.A. Bingöl, I. Boureanu, S. čapkun, G. Hancke, S. Kardaş, C.H. Kim, C. Lauradoux, B. Martin, J. Munilla, A. Peinado, K.B. Rasmussen, D. Singelée, A. Tchamkerten, R. Trujillo-Rasua, S. Vaudenay, Security of distance-bounding: a survey, ACM Comput. Surv. 51 (5) (2018),.
[12]
G. Bahle, V. Fortes Rey, S. Bian, H. Bello, P. Lukowicz, Using privacy respecting sound analysis to improve Bluetooth based proximity detection for COVID-19 exposure tracing and social distancing, Sensors 21 (16) (2021),.
[13]
L. Bai, L. Zhu, J. Liu, J. Choi, W. Zhang, Physical layer authentication in wireless communication networks: a survey, J. Commun. Inf. Netw. 5 (3) (2020) 237–264,.
[14]
S. Banerjee, S. Xu, S.D. Johnson, How does location based marketing affect mobile retail revenues? The complex interplay of delivery tactic, interface mobility and user privacy, J. Bus. Res. 130 (2021) 398–404,.
[15]
A. Basiri, E.S. Lohan, T. Moore, A. Winstanley, P. Peltola, C. Hill, P. Amirian, P. Figueiredo e Silva, Indoor location based services challenges, requirements and usability of current solutions, Comput. Sci. Rev. 24 (2017) 1–12,.
[16]
Bell, J., Butler, D., Hicks, C., Crowcroft, J., 2020. TraceSecure: towards privacy preserving contact tracing. 10.48550/ARXIV.2004.04059
[17]
C. Bettini, Privacy protection in location-based services: a survey, Springer International Publishing, Cham, 2018, pp. 73–96,.
[18]
Bock, K., Khne, C. R., Mhlhoff, R., Ost, M. R., Pohle, J., Rehak, R., 2021. Data protection impact assessment for the corona app. 10.48550/ARXIV.2101.07292
[19]
A. Boutet, M. Cunche, Privacy protection for Wi-Fi location positioning systems, J. Inf. Secur. Appl. 58 (2021) 102635,.
[20]
I. Braithwaite, T. Callender, M. Bullock, R.W. Aldridge, Automated and partly automated contact tracing: a systematic review to inform the control of COVID-19, Lancet Digit. Health 2 (11) (2020) e607–e621,.
[21]
S. Brands, D. Chaum, Distance-bounding protocols, Workshop on the Theory and Application of Cryptographic Techniques on Advances in Cryptology, Springer-Verlag, Berlin, Heidelberg, 1994, pp. 344–359,.
[22]
R.F. Brena, J.P. García-Vzquez, C.E. Galvín-Tejada, D. Muoz-Rodriguez, C. Vargas-Rosales, J. Fangmeyer, Evolution of indoor positioning technologies: a survey, J. Sens. 2017 (2017) 2630413,.
[23]
R. Brooks, P.Y. Govindaraju, M. Pirretti, N. Vijaykrishnan, M.T. Kandemir, On the detection of clones in sensor networks using random key predistribution, IEEE Trans. Syst., Man, Cybern., Part C (Applications and Reviews) 37 (6) (2007) 1246–1258,.
[24]
F. Buccafurri, V. De Angelis, M. Francesca Idone, C. Labrini, A privacy-preserving protocol for proximity-based services in social networks, 2021 IEEE Global Communications Conference (GLOBECOM), 2021, pp. 1–6,.
[25]
R.M. Buehrer, H. Wymeersch, R.M. Vaghefi, Collaborative sensor network localization: algorithms and practical issues, Proc. IEEE 106 (6) (2018) 1089–1114,.
[26]
R.M. Buehrer, H. Wymeersch, R.M. Vaghefi, Collaborative Sensor Network Localization: Algorithms and Practical Issues, Proceedings of the IEEE 106 (6) (2018) 1089–1114,.
[27]
R. Carotenuto, M. Merenda, D. Iero, F.G. Della Corte, Mobile synchronization recovery for ultrasonic indoor positioning, Sensors (Basel) 20 (3) (2020) 702,.
[28]
S.A. Carter, D. Avrahami, N. Tokunaga, Using inaudible audio to improve indoor-localization- and proximity-aware intelligent applications, CoRR abs/2002.00091 (2020) https://arxiv.org/abs/2002.00091.
[29]
Castelluccia, C., Bielova, N., Boutet, A., Cunche, M., Lauradoux, C., Le Métayer, D., Roca, V., 2020. ROBERT: ROBust and privacy-presERving proximity Tracing. Working paper or preprint. https://hal.inria.fr/hal-02611265.
[30]
Chan, A. C.-F., Chung, R. M. H., 2021. Security and privacy of wireless beacon systems. 10.48550/ARXIV.2107.05868
[31]
T. Chapman, E. Larsson, P. von Wrycza, E. Dahlman, S. Parkvall, J. Skld, Chapter 3—CDMA transmission principles, in: T. Chapman, E. Larsson, P. von Wrycza, E. Dahlman, S. Parkvall, J. Skld (Eds.), HSPA Evolution, Academic Press, Oxford, 2015, pp. 35–48,.
[32]
Cho, H., Ippolito, D., Yu, Y. W., 2020. Contact tracing mobile apps for COVID-19: privacy considerations and related trade-offs. 10.48550/ARXIV.2003.11511
[33]
W. Chen, M. Guan, L. Wang, R. Ruby, K. Wu, FLoc: device-free passive indoor localization in complex environments, 2017 IEEE International Conference on Communications (ICC), 2017, pp. 1–6,.
