Abstract
The evolution of wireless communications and pervasive computing is transforming current physical spaces into real smart environments. These emerging scenarios are expected to be composed by a potentially huge amount of heterogeneous smart objects which can be remotely accessed by users via their mobile devices anytime, anywhere. In this paper, we propose a distributed location-aware access control mechanism and its application in the smart building context. Our approach is based on an access control engine embedded into smart objects, which are responsible to make authorization decisions by considering both user location data and access credentials. User location data are estimated using a novel indoor localization system based on magnetic field data sent by user through her personal phone. This localization system implements a combination of soft computing techniques over the data collected by smartphones. Therefore, our location-aware access control mechanism does not require any intermediate entity, providing the benefits of a decentralized approach for smart environments. From the results obtained, we can consider our proposal as a promising approach to tackle the challenging security requirements of typical pervasive environments.
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References
Altun K, Barshan B (2010) Human activity recognition using inertial/magnetic sensor units. In: Human behavior understanding, pp 38–51. Springer, Berlin
Andreu J, Angelov P (2010) Real-time human activity recognition from wireless sensors using evolving fuzzy systems. In: 2010 IEEE international conference on fuzzy systems (FUZZ). IEEE, New York, pp 1–8
Angermann M, Frassl M, Doniec M, Julian BJ, Robertson P (2012) Characterization of the indoor magnetic field for applications in localization and mapping. In: 2012 International conference on indoor positioning and indoor navigation (IPIN). IEEE, New York, pp 1–9
Ardagna CA, Cremonini M, Damiani E, di Vimercati SDC, Samarati P (2006) Supporting location-based conditions in access control policies. In: Proceedings of the 2006 ACM symposium on information, computer and communications security. ACM, New York, pp 212–222
Atallah L, Lo B, King R, Yang GZ (2010) Sensor placement for activity detection using wearable accelerometers. In: 2010 International conference on body sensor networks (BSN). IEEE, New York, pp 24–29
Atallah L, Lo B, King R, Yang GZ (2011) Sensor positioning for activity recognition using wearable accelerometers. IEEE Trans Biomed Circuits Syst 5(4):320–329
Atzori L, Iera A, Morabito G (2010) The internet of things: a survey. Comput Netw 54(15):2787–2805
Bao L, Intille SS (2004) Activity recognition from user-annotated acceleration data. In: Pervasive computing. Springer, Berlin, pp 1–17
Boles LC, Lohmann KJ (2003) True navigation and magnetic maps in spiny lobsters. Nature 421(6918):60–63
Breiman L (1996) Bagging predictors. Mach Learn 24(2):123–140
Breiman L (2001) Random forests. Mach Learn 45(1):5–32
Covington MJ, Long W, Srinivasan S, Dev AK, Ahamad M, Abowd GD (2001) Securing context-aware applications using environment roles. In: Proceedings of the sixth ACM symposium on access control models and technologies. ACM, New York, pp 10–20
Denning DE, MacDoran PF (1996) Location-based authentication: grounding cyberspace for better security. Comput Fraud Secur 1996(2):12–16
Ebinger P, Ramos JLH, Kikiras P, Lischka M, Wiesmaier A (2013) Privacy in smart metering ecosystems. In: Smart grid security. Springer, Berlin, pp 120–131
Ferraiolo D, Cugini J, Kuhn R (1995) Role-based access control (RBAC): features and motivations. In: Proceedings of 11th annual computer security application conference, pp 241–48
Friedman J, Hastie T, Tibshirani R (2000) Additive logistic regression: a statistical view of boosting (with discussion and a rejoinder by the authors). Ann Stat 28(2):337–407
Gao C, Yu Z, Wei Y, Russell S, Guan Y (2009) A statistical indoor localization method for supporting location-based access control. Mob Netw Appl 14(2):253–263
Garcia-Valverde T, Garcia-Sola A, Hagras H, Dooley JA, Callaghan V, Botia JA (2013) A fuzzy logic-based system for indoor localization using WiFi in ambient intelligent environments. IEEE Trans Fuzzy Syst 21(4):702–718
Gozick B, Subbu KP, Dantu R, Maeshiro T (2011) Magnetic maps for indoor navigation. IEEE Trans Instrum Meas 60(12):3883–3891
Gupta SK, Mukheriee T, Venkatasubramanian K, Taylor T (2006) Proximity based access control in smart-emergency departments. In: Fourth annual IEEE international conference on pervasive computing and communications workshops, 2006. PerCom Workshops 2006. IEEE, New York
Győrbíró N, Fábián Á, Hományi G (2009) An activity recognition system for mobile phones. Mob Netw Appl 14(1):82–91
Haverinen J, Kemppainen A (2009) Global indoor self-localization based on the ambient magnetic field. Robot Auton Syst 57(10):1028–1035
Hernández-Ramos J et al (2013) Distributed capability-based access control for the internet of things. J Internet Serv Inf Secur 3(3/4): 1–16
Kanungo T, Mount DM, Netanyahu NS, Piatko CD, Silverman R, Wu AY (2002) An efficient k-means clustering algorithm: Analysis and implementation. IEEE Trans Pattern Anal Mach Intell 24(7):881–892
