{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T19:29:11Z","timestamp":1750188551900,"version":"3.37.3"},"reference-count":31,"publisher":"Springer Science and Business Media LLC","issue":"1-2","license":[{"start":{"date-parts":[[2020,9,18]],"date-time":"2020-09-18T00:00:00Z","timestamp":1600387200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2020,9,18]],"date-time":"2020-09-18T00:00:00Z","timestamp":1600387200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100000038","name":"Natural Sciences and Engineering Research Council of Canada","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000038","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Ann. Telecommun."],"published-print":{"date-parts":[[2021,2]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>In modern wireless systems such as ZigBee, sensitive information which is produced by the network is transmitted through different wired or wireless nodes. Providing the requisites of communication between diverse communication system types, such as mobiles, laptops, and desktop computers, does increase the risk of being attacked by outside nodes. Malicious (or unintentional) threats, such as trying to obtain unauthorized accessibility to the network, increase the requirements of data security against the rogue devices trying to tamper with the identity of authorized devices. In such manner, focusing on Radio Frequency Distinct Native Attributes (RF-DNA) of features extracted from physical layer responses (referred to as preambles) of ZigBee devices, a dataset of distinguishable features of all devices can be produced which can be exploited for the detection and rejection of spoofing\/rogue devices. Through this procedure, distinction of devices manufactured by the different\/same producer(s) can be realized resulting in an improvement of classification system accuracy. The two most challenging problems in initiating RF-DNA are (1) the mechanism of features extraction in the generation of a dataset in the most effective way for model classification and (2) the design of an efficient model for device discrimination of spoofing\/rogue devices. In this paper, we analyze the physical layer features of ZigBee devices and present methods based on deep learning algorithms to achieve high classification accuracy, based on wavelet decomposition and on the autoencoder representation of the original dataset.<\/jats:p>","DOI":"10.1007\/s12243-020-00796-x","type":"journal-article","created":{"date-parts":[[2020,9,18]],"date-time":"2020-09-18T11:36:43Z","timestamp":1600429003000},"page":"27-42","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Rogue device discrimination in ZigBee networks using wavelet transform and autoencoders"],"prefix":"10.1007","volume":"76","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0662-2666","authenticated-orcid":false,"given":"Mohammad Amin","family":"Haji Bagheri Fard","sequence":"first","affiliation":[]},{"given":"Jean-Yves","family":"Chouinard","sequence":"additional","affiliation":[]},{"given":"Bernard","family":"Lebel","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,9,18]]},"reference":[{"key":"796_CR1","unstructured":"Arana P (2006) Benefits and vulnerabilities of Wi-Fi protected access 2 (WPA2). INFS 612: Principles and Practices of Communication Networks. George Mason University"},{"key":"796_CR2","unstructured":"Wi-Fi Alliance. WPA3 specification version 1.0, 2019"},{"key":"796_CR3","doi-asserted-by":"crossref","unstructured":"Benkic K, Planinsic P, Cucej Z (2007) Custom wireless sensor network based on ZigBee. In: ELMAR, 2007. IEEE, pp 259\u2013262","DOI":"10.1109\/ELMAR.2007.4418844"},{"key":"796_CR4","doi-asserted-by":"crossref","unstructured":"Dubendorfer CK, Ramsey BW, Temple MA (2012) An RF-DNA verification process for ZigBee networks. In: 2012 Military Communications Conference (MILCOM 2012). IEEE, pp 1\u20136","DOI":"10.1109\/MILCOM.2012.6415804"},{"issue":"1","key":"796_CR5","doi-asserted-by":"publisher","first-page":"14","DOI":"10.1109\/TIFS.2011.2160170","volume":"7","author":"WE Cobb","year":"2011","unstructured":"Cobb WE, Laspe ED, Baldwin RO, Temple MA, Kim YC (2011) Intrinsic physical-layer authentication of integrated circuits. IEEE Trans Inform Forensics Secur 7(1):14\u201324","journal-title":"IEEE Trans Inform Forensics Secur"},{"key":"796_CR6","unstructured":"Ramsey BW (2014) Improved Wireless Security through Physical Layer Protocol Manipulation and Radio Frequency