[34]
L. Chen, S. Thombre, K. Jrvinen, E.S. Lohan, A. Aln-Savikko, H. Leppkoski, M.Z.H. Bhuiyan, S. Bu-Pasha, G.N. Ferrara, S. Honkala, J. Lindqvist, L. Ruotsalainen, P. Korpisaari, H. Kuusniemi, Robustness, security and privacy in location-based services for future IoT: a survey, IEEE Access 5 (2017) 8956–8977,.
[35]
J. Clulow, G.P. Hancke, M.G. Kuhn, T. Moore, So near and yet so far: distance-bounding attacks in wireless networks, Proceedings of the Third European Conference on Security and Privacy in Ad-Hoc and Sensor Networks, Springer-Verlag, Berlin, Heidelberg, 2006, pp. 83–97,.
[36]
C. Cremers, K.B. Rasmussen, B. Schmidt, S. Capkun, Distance hijacking attacks on distance bounding protocols, 2012 IEEE Symposium on Security and Privacy, 2012, pp. 113–127,.
[37]
L. Cui, C. Xu, G. Li, Z. Ming, Y. Feng, N. Lu, A high accurate localization algorithm with DV-Hop and differential evolution for wireless sensor network, Appl. Soft Comput. 68 (2018) 39–52,.
[38]
P. Davidson, R. Pich, A survey of selected indoor positioning methods for smartphones, IEEE Commun. Surv. Tutor. 19 (2) (2017) 1347–1370,.
[39]
Y. Desmedt, Major security problems with the ‘unforgeable’ (Feige)–Fiat–Shamir proofs of identity and how to overcome them, Proceedings of SECURICOM, vol. 88, 1988, pp. 15–17.
[40]
A.R. Destiarti, P. Kristalina, A. Sudarsono, Secure data transmission scheme for indoor mobile cooperative localization system, 2017 International Electronics Symposium on Engineering Technology and Applications (IES-ETA), 2017, pp. 50–56,.
[41]
C. Di Franco, M. Marinoni, E. Bini, G.C. Buttazzo, Dynamic multidimensional scaling with anchors and height constraints for indoor localization of mobile nodes, Robot. Auton. Syst. 108 (2018) 28–37,.
[42]
S. Djuraev, J.-G. Choi, K.-S. Sohn, S.Y. Nam, Channel hopping scheme to mitigate jamming attacks in wireless LANs, EURASIP J. Wirel. Commun. Netw. 2017 (1) (2017) 11,.
[43]
N.-S. Duong, T.-M.D. Thi, Smartphone indoor positioning based on enhanced BLE beacon multi-lateration, TELKOMNIKA 19 (1) (2021) 51–62,.
[44]
M. Dusmanu, J.L. Schönberger, S.N. Sinha, M. Pollefeys, Privacy-preserving image features via adversarial affine subspace embeddings, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021, pp. 14262–14272,.
[45]
N. Dutta, M.M. Singh, Wormhole attack in wireless sensor networks: a critical review, in: J.K. Mandal, D. Bhattacharyya, N. Auluck (Eds.), Advanced Computing and Communication Technologies, Springer Singapore, Singapore, 2019, pp. 147–161.
[46]
S. Faruque, Introduction to Channel Coding, Springer International Publishing, Cham, 2016, pp. 1–16.
[47]
Y. Feng, W. Wang, Y. Weng, H. Zhang, A replay-attack resistant authentication scheme for the Internet of Things, 2017 IEEE International Conference on Computational Science and Engineering (CSE) and IEEE International Conference on Embedded and Ubiquitous Computing (EUC), vol. 1, 2017, pp. 541–547,.
[48]
R. Focardi, F.L. Luccio, H.A. Wahsheh, Usable security for QR code, J. Inf. Secur. Appl. 48 (2019) 102369,.
[49]
B. Gao, T. Maekawa, D. Amagata, T. Hara, Environment-adaptive malicious node detection in MANETs with ensemble learning, 2018 IEEE 38th International Conference on Distributed Computing Systems (ICDCS), 2018, pp. 556–566,.
[50]
Google, 2020. Exposure notifications: helping fight COVID-19. https://www.google.com/covid19/exposurenotifications/.
[51]
M. Geppert, V. Larsson, J.L. Schönberger, M. Pollefeys, Privacy preserving partial localization, Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022, pp. 17337–17347,.
[52]
V. Gomathy, N. Padhy, D. Samanta, M. Sivaram, V. Jain, I.S. Amiri, Malicious node detection using heterogeneous cluster based secure routing protocol (HCBS) in wireless adhoc sensor networks, J. Ambient Intell. Humaniz. Comput. 11 (11) (2020) 4995–5001,.
[53]
F. Gu, J. Niu, L. Duan, WAIPO: a fusion-based collaborative indoor localization system on smartphones, IEEE/ACM Trans. Networking 25 (4) (2017) 2267–2280,.
[54]
R. Guan, R. Harle, Signal fingerprint anomaly detection for probabilistic indoor positioning, 2018 International Conference on Indoor Positioning and Indoor Navigation (IPIN), 2018, pp. 1–8,.
[55]
Á.M. Guerrero-Higueras, N. DeCastro-García, V. Matelln, Detection of cyber-attacks to indoor real time localization systems for autonomous robots, Robot. Auton. Syst. 99 (2018) 75–83,.
[56]
S. Han, U. Topcu, G.J. Pappas, Differentially private distributed constrained optimization, IEEE Trans. Autom. Control 62 (1) (2017) 50–64,.
[57]
V. Hassija, V. Chamola, V. Saxena, D. Jain, P. Goyal, B. Sikdar, A survey on IoT security: application areas, security threats, and solution architectures, IEEE Access 7 (2019) 82721–82743,.
[58]
M. Hata, Empirical formula for propagation loss in land mobile radio services, IEEE Trans. Veh. Technol. 29 (3) (1980) 317–325,.
