{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T22:57:24Z","timestamp":1774047444098,"version":"3.50.1"},"reference-count":20,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2020,10,19]],"date-time":"2020-10-19T00:00:00Z","timestamp":1603065600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2020,10,19]],"date-time":"2020-10-19T00:00:00Z","timestamp":1603065600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100001809","name":"The National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["61571063"],"award-info":[{"award-number":["61571063"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Natural Science Foundation of Beijing Municipality","award":["3182028"],"award-info":[{"award-number":["3182028"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Wireless Com Network"],"published-print":{"date-parts":[[2020,12]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>The electromagnetic radiation of electronic equipment carries information and can cause information leakage, which poses a serious threat to the security system; especially the information leakage caused by encryption or other important equipment will have more serious consequences. In the past decade or so, the attack technology and means for the physical layer have developed rapidly. And system designers have no effective method for this situation to eliminate or defend against threats with an absolute level of security. In recent years, device identification has been developed and improved as a physical-level technology to improve the security of integrated circuit (IC)-based multifactor authentication systems. Device identification tasks (including device identification and verification) are accomplished by monitoring and exploiting the characteristics of the IC\u2019s unintentional electromagnetic radiation, without requiring any modification and process to hardware devices, thereby providing versatility and adapting existing hardware devices. Device identification based on deep residual networks and radio frequency is a technology applicable to the physical layer, which can improve the security of integrated circuit (IC)-based multifactor authentication systems. Device identification tasks (identification and verification) are accomplished by passively monitoring and utilizing the inherent properties of IC unintended RF transmissions without requiring any modifications to the analysis equipment. After the device performs a series of operations, the device is classified and identified using a deep residual neural network. The gradient descent method is used to adjust the network parameters, the batch training method is used to speed up the parameter tuning speed, the parameter regularization is used to improve the generalization, and finally, the Softmax classifier is used for classification. In the end, 28 chips of 4 models can be accurately identified into 4 categories, then the individual chips in each category can be identified, and finally 28 chips can be accurately identified, and the verification accuracy reached 100%. Therefore, the identification of radio frequency equipment based on deep residual network is very suitable as a countermeasure for implementing the device cloning technology and is expected to be related to various security issues.<\/jats:p>","DOI":"10.1186\/s13638-020-01808-z","type":"journal-article","created":{"date-parts":[[2020,10,19]],"date-time":"2020-10-19T13:04:25Z","timestamp":1603112665000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Electromagnetic radiation-based IC device identification and verification using deep learning"],"prefix":"10.1186","volume":"2020","author":[{"given":"Hong-xin","family":"Zhang","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0654-8929","authenticated-orcid":false,"given":"Jia","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Jun","family":"Xu","sequence":"additional","affiliation":[]},{"given":"Fan","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Xiao-tong","family":"Cui","sequence":"additional","affiliation":[]},{"given":"Shao-fei","family":"Sun","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,10,19]]},"reference":[{"issue":"01","key":"1808_CR1","first-page":"61","volume":"20","author":"D Hu","year":"2020","unstructured":"D. Hu, D.T. Ma, H. Gong, Z. Ma, A physical layer security authentication method based on PUF [J]. Information Network Security 20(01), 61\u201366 (2020)","journal-title":"Information Network Security"},{"key":"1808_CR2","first-page":"250","volume":"14","author":"WJ Li","year":"2017","unstructured":"W.J. Li, AES energy analysis attack under simulated power collection platform[J]. Shandong Industrial Technology 14, 250\u2013251 (2017)","journal-title":"Shandong Industrial Technology"},{"issue":"03","key":"1808_CR3","first-page":"383","volume":"6","author":"D Li","year":"2019","unstructured":"D. Li, G.F. Dai, H.G. Hu, N.H. Yu, Side channel attacks against real RFID tags [J]. Journal of Cryptography 6(03), 383\u2013394 (2019)","journal-title":"Journal of Cryptography"},{"key":"1808_CR4","doi-asserted-by":"crossref","unstructured":"William E. Cobb, Eric D. Laspe, Rusty O. Baldwin, intrinsic physical-layer authentication of integrated circuits IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, VOL. 7, NO. 1, FEBRUARY 2012","DOI":"10.1109\/TIFS.2011.2160170"},{"issue":"1","key":"1808_CR5","doi-asserted-by":"publisher","first-page":"4","DOI":"10.1109\/TCSVT.2003.818349","volume":"14","author":"A Jain","year":"2004","unstructured":"A. Jain, A. Ross, S. Prabhakar, An introduction to biometric recognition. IEEE Trans. Circuits Syst. Video Technol. 