{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,28]],"date-time":"2026-03-28T06:12:23Z","timestamp":1774678343581,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":24,"publisher":"ACM","license":[{"start":{"date-parts":[[2019,5,15]],"date-time":"2019-05-15T00:00:00Z","timestamp":1557878400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2019,5,15]]},"DOI":"10.1145\/3324921.3328785","type":"proceedings-article","created":{"date-parts":[[2019,5,17]],"date-time":"2019-05-17T12:52:21Z","timestamp":1558097541000},"page":"25-30","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":46,"title":["On the Limitations of Targeted Adversarial Evasion Attacks Against Deep Learning Enabled Modulation Recognition"],"prefix":"10.1145","author":[{"given":"Samuel","family":"Bair","sequence":"first","affiliation":[{"name":"Hume Center for National Security and Technology, Virginia Polytechnic Institute and State University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Matthew","family":"DelVecchio","sequence":"additional","affiliation":[{"name":"Hume Center for National Security and Technology, Virginia Polytechnic Institute and State University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bryse","family":"Flowers","sequence":"additional","affiliation":[{"name":"Hume Center for National Security and Technology, Virginia Polytechnic Institute and State University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alan J.","family":"Michaels","sequence":"additional","affiliation":[{"name":"Hume Center for National Security and Technology, Virginia Polytechnic Institute and State University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"William C.","family":"Headley","sequence":"additional","affiliation":[{"name":"Hume Center for National Security and Technology, Virginia Polytechnic Institute and State University"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2019,5,15]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"IX International Symposium on Telecommunications (BIHTEL)","author":"Mohamed M.","year":"2013","unstructured":"Mohamed M. T. Abdelreheem and Mahi O. Helmi. 2013. Digital Modulation Classification through time and frequency domain features using Neural Networks . IX International Symposium on Telecommunications (BIHTEL) ( 2013 ). Mohamed M. T. Abdelreheem and Mahi O. Helmi. 2013. Digital Modulation Classification through time and frequency domain features using Neural Networks. IX International Symposium on Telecommunications (BIHTEL) (2013)."},{"key":"e_1_3_2_1_2_1","volume-title":"49th Asilomar Conference on Signals, Systems and Computers","author":"Bari Mohammad","year":"2016","unstructured":"Mohammad Bari , Awais Khawar , Milos Doroslovacki , and T. Charles Clancy . 2016. Recognizing FM, BPSK and 16-QAM using supervised and unsupervised learning techniques . 49th Asilomar Conference on Signals, Systems and Computers ( 2016 ). Mohammad Bari, Awais Khawar, Milos Doroslovacki, and T. Charles Clancy. 2016. Recognizing FM, BPSK and 16-QAM using supervised and unsupervised learning techniques. 49th Asilomar Conference on Signals, Systems and Computers (2016)."},{"key":"e_1_3_2_1_3_1","first-page":"137","article-title":"Survey of automatic modulation classification techniques: classical approaches and new trends","volume":"1","author":"Dobre Octavia A.","year":"2007","unstructured":"Octavia A. Dobre , Ali Abdi , Yeheskel Bar-Ness , and Wei Su . 2007 . Survey of automatic modulation classification techniques: classical approaches and new trends . Journal 1 , 2 (2007), 137 -- 156 . Octavia A. Dobre, Ali Abdi, Yeheskel Bar-Ness, and Wei Su. 2007. Survey of automatic modulation classification techniques: classical approaches and new trends. Journal 1, 2 (2007), 137--156.","journal-title":"Journal"},{"key":"e_1_3_2_1_4_1","volume-title":"Boosting Adversarial Attacks with Momentum. Journal","author":"Dong Yinpeng","year":"2017","unstructured":"Yinpeng Dong , Fangzhou Liao , Tianyu Pang , Hang Su , Jun Zhu , Xiaolin Hu , and Jianguo Li. 2017. Boosting Adversarial Attacks with Momentum. Journal ( 2017 ). Yinpeng Dong, Fangzhou Liao, Tianyu Pang, Hang Su, Jun Zhu, Xiaolin Hu, and Jianguo Li. 2017. Boosting Adversarial Attacks with Momentum. Journal (2017)."},{"key":"e_1_3_2_1_5_1","volume-title":"Deep Learning for Launching and MitigatingWireless Jamming Attacks. arXiv preprint arXiv:1807.02567","author":"Erpek Tugba","year":"2018","unstructured":"Tugba Erpek , Yalin E. Sagduyu , and Yi Shi . 