[59]
K. Heurtefeux, F. Valois, Is RSSI a good choice for localization in wireless sensor network?, 2012 IEEE 26th International Conference on Advanced Information Networking and Applications, 2012, pp. 732–739,.
[60]
S. Holcer, J. Torres-Sospedra, M. Gould, I. Remolar, Privacy in indoor positioning systems: a systematic review, 2020 International Conference on Localization and GNSS (ICL-GNSS), 2020, pp. 1–6,.
[61]
Y. Hou, X. Yang, Q.H. Abbasi, Efficient AoA-based wireless indoor localization for hospital outpatients using mobile devices, Sensors 18 (11) (2018),.
[62]
J. Hu, H. Lin, X. Guo, J. Yang, DTCs: an integrated strategy for enhancing data trustworthiness in mobile crowdsourcing, IEEE Internet Things J. 5 (6) (2018) 4663–4671,.
[63]
Z. Hu, Y. Li, G. Jiang, R. Zhang, M. Xie, Prihorus: privacy-preserving RSS-based indoor positioning, ICC 2022 - IEEE International Conference on Communications, 2022, pp. 5627–5632,.
[64]
J. Hua, H. Sun, Z. Shen, Z. Qian, S. Zhong, Accurate and efficient wireless device fingerprinting using channel state information, IEEE INFOCOM 2018 - IEEE Conference on Computer Communications, 2018, pp. 1700–1708,.
[65]
D.-W. Huang, W. Liu, J. Bi, Data tampering attacks diagnosis in dynamic wireless sensor networks, Comput. Commun. 172 (2021) 84–92,.
[66]
S.U. Hussain, F. Koushanfar, Privacy preserving localization for smart automotive systems, Proceedings of the 53rd Annual Design Automation Conference, Association for Computing Machinery, New York, NY, USA, 2016,.
[67]
S. Hymlin Rose, T. Jayasree, Detection of jamming attack using timestamp for WSN, Ad Hoc Netw. 91 (2019) 101874,.
[68]
A. Ihler, J. Fisher, R. Moses, A. Willsky, Nonparametric belief propagation for self-localization of sensor networks, IEEE J. Sel. Areas Commun. 23 (4) (2005) 809–819,.
[69]
S. Jain, A. Singh, A. Kaur, S. Jain, Improved APIT localization algorithm in wireless sensor networks, 2017 4th International Conference on Signal Processing, Computing and Control (ISPCC), 2017, pp. 77–81,.
[70]
K. Järvinen, Á. Kiss, T. Schneider, O. Tkachenko, Z. Yang, Faster privacy-preserving location proximity schemes, in: J. Camenisch, P. Papadimitratos (Eds.), Cryptology and Network Security, Springer International Publishing, Cham, 2018, pp. 3–22,.
[71]
K. Järvinen, H. Leppkoski, E.-S. Lohan, P. Richter, T. Schneider, O. Tkachenko, Z. Yang, PILOT: practical privacy-preserving indoor localization using outsourcing, 2019 IEEE European Symposium on Security and Privacy (EuroS&P), 2019, pp. 448–463,.
[72]
K.E. Jeon, J. She, P. Soonsawad, P.C. Ng, BLE beacons for Internet of Things applications: survey, challenges, and opportunities, IEEE Internet Things J. 5 (2) (2018) 811–828,.
[73]
H. Jiang, J. Li, P. Zhao, F. Zeng, Z. Xiao, A. Iyengar, Location privacy-preserving mechanisms in location-based services: a comprehensive survey, ACM Comput. Surv. 54 (1) (2021),.
[74]
J. Jiang, G. Han, H. Wang, M. Guizani, A survey on location privacy protection in wireless sensor networks, J. Netw. Comput. Appl. 125 (2019) 93–114,.
[75]
G. Kalantar, A. Mohammadi, S.N. Sadrieh, Analyzing the effect of Bluetooth Low Energy (BLE) with randomized MAC addresses in IoT applications, 2018 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData), 2018, pp. 27–34,.
[76]
J. Kang, J. Seo, Y. Won, Ephemeral ID beacon-based improved indoor positioning system, Symmetry 10 (11) (2018),.
[77]
H. Kaur, S. Saxena, A review on node replication attack identification schemes in WSN, 2017 8th International Conference on Computing, Communication and Networking Technologies (ICCCNT), 2017, pp. 1–8,.
[78]
A. Khalajmehrabadi, N. Gatsis, D. Akopian, Modern WLAN fingerprinting indoor positioning methods and deployment challenges, IEEE Commun. Surv. Tutor. 19 (3) (2017) 1974–2002,.
[79]
B. Kim, J. Song, An efficient and practical mobile node reauthentication scheme for mobile wireless sensor networks, Proceedings of the 3rd International Conference on Communication and Information Processing, Association for Computing Machinery, New York, NY, USA, 2017, pp. 326–331,.
[80]
J.W. Kim, D.-H. Kim, B. Jang, Application of local differential privacy to collection of indoor positioning data, IEEE Access 6 (2018) 4276–4286,.
[81]
T. Kluge, C. Groba, T. Springer, Trilateration, fingerprinting, and centroid: taking indoor positioning with Bluetooth LE to the wild, 2020 IEEE 21st International Symposium on “A World of Wireless, Mobile and Multimedia Networks” (WoWMoM), 2020, pp. 264–272,.
[82]
C.P. Kohlios, T. Hayajneh, A comprehensive attack flow model and security analysis for Wi-Fi and WPA3, Electronics 7 (11) (2018),.
[83]
M. Kolakowski, Automated calibration of RSS fingerprinting based systems using a mobile robot and machine learning, Sensors 21 (18) (2021),.