14(1), 4\u201320 (2004)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"1808_CR6","unstructured":"Federal Communications Commission (FCC), Code of Federal Regulations, Title 47 2009"},{"key":"1808_CR7","doi-asserted-by":"crossref","unstructured":"C. Paar, T. Eisenbarth, M. Kasper, T. Kasper, and A. Moradi, \u201cKeeloq and side-channel analysis-evolution of an attack,\u201d in FDTC, L. Breveg- lieri, S. Gueron, I. Koren, D. Naccache, and J.-P. Seifert, Eds. Los Alamitos, CA: IEEE Comput. Soc. Press, 2009, pp. 65\u201369.","DOI":"10.1109\/FDTC.2009.44"},{"key":"1808_CR8","volume-title":"Deep learning-based classification and anomaly detection of side-channel signals [C]\/\/ Cyber Sensing 2018","author":"X Wang","year":"2018","unstructured":"Wang X, Zhou Q , Harer J , et al. Deep learning-based classification and anomaly detection of side-channel signals [C]\/\/ Cyber Sensing 2018. 2018."},{"key":"1808_CR9","first-page":"534","volume":"18","author":"YJ Xiao","year":"2017","unstructured":"Y.J. Xiao, W.Y. Xu, Z.H. Jia, et al., NIPAD: a non-invasive power-based anomaly detection scheme for programmable logic controllers [J]. Frontiers of Information and Electronic Engineering: English 18, 534 (2017)","journal-title":"Frontiers of Information and Electronic Engineering: English"},{"key":"1808_CR10","doi-asserted-by":"crossref","unstructured":"W. Cobb, E. Garcia, M. Temple, R. Baldwin, and Y. Kim, \u201cPhysical layer identification of embedded devices using RF-DNA finger- printing,\u201d in Proc. 2010 Mil. Commun. (MILCOM2010) Conf., 2010, pp. 682\u2013687.","DOI":"10.1109\/MILCOM.2010.5680487"},{"key":"1808_CR11","volume-title":"Secure integrated circuits and systems, I. Ver- bauwhede, Ed","author":"R Maes","year":"2010","unstructured":"R. Maes, P. Tuyls, Secure integrated circuits and systems, I. Ver- bauwhede, Ed (Springer, New York, 2010)"},{"issue":"5589","key":"1808_CR12","doi-asserted-by":"publisher","first-page":"2026","DOI":"10.1126\/science.1074376","volume":"297","author":"R Pappu","year":"2002","unstructured":"R. Pappu, B. Recht, J. Taylor, N. Gershenfeld, Physical one-way functions. Science 297(5589), 2026\u20132030 (2002)","journal-title":"Science"},{"key":"1808_CR13","doi-asserted-by":"crossref","unstructured":"G. DeJean and D. Kirovski, \u201cRF-DNA: Radio-frequency certificates of authenticity,\u201d in CHES, ser. Lecture Notes in Computer Science, P. Paillier and I. Verbauwhede, Eds. New York: Springer, 2007, vol. 4727, pp. 346\u2013363.","DOI":"10.1007\/978-3-540-74735-2_24"},{"key":"1808_CR14","unstructured":"B. Danev, T. Heydt-Benjamin, and S. \u010capkun, USENIX Association, \u201cPhysical-layer identification of RFID devices,\u201d in Proc. 18th Conf. USENIX Security Symp., 2009, pp. 199\u2013214."},{"issue":"02","key":"1808_CR15","first-page":"48","volume":"19","author":"J Zhang","year":"2019","unstructured":"J. Zhang, Y. Xu, Y.T. Mei, A PUF-based lightweight RFID security authentication protocol for low-cost tags [J]. Journal of Anhui Vocational College of Water Resources and Hydropower 19(02), 48\u201351 (2019)","journal-title":"Journal of Anhui Vocational College of Water Resources and Hydropower"},{"key":"1808_CR16","doi-asserted-by":"publisher","first-page":"8","DOI":"10.1002\/dac.3935","volume":"32","author":"MH Ameri","year":"2019","unstructured":"M.H. Ameri, M. Delavar, J. Mohajeri, Provably secure and efficient PUF-based broadcast authentication schemes for smart grid applications [J]. Int. J. Commun. Syst. 32, 8 (2019)","journal-title":"Int. J. Commun. Syst."},{"issue":"1","key":"1808_CR17","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s13638-018-1318-8","volume":"2019","author":"XL Wang","year":"2019","unstructured":"X.L. Wang, Y.F. Zhang, H.X. Zhang, X.F. Wei, G.Y. Wang, Identification and authentication for wireless transmission security based on RF-DNA fingerprint. EURASIP J. Wirel. Commun. Netw. 2019(1), 1\u201312 (2019)","journal-title":"EURASIP J. Wirel. Commun. Netw."},{"key":"1808_CR18","doi-asserted-by":"crossref","unstructured":"Zhao B , Zhu L , Ma Z , et al. Object detection based on multi-channel deep CNN [C]\/\/ 2018 14th International Conference on Computational Intelligence and Security (CIS). IEEE Computer Society, 2018.","DOI":"10.1109\/CIS2018.2018.00043"},{"key":"1808_CR19","volume-title":"Reserch on bioelectrical signal recognition for smarter healthcare [D]","author":"L Duan","year":"2018","unstructured":"L. Duan, Reserch on bioelectrical signal recognition for smarter healthcare [D] (Beijing University of Posts and Telecommunications, Beijing, 2018)"},{"key":"1808_CR20","unstructured":"F. Jiang, Y. Fu, B.B. Gupta, et al., Deep learning based multi-channel intelligent attack detection for data security [J]. IEEE Transactions on Sustainable Computing, 1\u20131 (2018)"}],"container-title":["EURASIP Journal on Wireless Communications and Networking"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s13638-020-01808-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s13638-020-01808-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s13638-020-01808-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,10,19]],"date-time":"2021-10-19T00:39:56Z","timestamp":1634603996000},"score":1,"resource":{"primary":{"URL":"https:\/\/jwcn-eurasipjournals.springeropen.com\/articles\/10.1186\/s13638-020-01808-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,10,19]]},"references-count":20,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2020,12]]}},"alternative-id":["1808"],"URL":"https:\/\/doi.org\/10.1186\/s13638-020-01808-z","relation":{},"ISSN":["1687-1499"],"issn-type":[{"value":"1687-1499","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,10,19]]},"assertion":[{"value":"22 January 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 September 2020","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 October 2020","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"There are no competing interests in this study.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"206"}}