2018. Deep Learning for Launching and MitigatingWireless Jamming Attacks. arXiv preprint arXiv:1807.02567 ( 2018 ). Tugba Erpek, Yalin E. Sagduyu, and Yi Shi. 2018. Deep Learning for Launching and MitigatingWireless Jamming Attacks. arXiv preprint arXiv:1807.02567 (2018)."},{"key":"e_1_3_2_1_6_1","volume-title":"Evaluating Adversarial Evasion Attacks in the Context of Wireless Communications. arXiv preprint arXiv:1903.01563","author":"Flowers Bryse","year":"2019","unstructured":"Bryse Flowers , R Michael Buehrer , and William C Headley . 2019. Evaluating Adversarial Evasion Attacks in the Context of Wireless Communications. arXiv preprint arXiv:1903.01563 ( 2019 ). Bryse Flowers, R Michael Buehrer, and William C Headley. 2019. Evaluating Adversarial Evasion Attacks in the Context of Wireless Communications. arXiv preprint arXiv:1903.01563 (2019)."},{"key":"e_1_3_2_1_7_1","volume-title":"Explaining and Harnessing Adversarial Examples. International Conference on Learning Representaions","author":"Goodfellow Ian","year":"2015","unstructured":"Ian Goodfellow , Jonathon Shelens , and Christian Szegedy . 2015 . Explaining and Harnessing Adversarial Examples. International Conference on Learning Representaions (2015). Ian Goodfellow, Jonathon Shelens, and Christian Szegedy. 2015. Explaining and Harnessing Adversarial Examples. International Conference on Learning Representaions (2015)."},{"key":"e_1_3_2_1_8_1","volume-title":"Communication without Interception: Defenseagainst Deep-Learning-based Modulation Detection. arXiv preprint arXiv","author":"Hameed Muhammad Zaid","year":"1902","unstructured":"Muhammad Zaid Hameed , Andr\u00e1s Gy\u00f6rgy , and Deniz G\u00fcnd\u00fcz . 2019. Communication without Interception: Defenseagainst Deep-Learning-based Modulation Detection. arXiv preprint arXiv : 1902 .10674 (2019). Muhammad Zaid Hameed, Andr\u00e1s Gy\u00f6rgy, and Deniz G\u00fcnd\u00fcz. 2019. Communication without Interception: Defenseagainst Deep-Learning-based Modulation Detection. arXiv preprint arXiv: 1902.10674 (2019)."},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCSPA.2013.6487244"},{"key":"e_1_3_2_1_10_1","volume-title":"Distributed Cyclic Spectrum Feature-Based Modulation Classification. IEEE Wireless Communications and Networking Conference","author":"Headley William C.","year":"2008","unstructured":"William C. Headley , Jesse D. Reed , and Claudio R. C. M. da Silva. 2008 . Distributed Cyclic Spectrum Feature-Based Modulation Classification. IEEE Wireless Communications and Networking Conference ( 2008 ). William C. Headley, Jesse D. Reed, and Claudio R. C. M. da Silva. 2008. Distributed Cyclic Spectrum Feature-Based Modulation Classification. IEEE Wireless Communications and Networking Conference (2008)."},{"key":"e_1_3_2_1_11_1","volume-title":"Adversarial Machine Learning. ACM workshop on Security and artificial intelligence","author":"Huang Ling","year":"2011","unstructured":"Ling Huang , Anthony D. Joseph , Blaine Nelson , Benjamin I.P. Rubinstein , and J.D. Tygar . 2011 . Adversarial Machine Learning. ACM workshop on Security and artificial intelligence ( 2011 ), 43--58. Ling Huang, Anthony D. Joseph, Blaine Nelson, Benjamin I.P. Rubinstein, and J.D. Tygar. 2011. Adversarial Machine Learning. ACM workshop on Security and artificial intelligence (2011), 43--58."},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/DySPAN.2017.7920746"},{"key":"e_1_3_2_1_13_1","first-page":"1","article-title":"Rigorous Moment-Based Automatic Modulation Classification","volume":"1","author":"Kawamoto Darek T","year":"2016","unstructured":"Darek T Kawamoto and Robert W. McGwier . 2016 . Rigorous Moment-Based Automatic Modulation Classification . Proc. of the GNU Radio Conference 1 , 1 . Darek T Kawamoto and Robert W. McGwier. 2016. Rigorous Moment-Based Automatic Modulation Classification. Proc. of the GNU Radio Conference 1, 1.","journal-title":"Proc. of the GNU Radio Conference"},{"key":"e_1_3_2_1_14_1","volume-title":"Adversarial Examples in RF Deep Learning:Detection of the Attack and its Physical Robustness. arXiv preprint arXiv:1902.06044","author":"Kokalj-Filipovic Silvija","year":"2019","unstructured":"Silvija Kokalj-Filipovic and Rob Miller . 2019. Adversarial Examples in RF Deep Learning:Detection of the Attack and its Physical Robustness. arXiv preprint arXiv:1902.06044 ( 2019 ). Silvija Kokalj-Filipovic and Rob Miller. 2019. Adversarial Examples in RF Deep Learning:Detection of the Attack and its Physical Robustness. arXiv preprint arXiv:1902.06044 (2019)."