Fingerprinting. Ph.D. dissertation, Air Force Institute of Technology, Wright-Patterson Graduate School of Engineering and Management"},{"key":"796_CR7","doi-asserted-by":"crossref","unstructured":"Reising DR, Temple MA (2012) WiMAX mobile subscriber verification using Gabor-based RF-DNA fingerprints. In: 2012 IEEE International Conference on Communications (ICC). IEEE, pp 1005\u20131010","DOI":"10.1109\/ICC.2012.6364039"},{"issue":"6","key":"796_CR8","doi-asserted-by":"publisher","first-page":"1180","DOI":"10.1109\/TIFS.2015.2400426","volume":"10","author":"DR Reising","year":"2015","unstructured":"Reising DR, Temple MA, Jackson JA (2015) Authorized and rogue device discrimination using dimensionally reduced RF-DNA fingerprints. IEEE Trans Inform Forensics Secur 10(6):1180\u20131192","journal-title":"IEEE Trans Inform Forensics Secur"},{"key":"796_CR9","doi-asserted-by":"crossref","unstructured":"Patel H (2015) Non-parametric feature generation for RF-fingerprinting on ZigBee devices. In: 2015 IEEE Symposium on Computational Intelligence for Security and Defense Applications (CISDA). IEEE, pp 1\u20135","DOI":"10.1109\/CISDA.2015.7208645"},{"issue":"8","key":"796_CR10","doi-asserted-by":"publisher","first-page":"1862","DOI":"10.1109\/TIFS.2016.2561902","volume":"11","author":"TJ Bihl","year":"2016","unstructured":"Bihl TJ, Bauer KW, Temple MA (2016) Feature selection for RF fingerprinting with multiple discriminant analysis and using ZigBee device emissions. IEEE Trans Inform Forensics Secur 11(8):1862\u20131874","journal-title":"IEEE Trans Inform Forensics Secur"},{"key":"796_CR11","doi-asserted-by":"crossref","unstructured":"Dubendorfer C, Ramsey B, Temple M (2013) Zigbee device verification for securing industrial control and building automation systems. In: International Conference on Critical Infrastructure Protection. Springer, Berlin, pp 47\u201362","DOI":"10.1007\/978-3-642-45330-4_4"},{"issue":"1","key":"796_CR12","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1109\/CJECE.2007.364330","volume":"32","author":"O Ureten","year":"2007","unstructured":"Ureten O, Serinken N (2007) Wireless security through RF fingerprinting. Can J Electr Comput Eng 32(1):27\u201333","journal-title":"Can J Electr Comput Eng"},{"key":"796_CR13","doi-asserted-by":"crossref","unstructured":"O\u2019Shea TJ, Corgan J, Clancy TC (2016) Convolutional radio modulation recognition networks. In: International Conference on Engineering Applications of Neural Networks. Springer, Berlin, pp 213\u2013226","DOI":"10.1007\/978-3-319-44188-7_16"},{"key":"796_CR14","doi-asserted-by":"crossref","unstructured":"Schmidt M, Block D, Meier U (2017) Wireless interference identification with convolutional neural networks. In: 2017 IEEE 15th International Conference on Industrial Informatics (INDIN). IEEE, pp 180\u2013185","DOI":"10.1109\/INDIN.2017.8104767"},{"key":"796_CR15","doi-asserted-by":"crossref","unstructured":"Yuan Y, Huang Z, Wang F, Wang X (2015) Radio specific emitter identification based on nonlinear characteristics of signal. In: 2015 IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom). IEEE, pp 77\u201381","DOI":"10.1109\/BlackSeaCom.2015.7185090"},{"key":"796_CR16","doi-asserted-by":"crossref","unstructured":"Zhao C, Wu X, Huang L, Yao Y, Chang Yao-Chung (2014) Compressed sensing based fingerprint identification for wireless transmitters. The Scientific World Journal, 2014","DOI":"10.1155\/2014\/473178"},{"issue":"1","key":"796_CR17","doi-asserted-by":"publisher","first-page":"160","DOI":"10.1109\/JSTSP.2018.2796446","volume":"12","author":"K Merchant","year":"2018","unstructured":"Merchant K, Revay S, Stantchev G, Nousain B (2018) Deep learning for RF device fingerprinting in cognitive communication networks. IEEE Journal of Selected Topics in Signal Processing 12(1):160\u2013167","journal-title":"IEEE Journal of Selected Topics in Signal Processing"},{"issue":"13","key":"796_CR18","doi-asserted-by":"publisher","first-page":"2404","DOI":"10.1049\/iet-com.2013.0865","volume":"8","author":"Y Yuan","year":"2014","unstructured":"Yuan Y, Huang Z, Wu H, Wang X (2014) Specific emitter identification based on Hilbert\u2013Huang transform-based time\u2013frequency\u2013energy distribution features. IET Commun 8(13):2404\u20132412","journal-title":"IET Commun"},{"issue":"12","key":"796_CR19","doi-asserted-by":"publisher","first-page":"4843","DOI":"10.1109\/TIE.2011.2179276","volume":"59","author":"C Bertoncini","year":"2012","unstructured":"Bertoncini