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In particular, we introduce the concept of\n            <jats:italic>cyber deception<\/jats:italic>\n            using honey drones (HDs) to protect the mission system from DoS attacks. HDs exhibit fake vulnerabilities and employ stronger signal strengths to lure DoS attacks, unlike the legitimate drones called\n            <jats:italic>mission drones<\/jats:italic>\n            (MDs) deployed for mission execution. This research formulates an optimization problem to identify an optimal set of signal strengths of HDs and MDs to best prevent the system from DoS attacks while maximizing mission performance under the resource constraints of UAVs. To solve this optimization problem, we leverage deep reinforcement learning (DRL) to achieve these multiple objectives of the mission system concerning system security and performance. Particularly, for efficient and effective parallel processing in DRL, we utilize a DRL algorithm called the\n            <jats:italic>Asynchronous Advantage Actor-Critic<\/jats:italic>\n            (A3C) algorithm to model attack-defense interactions. We employ a physical engine-based simulation testbed to consider realistic scenarios and demonstrate valid findings from the realistic testbed. The extensive experiments proved that our HD-based approach could achieve up to a 32% increase in mission completion, a 20% reduction in energy consumption, and a 62% decrease in attack success rates compared to existing defense strategies.\n          <\/jats:p>","DOI":"10.1145\/3701233","type":"journal-article","created":{"date-parts":[[2024,10,25]],"date-time":"2024-10-25T11:00:08Z","timestamp":1729854008000},"page":"1-26","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["Optimizing Effectiveness and Defense of Drone Surveillance Missions via Honey Drones"],"prefix":"10.1145","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5293-0363","authenticated-orcid":false,"given":"Zelin","family":"Wan","sequence":"first","affiliation":[{"name":"Computer Science, Virginia Tech, Falls Church, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5908-4662","authenticated-orcid":false,"given":"Jin-Hee","family":"Cho","sequence":"additional","affiliation":[{"name":"Virginia Tech, Falls Church, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4303-4318","authenticated-orcid":false,"given":"Mu","family":"Zhu","sequence":"additional","affiliation":[{"name":"North Carolina State University at Raleigh, Raleigh, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8907-3043","authenticated-orcid":false,"given":"Ahmed","family":"Anwar","sequence":"additional","affiliation":[{"name":"US Army DEVCOM Army Research Laboratory, Adelphi, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2169-5975","authenticated-orcid":false,"given":"Charles","family":"Kamhoua","sequence":"additional","affiliation":[{"name":"US Army DEVCOM Army Research Laboratory, Adelphi, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3599-3893","authenticated-orcid":false,"given":"Munindar","family":"Singh","sequence":"additional","affiliation":[{"name":"North Carolina State University, Raleigh, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2024,11,18]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.1109\/MCOM.2016.7470933"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.1109\/COMST.2015.2495297"},{"key":"e_1_3_2_4_2","first-page":"613","article-title":"UAV-based Cadasral mapping: An assessment of the impact of flight parameters and ground truth measurements on the absolute accuracy of derived orthoimages","volume":"2","author":"St\u00f6cker C.","year":"2019","unstructured":"C. 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