[84]
S. Krishnan, R. Xenia Mendoza Santos, E. Ranier Yap, M. Thu Zin, Improving UWB based indoor positioning in industrial environments through machine learning, 2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV), 2018, pp. 1484–1488,.
[85]
E. Kudoh, J. Watanabe, Y. Hiratsuka, MMSE location estimation using multiple items of sensed information in indoor environments, 2017 Ninth International Conference on Ubiquitous and Future Networks (ICUFN), 2017, pp. 266–268,.
[86]
D. Kukreja, S.K. Dhurandher, B.R. Reddy, Power aware malicious nodes detection for securing MANETs against packet forwarding misbehavior attack, J. Ambient Intell. Humaniz. Comput. 9 (4) (2018) 941–956,.
[87]
J. Kunhoth, A. Karkar, S. Al-Maadeed, A. Al-Ali, Indoor positioning and wayfinding systems: a survey, Human-Centric Comput. Inf. Sci. 10 (1) (2020) 18,.
[88]
C. Laoudias, A. Moreira, S. Kim, S. Lee, L. Wirola, C. Fischione, A survey of enabling technologies for network localization, tracking, and navigation, IEEE Commun. Surv. Tutor. 20 (4) (2018) 3607–3644,.
[89]
Lehtimaki, S., 2018. Bluetooth angle estimation for real-time locationing. https://bit.ly/3NQRaEc.
[90]
P. Leu, M. Singh, M. Roeschlin, K.G. Paterson, S. Čapkun, Message time of arrival codes: a fundamental primitive for secure distance measurement, 2020 IEEE Symposium on Security and Privacy (SP), 2020, pp. 500–516,.
[91]
H. Li, Y. He, X. Cheng, L. Sun, A lightweight location privacy-preserving scheme for WiFi fingerprint-based localization, 2016 International Conference on Identification, Information and Knowledge in the Internet of Things (IIKI), 2016, pp. 525–529,.
[92]
S. Li, W. Ni, C.K. Sung, M. Hedley, Recent advances on cooperative wireless localization and their application in inhomogeneous propagation environments, Comput. Netw. 142 (2018) 253–271,.
[93]
S. Li, R. Rashidzadeh, Hybrid indoor location positioning system, IET Wirel. Sens. Syst. 9 (5) (2019) 257–264,.
[94]
W. Li, Z. Su, R. Li, K. Zhang, Q. Xu, Abnormal crowd traffic detection for crowdsourced indoor positioning in heterogeneous communications networks, IEEE Trans. Netw. Sci. Eng. 7 (4) (2020) 2494–2505,.
[95]
Y. Li, Y. Hu, R. Zhang, Y. Zhang, T. Hedgpeth, Secure indoor positioning against signal strength attacks via optimized multi-voting, Proceedings of the International Symposium on Quality of Service, Association for Computing Machinery, New York, NY, USA, 2019,.
[96]
Z. Li, J. Huang, Study on the use of Q-R codes as landmarks for indoor positioning: preliminary results, 2018 IEEE/ION Position, Location and Navigation Symposium (PLANS), 2018, pp. 1270–1276,.
[97]
Z. Li, K. Xu, H. Wang, Y. Zhao, X. Wang, M. Shen, Machine-learning-based positioning: a survey and future directions, IEEE Netw. 33 (3) (2019) 96–101,.
[98]
A. Liberati, D.G. Altman, J. Tetzlaff, C. Mulrow, P.C. Gøtzsche, J.P.A. Ioannidis, M. Clarke, P.J. Devereaux, J. Kleijnen, D. Moher, The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate healthcare interventions: explanation and elaboration, BMJ 339 (2009),.
[99]
Y. Liu, A. Liu, X. Liu, X. Huang, A statistical approach to participant selection in location-based social networks for offline event marketing, Inf. Sci. 480 (2019) 90–108,.
[100]
Z. Liu, J. Liu, Y. Zeng, J. Ma, Covert wireless communications in IoT systems: hiding information in interference, IEEE Wirel. Commun. 25 (6) (2018) 46–52,.
[101]
X. Liu, S. Su, F. Han, Y. Liu, Z. Pan, A range-based secure localization algorithm for wireless sensor networks, IEEE Sens. J. 19 (2) (2019) 785–796,.
[102]
B. Liu, W. Zhou, T. Zhu, L. Gao, Y. Xiang, Location privacy and its applications: a systematic study, IEEE Access 6 (2018) 17606–17624,.
[103]
K. Lounis, M. Zulkernine, Attacks and defenses in short-range wireless technologies for IoT, IEEE Access 8 (2020) 88892–88932,.
[104]
J. Luo, X. Yin, Y. Zheng, C. Wang, Secure indoor localization based on extracting trusted fingerprint, Sensors 18 (2) (2018),.
[105]
R.C. Luo, T.J. Hsiao, Dynamic wireless indoor localization incorporating with an autonomous mobile robot based on an adaptive signal model fingerprinting approach, IEEE Trans. Ind. Electron. 66 (3) (2019) 1940–1951,.
[106]
M.T. Lwin, J. Yim, Y.-B. Ko, Blockchain-based lightweight trust management in mobile ad-hoc networks, Sensors 20 (3) (2020),.
[107]
R.C. Marqués, P. Pascacio, J. Hajny, J. Torres-Sospedra, Anonymous attribute-based credentials in collaborative indoor positioning systems, SECRYPT, 2021.
[108]
R. Mendrzik, G. Bauch, Position-constrained stochastic inference for cooperative indoor localization, IEEE Trans. Signal Inf. Process. Netw. 5 (3) (2019) 454–468,.
[109]
A.K. Mishra, A.K. Tripathy, D. Puthal, L.T. Yang, Analytical model for Sybil attack phases in Internet of Things, IEEE Internet Things J. 6 (1) (2019) 379–387,.