Katzakis N, Hori M (2009) Mobile phones as 3-dof controllers: a comparative study. In: DASC’09. Eighth IEEE international conference on dependable, autonomic and secure computing, 2009. IEEE, New York, pp 345–349
Kim JE, Boulos G, Yackovich J, Barth T, Beckel C, Mosse D (2012) Seamless integration of heterogeneous devices and access control in smart homes. In: 2012 8th International conference on intelligent environments (IE). IEEE, New York, pp 206–213
Kunze K, Lukowicz P, Junker H, Tröster G (2005) Where am I: Recognizing on-body positions of wearable sensors. In: Location-and context-awareness, pp 264–275 Springer, Berlin
Lane ND, Miluzzo E, Lu H, Peebles D, Choudhury T, Campbell AT (2010) A survey of mobile phone sensing. IEEE Commun Mag 48(9):140–150
Li B, Gallagher T, Dempster AG, Rizos C (2012) How feasible is the use of magnetic field alone for indoor positioning? In: 2012 International conference on indoor positioning and indoor navigation (IPIN). IEEE, New York, pp 1–9
Luna F, Estébanez C, León C, Chaves-González JM, Nebro AJ, Aler R, Segura C, Vega-Rodríguez MA, Alba E, Valls JM et al (2011) Optimization algorithms for large-scale real-world instances of the frequency assignment problem. Soft Comput 15(5):975–990
Luoh L (2014) ZigBee-based intelligent indoor positioning system soft computing. Soft Comput 18:443–456
McGregor A, Hall M, Lorier P, Brunskill J (2004) Flow clustering using machine learning techniques. In: Passive and active network measurement. Springer, Berlin, pp 205–214
Melville P, Mooney RJ (2005) Creating diversity in ensembles using artificial data. Inf Fusion 6(1):99–111
Misra P, Enge P (1999) Special issue on global positioning system. Proc IEEE 87(1):3–15
Moses T et al (2005) Extensible access control markup language (XACML) version 2.0. Oasis Standard 200502
Mulligan G (2007) The 6lowpan architecture. In: Proceedings of the 4th workshop on embedded networked sensors. ACM, New York, pp 78–82
Ni L, Liu Y, Lau Y, Patil A (2004) LANDMARC: indoor location sensing using active RFID. Wirel Netw 10(6):701–710
Ofstad A, Nicholas E, Szcodronski R, Choudhury RR (2008) AAMPL: accelerometer augmented mobile phone localization. In: Proceedings of the first ACM international workshop on mobile entity localization and tracking in GPS-less environments. ACM, New York, pp 13–18
Oliveira LM, Rodrigues JJ, Sousa AF, Lloret J (2013a) Denial of service mitigation approach for IPv6-enabled smart object networks. Concurr Comput Pract Exp 25(1):129–142
Oliveira LM, Rodrigues JJ, de Sousa AF, Lloret J (2013b) A network access control framework for 6LoWPAN networks. Sensors 13(1):1210–1230
Ravi N, Dandekar N, Mysore P, Littman ML (2005) Activity recognition from accelerometer data. AAAI, Pittsburgh, pp 1541–1546
Rodriguez MD, Favela J, Martínez EA, Muñoz MA (2004) Location-aware access to hospital information and services. IEEE Trans Inf Technol Biomed 8(4):448–455
Shelby Z, Hartke K, Bormann C (2013) Constrained application protocol (CoAP). Constrained resources (CoRE) working group, internet engineering task force (IETF), work in progress, draft-ietf-core-coap-18. http://tools.ietf.org/html/draft-ietf-core-coap-18
Shi Y, Shi Y, Liu J (2011) A rotation based method for detecting on-body positions of mobile devices. In: Proceedings of the 13th international conference on ubiquitous computing. ACM, New York, pp 559–560
Simon H (1999) Neural networks: a comprehensive foundation. Prentice Hall, Upper Saddle River
Sun M, Hill J (1993) A method for measuring mechanical work and work efficiency during human activities. J Biomech 26(3):229–241
Wang Y, Zhao J, Fukushima T (2009) Lock: a highly accurate, easy-to-use location-based access control system. In: Location and context awareness. Springer, Berlin, pp 254–270
Weiser M (1991) The computer for the 21st century. Sci Am 265(3):94–104
Xin-fang Z, Ming-wei F, Jun-jun W (2011) An indoor location-based access control system by RFID. In: 2011 IEEE international conference on cyber technology in automation, control, and intelligent systems (CYBER). IEEE, New York, pp 43–47
Yang J (2009) Toward physical activity diary: motion recognition using simple acceleration features with mobile phones. In: Proceedings of the 1st international workshop on interactive multimedia for consumer electronics. ACM, New York, pp 1–10
Yuan E, Tong J (2005) Attributed based access control (ABAC) for web services. In: Proceedings of the 12th IEEE international conference on web services (ICWS), Orlando, USA. IEEE, New York
Zadeh LA (1997) What is soft computing? Soft Comput 1(1):1–1s
Acknowledgments
This work has been sponsored by European Commission through the FP7-IoT6-288455 and FP7-SOCIOTAL-609112 EU Projects, and the Spanish Seneca Foundation by means of the Excellence Researching Group Program (04552/GERM/06) and the FPI program (Grant 15493/FPI/10).
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Communicated by A. Castiglione.
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Hernández, J.L., Moreno, M.V., Jara, A.J. et al. A soft computing based location-aware access control for smart buildings. Soft Comput 18, 1659–1674 (2014). https://doi.org/10.1007/s00500-014-1278-9
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DOI: https://doi.org/10.1007/s00500-014-1278-9