DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, Dohyun | ko |
dc.contributor.author | Cho, Mangi | ko |
dc.contributor.author | Shin, Hocheol | ko |
dc.contributor.author | Kim, Jaehoon | ko |
dc.contributor.author | Noh, Juhwan | ko |
dc.contributor.author | Kim, Yongdae | ko |
dc.date.accessioned | 2023-12-27T03:01:39Z | - |
dc.date.available | 2023-12-27T03:01:39Z | - |
dc.date.created | 2023-12-27 | - |
dc.date.created | 2023-12-27 | - |
dc.date.issued | 2023-11 | - |
dc.identifier.citation | ACM TRANSACTIONS ON PRIVACY AND SECURITY, v.26, no.4 | - |
dc.identifier.issn | 2471-2566 | - |
dc.identifier.uri | http://hdl.handle.net/10203/316918 | - |
dc.description.abstract | Photoelectric sensors are utilized in a range of safety-critical applications, such as medical devices and autonomous vehicles. However, the public exposure of the input channel of a photoelectric sensor makes it vulnerable to malicious inputs. Several studies have suggested possible attacks on photoelectric sensors by injecting malicious signals. While a few defense techniques have been proposed against such attacks, they could be either bypassed or used for limited purposes. In this study, we propose Lightbox, a novel defense system to detect sensor attacks on photoelectric sensors based on signal fingerprinting. Lightbox uses the spectrum of the received light as a feature to distinguish the attacker's malicious signals fromthe authentic signal, which is a signal from the sensor's light source. We evaluated Lightbox against (1) a saturation attacker, (2) a simple spoofing attacker, and (3) a sophisticated attacker who is aware of Lightbox and can combine multiple light sources tomimic the authentic light source. Lightbox achieved the overall accuracy over 99% for the saturation attacker and simple spoofing attacker, and robustness against a sophisticated attacker. We also evaluated Lightbox considering various environments such as transmission medium, background noise, and input waveform. Finally, we demonstrate the practicality of Lightbox with experiments using a single-board computer after further reducing the training time. | - |
dc.language | English | - |
dc.publisher | ASSOC COMPUTING MACHINERY | - |
dc.title | Lightbox: Sensor Attack Detection for Photoelectric Sensors via Spectrum Fingerprinting | - |
dc.type | Article | - |
dc.identifier.wosid | 001112427200004 | - |
dc.identifier.scopusid | 2-s2.0-85179126089 | - |
dc.type.rims | ART | - |
dc.citation.volume | 26 | - |
dc.citation.issue | 4 | - |
dc.citation.publicationname | ACM TRANSACTIONS ON PRIVACY AND SECURITY | - |
dc.identifier.doi | 10.1145/3615867 | - |
dc.contributor.localauthor | Kim, Yongdae | - |
dc.contributor.nonIdAuthor | Kim, Dohyun | - |
dc.description.isOpenAccess | N | - |
dc.type.journalArticle | Article | - |
dc.subject.keywordAuthor | Photoelectric sensors | - |
dc.subject.keywordAuthor | neural networks | - |
dc.subject.keywordAuthor | signal fingerprinting | - |
dc.subject.keywordPlus | DEFECTS | - |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.