},{"key":"e_1_3_2_1_15_1","volume-title":"Adversarial Examples in the Physical World. International Conference on Learning Representaions","author":"Kurakin Alexey","year":"2017","unstructured":"Alexey Kurakin , Ian J. Goodfellow , and Samy Bengio . 2017 . Adversarial Examples in the Physical World. International Conference on Learning Representaions (2017). Alexey Kurakin, Ian J. Goodfellow, and Samy Bengio. 2017. Adversarial Examples in the Physical World. International Conference on Learning Representaions (2017)."},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/TCCN.2017.2758370"},{"key":"e_1_3_2_1_17_1","volume-title":"Convolutional Radio Modulation Recognition Networks. Communications in Computer and Information Science 629","author":"O'Shea Timothy J.","year":"2016","unstructured":"Timothy J. O'Shea , Johnathan Corgan , and T. Charles Clancy . 2016. Convolutional Radio Modulation Recognition Networks. Communications in Computer and Information Science 629 ( 2016 ). Timothy J. O'Shea, Johnathan Corgan, and T. Charles Clancy. 2016. Convolutional Radio Modulation Recognition Networks. Communications in Computer and Information Science 629 (2016)."},{"key":"e_1_3_2_1_18_1","volume-title":"Proc. of the GNU Radio Conf. 1","author":"O'Shea Timothy J.","year":"2016","unstructured":"Timothy J. O'Shea and Nathan West . 2016 . Radio machine learning dataset generation with gnu radio . Proc. of the GNU Radio Conf. 1 (2016). Timothy J. O'Shea and Nathan West. 2016. Radio machine learning dataset generation with gnu radio. Proc. of the GNU Radio Conf. 1 (2016)."},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/EuroSP.2016.36"},{"key":"e_1_3_2_1_20_1","volume-title":"Larsson","author":"Sadegh Meysam","year":"2018","unstructured":"Meysam Sadegh and Erik G . Larsson . 2018 . Adversarial Attacks on DeepLearning Based Radio Signal Classification. IEEE Wireless Communication Letters ( 2018). Meysam Sadegh and Erik G. Larsson. 2018. Adversarial Attacks on DeepLearning Based Radio Signal Classification. IEEE Wireless Communication Letters (2018)."},{"key":"e_1_3_2_1_21_1","volume-title":"Li","author":"Shi Yi","year":"2019","unstructured":"Yi Shi , Tugba Erpek , Yalin E. Sagduyu , and Jason H . Li . 2019 . Spectrum Data Poisoning with Adversarial DeepLearning . arXiv preprint arXiv:1901.09247 (2019). Yi Shi, Tugba Erpek, Yalin E. Sagduyu, and Jason H. Li. 2019. Spectrum Data Poisoning with Adversarial DeepLearning. arXiv preprint arXiv:1901.09247 (2019)."},{"key":"e_1_3_2_1_22_1","volume-title":"IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN)","author":"Nathan","year":"2017","unstructured":"Nathan E. West and Tim O'Shea. 2017. Deep architectures for modulation recognition . IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN) ( 2017 ). Nathan E. West and Tim O'Shea. 2017. Deep architectures for modulation recognition. IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN) (2017)."},{"key":"e_1_3_2_1_23_1","volume-title":"MILCOM 2018","author":"Wong Lauren J.","year":"2018","unstructured":"Lauren J. Wong , William C. Headley , Seth Andrews , Ryan M. Gerdes , and Alan J. Michaels . 2018. Clustering Learned CNN Features from Raw I\/Q Data for Emitter Identification . MILCOM 2018 ( 2018 ). Lauren J. Wong, William C. Headley, Seth Andrews, Ryan M. Gerdes, and Alan J. Michaels. 2018. Clustering Learned CNN Features from Raw I\/Q Data for Emitter Identification. MILCOM 2018 (2018)."},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1109\/DySPAN.2017.7920747"}],"event":{"name":"WiSec '19: 12th ACM Conference on Security and Privacy in Wireless and Mobile Networks","location":"Miami FL USA","acronym":"WiSec '19","sponsor":["SIGSAC ACM Special Interest Group on Security, Audit, and Control","SIGMOBILE ACM Special Interest Group on Mobility of Systems, Users, Data and Computing"]},"container-title":["Proceedings of the ACM Workshop on Wireless Security and Machine Learning"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3324921.3328785","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3324921.3328785","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T20:47:24Z","timestamp":1750193244000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3324921.3328785"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,5,15]]},"references-count":24,"alternative-id":["10.1145\/3324921.3328785","10.1145\/3324921"],"URL":"https:\/\/doi.org\/10.1145\/3324921.3328785","relation":{},"subject":[],"published":{"date-parts":[[2019,5,15]]},"assertion":[{"value":"2019-05-15","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}