[110]
M. binti Mohamad Noor, W.H. Hassan, Current research on Internet of Things (IoT) security: a survey, Comput. Netw. 148 (2019) 283–294,.
[111]
B.K. Mohanta, D. Jena, U. Satapathy, S. Patnaik, Survey on IoT security: challenges and solution using machine learning, artificial intelligence and blockchain technology, Internet Things 11 (2020) 100227,.
[112]
T. Muhammed, R.A. Shaikh, An analysis of fault detection strategies in wireless sensor networks, J. Netw. Comput. Appl. 78 (2017) 267–287,.
[113]
A. Narayanan, V. Shmatikov, Robust de-anonymization of large sparse datasets, 2008 IEEE Symposium on Security and Privacy (sp 2008), 2008, pp. 111–125,.
[114]
A.P. Nasution, V. Suryani, A.A. Wardana, IoT object security towards on-off attack using trustworthiness management, 2020 8th International Conference on Information and Communication Technology (ICoICT), 2020, pp. 1–6,.
[115]
N. Neshenko, E. Bou-Harb, J. Crichigno, G. Kaddoum, N. Ghani, Demystifying IoT security: an exhaustive survey on IoT vulnerabilities and a first empirical look on internet-scale IoT exploitations, IEEE Commun. Surv. Tutor. 21 (3) (2019) 2702–2733,.
[116]
A. Nessa, B. Adhikari, F. Hussain, X.N. Fernando, A survey of machine learning for indoor positioning, IEEE Access 8 (2020) 214945–214965,.
[117]
P.C. Ng, J. She, S. Park, High resolution beacon-based proximity detection for dense deployment, IEEE Trans. Mob. Comput. 17 (6) (2018) 1369–1382,.
[118]
T.N. Nguyen, V.V. Le, S.-I. Chu, B.-H. Liu, Y.-C. Hsu, Secure localization algorithms against localization attacks in wireless sensor networks, Wirel. Pers. Commun. (2021),.
[119]
R. Nieminen, K. Järvinen, Practical privacy-preserving indoor localization based on secure two-party computation, IEEE Trans. Mob. Comput. 20 (9) (2021) 2877–2890,.
[120]
M. Numan, F. Subhan, W.Z. Khan, S. Hakak, S. Haider, G.T. Reddy, A. Jolfaei, M. Alazab, A systematic review on clone node detection in static wireless sensor networks, IEEE Access 8 (2020) 65450–65461,.
[121]
H. Ólafsdóttir, A. Ranganathan, S. Capkun, On the security of carrier phase-based ranging, in: Fischer W., Homma N. (Eds.), Cryptographic Hardware and Embedded Systems – CHES 2017, Springer International Publishing, Cham, 2017, pp. 490–509.
[122]
F. Orujov, R. Maskeliunas, R. Damaševičius, W. Wei, Y. Li, Smartphone based intelligent indoor positioning using fuzzy logic, Future Gener. Comput. Syst. 89 (2018) 335–348,.
[123]
O. Osanaiye, A.S. Alfa, G.P. Hancke, A statistical approach to detect jamming attacks in wireless sensor networks, Sensors 18 (6) (2018),.
[124]
P. Paillier, Public-key cryptosystems based on composite degree residuosity classes, in: Stern J. (Ed.), Advances in Cryptology — EUROCRYPT ’99, Springer Berlin Heidelberg, Berlin, Heidelberg, 1999, pp. 223–238.
[125]
F. Pan, Z. Pang, M. Xiao, H. Wen, R.-F. Liao, Clone detection based on physical layer reputation for proximity service, IEEE Access 7 (2019) 3948–3957,.
[126]
P. Pascacio, S. Casteleyn, J. Torres-Sospedra, E.S. Lohan, J. Nurmi, Collaborative indoor positioning systems: a systematic review, Sensors 21 (3) (2021),.
[127]
B. Pestourie, V. Beroulle, N. Fourty, Security evaluation with an indoor UWB localization open platform: acknowledgment attack case study, 2019 IEEE 30th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), 2019, pp. 1–7,.
[128]
Manohar, N., Manohar, P., Manohar, R., 2020. Habit: Hardware-assisted Bluetooth-based infection tracking. Cryptology ePrint Archive, Paper 2020/949. https://eprint.iacr.org/2020/949.
[129]
Pietrzak, K., 2020. Delayed authentication: preventing replay and relay attacks in private contact tracing. Cryptology ePrint Archive, Paper 2020/418. https://eprint.iacr.org/2020/418.
[130]
E.M.d.L. Pinto, R. Lachowski, M.E. Pellenz, M.C. Penna, R.D. Souza, A machine learning approach for detecting spoofing attacks in wireless sensor networks, 2018 IEEE 32nd International Conference on Advanced Information Networking and Applications (AINA), 2018, pp. 752–758,.
[131]
H. Pirayesh, P. Kheirkhah Sangdeh, H. Zeng, Securing ZigBee communications against constant jamming attack using neural network, IEEE Internet Things J. 8 (6) (2021) 4957–4968,.
[132]
H. Pirayesh, H. Zeng, Jamming attacks and anti-jamming strategies in wireless networks: a comprehensive survey, IEEE Commun. Surv. Tutor. 24 (2) (2022) 767–809,.
[133]
C. Qiu, M.W. Mutka, Silent whistle: effective indoor positioning with assistance from acoustic sensing on smartphones, 2017 IEEE 18th International Symposium on A World of Wireless, Mobile and Multimedia Networks (WoWMoM), 2017, pp. 1–6,.
[134]
A. Ranganathan, S. Capkun, Are we really close? Verifying proximity in wireless systems, IEEE Secur. Privacy 15 (3) (2017) 52–58,.