C, Rudd K, Nousain B, Hinders M (2012) Wavelet fingerprinting of radio-frequency identification (RFID) tags. IEEE Trans Ind Electron 59(12):4843\u20134850","journal-title":"IEEE Trans Ind Electron"},{"key":"796_CR20","doi-asserted-by":"crossref","unstructured":"Benvenuto N, Piazza F, Uncini A (1993) A neural network approach to data predistortion with memory in digital radio systems. In: Proceedings of ICC\u201993-IEEE International Conference on Communications, vol 1. IEEE, pp 232\u2013236","DOI":"10.1109\/ICC.1993.397263"},{"issue":"4","key":"796_CR21","doi-asserted-by":"publisher","first-page":"913","DOI":"10.1109\/TMTT.2010.2098041","volume":"59","author":"F Mkadem","year":"2011","unstructured":"Mkadem F, Boumaiza S (2011) Physically inspired neural network model for RF power amplifier behavioral modeling and digital predistortion. IEEE Transactions on Microwave Theory and Techniques 59 (4):913\u2013923","journal-title":"IEEE Transactions on Microwave Theory and Techniques"},{"key":"796_CR22","doi-asserted-by":"crossref","unstructured":"Shi G, Li K (2017) Fundamentals of ZigBee and WiFi. In: Signal interference in WiFi and ZigBee networks, chapter 2. Springer, Cham, pp 9\u201327","DOI":"10.1007\/978-3-319-47806-7_2"},{"issue":"12","key":"796_CR23","doi-asserted-by":"publisher","first-page":"2091","DOI":"10.1109\/29.45554","volume":"37","author":"SG Mallat","year":"1989","unstructured":"Mallat SG, et al. (1989) Multifrequency channel decompositions of images and wavelet models. IEEE Trans Acoustics, Speech, and Signal Processing 37(12):2091\u20132110","journal-title":"IEEE Trans Acoustics, Speech, and Signal Processing"},{"key":"796_CR24","doi-asserted-by":"crossref","unstructured":"Nievergelt Y (1999) Wavelets made easy. Birkh\u00e4user","DOI":"10.1007\/978-1-4612-0573-9"},{"key":"796_CR25","doi-asserted-by":"crossref","unstructured":"Boehmke B, Greenwell BM (2019) Hands-on machine learning with R. CRC Press","DOI":"10.1201\/9780367816377"},{"key":"796_CR26","doi-asserted-by":"crossref","unstructured":"Meng Q, Catchpoole D, Skillicom D, Kennedy PJ (2017) Relational autoencoder for feature extraction. In: 2017 International Joint Conference on Neural Networks (IJCNN). IEEE, pp 364\u2013371","DOI":"10.1109\/IJCNN.2017.7965877"},{"key":"796_CR27","unstructured":"Cao X (2015) A practical theory for designing very deep convolutional neural networks. Technical Report"},{"key":"796_CR28","volume-title":"Introduction to machine learning","author":"E Alpaydin","year":"2014","unstructured":"Alpaydin E (2014) Introduction to machine learning, 2nd edn. MIT Press, Cambridge","edition":"2nd edn."},{"key":"796_CR29","volume-title":"Deep learning","author":"I Goodfellow","year":"2016","unstructured":"Goodfellow I, Bengio Y, Courville A (2016) Deep learning. MIT Press, Cambridge"},{"key":"796_CR30","unstructured":"Kingma DP, Ba J (2014) Adam: a method for stochastic optimization. arXiv:1412.6980"},{"key":"796_CR31","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1016\/j.ijcip.2014.11.002","volume":"8","author":"BW Ramsey","year":"2015","unstructured":"Ramsey BW, Stubbs TD, Mullins BE, Temple MA, Buckner MA (2015) Wireless infrastructure protection using low-cost radio frequency fingerprinting receivers. Int J Critical Infrastruct Protect 8:27\u201339","journal-title":"Int J Critical Infrastruct Protect"}],"container-title":["Annals of Telecommunications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12243-020-00796-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s12243-020-00796-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12243-020-00796-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,9,17]],"date-time":"2021-09-17T23:15:34Z","timestamp":1631920534000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s12243-020-00796-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,9,18]]},"references-count":31,"journal-issue":{"issue":"1-2","published-print":{"date-parts":[[2021,2]]}},"alternative-id":["796"],"URL":"https:\/\/doi.org\/10.1007\/s12243-020-00796-x","relation":{},"ISSN":["0003-4347","1958-9395"],"issn-type":[{"type":"print","value":"0003-4347"},{"type":"electronic","value":"1958-9395"}],"subject":[],"published":{"date-parts":[[2020,9,18]]},"assertion":[{"value":"12 July 2019","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 August 2020","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 September 2020","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}