[135]
R. Raskar, A. Singh, S. Zimmerman, S. Kanaparti, Adding location and global context to the Google/Apple exposure notification Bluetooth API, 2020,.
[136]
P. Richter, H. Leppakoski, E.S. Lohan, Z. Yang, K. Jarvinen, O. Tkachenko, T. Schneider, Received signal strength quantization for secure indoor positioning via fingerprinting, 2018 8th International Conference on Localization and GNSS (ICL-GNSS), 2018, pp. 1–6,.
[137]
M. Ridolfi, A. Kaya, R. Berkvens, M. Weyn, W. Joseph, E.D. Poorter, Self-calibration and collaborative localization for UWB positioning systems: a survey and future research directions, ACM Comput. Surv. 54 (4) (2021),.
[138]
P. Roy, C. Chowdhury, A survey of machine learning techniques for indoor localization and navigation systems, J. Intell. Robot. Syst. 101 (3) (2021) 1–34,.
[139]
V. Sadhu, S. Zonouz, V. Sritapan, D. Pompili, CollabLoc: privacy-preserving multi-modal collaborative mobile phone localization, IEEE Trans. Mob. Comput. 20 (1) (2021) 104–116,.
[140]
N. Saeed, H. Nam, T.Y. Al-Naffouri, M.-S. Alouini, A state-of-the-art survey on multidimensional scaling-based localization techniques, IEEE Commun. Surv. Tutor. 21 (4) (2019) 3565–3583,.
[141]
H. Santo, T. Maekawa, Y. Matsushita, Device-free and privacy preserving indoor positioning using infrared retro-reflection imaging, 2017 IEEE International Conference on Pervasive Computing and Communications (PerCom), 2017, pp. 141–152,.
[142]
R. Santos, R. Leonardo, M. Barandas, D. Moreira, T. Rocha, P. Alves, J.P. Oliveira, H. Gamboa, Crowdsourcing-based fingerprinting for indoor location in multi-storey buildings, IEEE Access 9 (2021) 31143–31160,.
[143]
D. Schepers, M. Singh, A. Ranganathan, Here, there, and everywhere: security analysis of Wi-Fi fine timing measurement, Proceedings of the 14th ACM Conference on Security and Privacy in Wireless and Mobile Networks, Association for Computing Machinery, New York, NY, USA, 2021, pp. 78–89,.
[144]
M. Sen, G. Mahapatra, Secure remote patient monitoring with location-based services, in: Abraham A., Dutta P., Mandal J.K., Bhattacharya A., Dutta S. (Eds.), Emerging Technologies in Data Mining and Information Security, Springer Singapore, Singapore, 2019, pp. 715–726.
[145]
M.K. Sharma, B. Kumar Joshi, Adaptive mitigation policy to avoid resource draining attacks in wireless sensor networks, 2019 IEEE 5th International Conference for Convergence in Technology (I2CT), 2019, pp. 1–6,.
[146]
V. Sharma, M. Hussain, Mitigating replay attack in wireless sensor network through assortment of packets, in: Satapathy S.C., Prasad V.K., Rani B.P., Udgata S.K., Raju K.S. (Eds.), Proceedings of the First International Conference on Computational Intelligence and Informatics, Springer Singapore, Singapore, 2017, pp. 221–230.
[147]
W. She, Q. Liu, Z. Tian, J.-S. Chen, B. Wang, W. Liu, Blockchain trust model for malicious node detection in wireless sensor networks, IEEE Access 7 (2019) 38947–38956,.
[148]
G. Shi, Y. Ming, Survey of indoor positioning systems based on ultra-wideband (UWB) technology, in: Zeng Q.-A. (Ed.), Wireless Communications, Networking and Applications, Springer India, New Delhi, 2016, pp. 1269–1278.
[149]
X. Shi, J. Wu, To hide private position information in localization using time difference of arrival, IEEE Trans. Signal Process. 66 (18) (2018) 4946–4956,.
[150]
M. Shibuya, S. Sumikura, K. Sakurada, Privacy preserving visual SLAM, European Conference on Computer Vision, Springer, 2020, pp. 102–118.
[151]
C.-H. Shieh, Y. Xu, I.L. Ling, How location-based advertising elicits in-store purchase, J. Serv. Mark. 33 (4) (2019) 380–395,.
[152]
Y. Shoukry, K. Gatsis, A. Alanwar, G.J. Pappas, S.A. Seshia, M. Srivastava, P. Tabuada, Privacy-aware quadratic optimization using partially homomorphic encryption, 2016 IEEE 55th Conference on Decision and Control (CDC), 2016, pp. 5053–5058,.
[153]
D. Singelee, B. Preneel, Location verification using secure distance bounding protocols, IEEE International Conference on Mobile Adhoc and Sensor Systems Conference, 2005, 2005, pp. 7–840,.
[154]
M. Singh, P.M. Khilar, A range free geometric technique for localization of wireless sensor network (WSN) based on controlled communication range, Wirel. Pers. Commun. 94 (3) (2017) 1359–1385,.
[155]
Singh, M., Leu, P., Capkun, S., 2017. UWB with pulse reordering: securing ranging against relay and physical-layer attacks. Cryptology ePrint Archive, Paper 2017/1240. 10.14722/ndss.2019.23109
[156]
P. Speciale, J.L. Schönberger, S.B. Kang, S.N. Sinha, M. Pollefeys, Privacy preserving image-based localization, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019, pp. 5488–5498,.
[157]
P. Speciale, J.L. Schönberger, S. Sinha, M. Pollefeys, Privacy preserving image queries for camera localization, 2019 IEEE/CVF International Conference on Computer Vision (ICCV), 2019, pp. 1486–1496,.
[158]
M. Stocker, B. Großwindhager, C.A. Boano, K. Römer, Towards secure and scalable UWB-based positioning systems, 2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS), 2020, pp. 247–255,.
[159]
S. Subedi, J.-Y. Pyun, Practical fingerprinting localization for indoor positioning system by using beacons, J. Sens. 2017 (2017) 9742170,.
[160]
S. Subedi, J.-Y. Pyun, A survey of smartphone-based indoor positioning system using RF-based wireless technologies, Sensors 20 (24) (2020),.
[161]
Y. Sun, Q. Sun, K. Chang, The application of indoor localization systems based on the improved Kalman filtering algorithm, 2017 4th International Conference on Systems and Informatics (ICSAI), 2017, pp. 768–772,.
[162]
Tang, Q., 2020. Privacy-preserving contact tracing: current solutions and open questions. 10.48550/ARXIV.2004.06818
[163]
N.K. Thanigaivelan, E. Nigussie, R.K. Kanth, S. Virtanen, J. Isoaho, Distributed internal anomaly detection system for Internet-of-Things, 2016 13th IEEE Annual Consumer Communications Networking Conference (CCNC), 2016, pp. 319–320,.
[164]
J. Tiemann, O. Fuhr, C. Wietfeld, CELIDON: supporting first responders through 3D AoA-based UWB ad-hoc localization, 2020 16th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), 2020, pp. 20–25,.
[165]
S. Tiku, S. Pasricha, Overcoming security vulnerabilities in deep learning–based indoor localization frameworks on mobile devices, ACM Trans. Embed. Comput. Syst. 18 (6) (2019),.
[166]
N.O. Tippenhauer, H. Luecken, M. Kuhn, S. Capkun, UWB rapid-bit-exchange system for distance bounding, Proceedings of the 8th ACM Conference on Security & Privacy in Wireless and Mobile Networks, Association for Computing Machinery, New York, NY, USA, 2015,.
[167]
Y.-J. Tu, S. Piramuthu, On addressing RFID/NFC-based relay attacks: an overview, Decis. Support Syst. 129 (2020) 113194,.
[168]
P. Uphaus, B. Beringer, K. Siemens, A. Ehlers, H. Rau, Location-based services – the market: success factors and emerging trends from an exploratory approach, J. Locat. Based Serv. 15 (1) (2021) 1–26,.
[169]
R.M. Vaghefi, R.M. Buehrer, Cooperative localization in NLOS environments using semidefinite programming, IEEE Commun. Lett. 19 (8) (2015) 1382–1385,.
[170]
Vaudenay, S., 2020b. Centralized or decentralized? The contact tracing dilemma. Cryptology ePrint Archive, Paper 2020/531. https://eprint.iacr.org/2020/531.
[171]
Vaudenay, S., 2020a. Analysis of DP3T - Between Scylla and Charybdis. Cryptology ePrint Archive, Paper 2020/399. https://eprint.iacr.org/2020/399.
[172]
W. Wang, Z. Gong, J. Zhang, H. Lu, W.-S. Ku, On location privacy in fingerprinting-based indoor positioning system: An encryption approach, Proceedings of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, Association for Computing Machinery, New York, NY, USA, 2019, pp. 289–298,.
[173]
J. Wang, K. Lounis, M. Zulkernine, Security features for proximity verification, 2019 IEEE 43rd Annual Computer Software and Applications Conference (COMPSAC), vol. 2, 2019, pp. 592–597,.
[174]
C. Wang, J. Luo, X. Liu, X. He, Secure and reliable indoor localization based on multi-task collaborative learning for large-scale buildings, IEEE Internet Things J. (2021) 1,.
[175]
J.R. Ward, M. Younis, Cross-layer traffic analysis countermeasures against adaptive attackers of wireless sensor networks, Wirel. Netw. 25 (5) (2019) 2869–2887,.
[176]
L. White, P. van Basshuysen, Privacy versus public health? A reassessment of centralised and decentralised digital contact tracing, Sci. Eng. Ethics 27 (2) (2021) 23,.
[177]
S.N. Williams, C.J. Armitage, T. Tampe, K. Dienes, Public attitudes towards COVID-19 contact tracing apps: a UK-based focus group study, Health Expect. 24 (2) (2021) 377–385,.
[178]
J. Wu, Y. Nan, V. Kumar, M. Payer, D. Xu, BlueShield: detecting spoofing attacks in Bluetooth Low Energy networks, 23rd International Symposium on Research in Attacks, Intrusions and Defenses (RAID 2020), USENIX Association, San Sebastian, 2020, pp. 397–411.
[179]
P. Wu, S. Su, Z. Zuo, X. Guo, B. Sun, X. Wen, Time difference of arrival (TDOA) localization combining weighted least squares and firefly algorithm, Sensors 19 (11) (2019),.
[180]
Wu, W., Fu, S., Luo, Y., 2020b. Practical privacy protection scheme in WiFi fingerprint-based localization. Proceedings - 2020 IEEE 7th International Conference on Data Science and Advanced Analytics, DSAA 2020b. pp. 699–708.
[181]
Z. Yang, K. Järvinen, Modeling privacy in WiFi fingerprinting indoor localization, in: J. Baek, W. Susilo, J. Kim (Eds.), Provable Security, Springer International Publishing, Cham, 2018, pp. 329–346,.
[182]
Z. Yang, K. Järvinen, The death and rebirth of privacy-preserving WiFi fingerprint localization with Paillier encryption, IEEE INFOCOM 2018 - IEEE Conference on Computer Communications, 2018, pp. 1223–1231,.
[183]
Q. Yaseen, M. Aldwairi, Y. Jararweh, M. Al-Ayyoub, B. Gupta, Collusion attacks mitigation in Internet of Things: a fog based model, Multimed. Tools Appl. 77 (14) (2018) 18249–18268,.
[184]
A. Ye, Q. Chen, L. Xu, W. Wu, The flexible and privacy-preserving proximity detection in mobile social network, Future Gener. Comput. Syst. 79 (2018) 271–283,.
[185]
A. Yessembayev, D. Sarkar, F. Sikder, Detection of good and bad sensor nodes in the presence of malicious attacks and its application to data aggregation, IEEE Trans. Signal Inf. Process. Netw. 4 (3) (2018) 549–563,.
[186]
F. Yin, Z. Lin, Q. Kong, Y. Xu, D. Li, S. Theodoridis, S.R. Cui, Fedloc: federated learning framework for data-driven cooperative localization and location data processing, IEEE Open J. Signal Process. 1 (2020) 187–215,.
[187]
R. Yonetani, V.N. Boddeti, K.M. Kitani, Y. Sato, Privacy-preserving visual learning using doubly permuted homomorphic encryption, 2017 IEEE International Conference on Computer Vision (ICCV), 2017, pp. 2059–2069,.
[188]
S.G. Yoo, J.J. Barriga, Privacy-aware authentication for Wi-Fi based indoor positioning systems, in: Batten L., Kim D.S., Zhang X., Li G. (Eds.), Applications and Techniques in Information Security, Springer Singapore, Singapore, 2017, pp. 201–213.
[189]
N. Yu, S. Zhao, X. Ma, Y. Wu, R. Feng, Effective fingerprint extraction and positioning method based on crowdsourcing, IEEE Access 7 (2019) 162639–162651,.
[190]
L. Yuan, Y. Hu, Y. Li, R. Zhang, Y. Zhang, T. Hedgpeth, Secure RSS-fingerprint-based indoor positioning: attacks and countermeasures, 2018 IEEE Conference on Communications and Network Security (CNS), 2018, pp. 1–9,.
[191]
F. Zafari, A. Gkelias, K.K. Leung, A survey of indoor localization systems and technologies, IEEE Commun. Surv. Tutor. 21 (3) (2019) 2568–2599,.
[192]
Z. Zhang, X. Guo, Y. Lin, Trust management method of D2D communication based on RF fingerprint identification, IEEE Access 6 (2018) 66082–66087,.
[193]
X. Zhang, F. He, Q. Chen, X. Jiang, J. Bao, T. Ren, X. Du, A differentially private indoor localization scheme with fusion of WiFi and Bluetooth fingerprints in edge computing, Neural Comput. Appl. 34 (6) (2022) 4111–4132,.
[194]
Z. Zhang, A. Mehmood, L. Shu, Z. Huo, Y. Zhang, M. Mukherjee, A survey on fault diagnosis in wireless sensor networks, IEEE Access 6 (2018) 11349–11364,.
[195]
Y. Zhang, J. Weng, R. Dey, X. Fu, Bluetooth Low Energy (BLE) Security and Privacy, Springer International Publishing, Cham, 2020, pp. 123–134.
[196]
G. Zhang, A. Zhang, P. Zhao, J. Sun, Lightweight privacy-preserving scheme in Wi-Fi fingerprint-based indoor localization, IEEE Syst. J. 14 (3) (2020) 4638–4647,.
[197]
J. Zhao, N. Frumkin, J. Konrad, P. Ishwar, Privacy-preserving indoor localization via active scene illumination, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2018.
[198]
P. Zhao, H. Jiang, J.C.S. Lui, C. Wang, F. Zeng, F. Xiao, Z. Li, P3-LOC: a privacy-preserving paradigm-driven framework for indoor localization, IEEE/ACM Trans. Netw. 26 (6) (2018) 2856–2869,.
[199]
W. Zhao, L. Xu, B. Qi, J. Hu, T. Wang, T. Runge, Vivid: augmenting vision-based indoor navigation system with edge computing, IEEE Access 8 (2020) 42909–42923,.
[200]
H. Zhu, F. Wang, R. Lu, F. Liu, G. Fu, H. Li, Efficient and privacy-preserving proximity detection schemes for social applications, IEEE Internet Things J. 5 (4) (2018) 2947–2957,.
[201]
Y. Zhuang, L. Hua, L. Qi, J. Yang, P. Cao, Y. Cao, Y. Wu, J. Thompson, H. Haas, A Survey of Positioning Systems Using Visible LED Lights, IEEE Commun. Surv. Tutor. 20 (3) (2018) 1963–1988,.
Recommendations
Indoor Localization Techniques Based on UWB Technology
Ubiquitous NetworkingAbstractIndoor positioning attracts a lot of attention because people spend their maximum time indoors. As well as the loss of GPS signal power through walls, which requires the integration of other approaches to locate passengers indoors. With the ...
Impact of Radio Map Size on Indoor Localization Accuracy
Computational Science and Its Applications – ICCSA 2022AbstractNowadays Indoor Positioning Systems (IPS) are attracting attention in literature because of Global Positioning System (GPS) challenge to track and navigate indoors. These IPSs intend to provide information about a wireless object’s current ...
MIMO CSI-based Super-resolution AoA Estimation for Wi-Fi Indoor Localization
ICMLC '20: Proceedings of the 2020 12th International Conference on Machine Learning and ComputingIndoor localization technology has always been a research hotspot in industry and academia. Indoor localization research using channel state information (CSI) of Wi-Fi signals has also received more and more attention. The existing Angle of Arrival (AoA)...
Comments
Please enable JavaScript to view thecomments powered by Disqus.Information & Contributors
Information
Published In
Copyright © 2023.
Publisher
Elsevier Advanced Technology Publications
United Kingdom
Publication History
Published: 01 August 2023
Author Tags
Author Tags
Qualifiers
- Research-article
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 0Total Downloads
- Downloads (Last 12 months)0
- Downloads (Last 6 weeks)0
Reflects downloads up to 26 Jan 2025