Detecting Fake QR Codes Using Information from Error-Correction

• Item type: Journal(1)
• 公開日: 2021-09-15
• タイトル: Detecting Fake QR Codes Using Information from Error-Correction
• タイトル / 言語: en
• タイトル: Detecting Fake QR Codes Using Information from Error-Correction
• 言語: eng
• キーワード / 主題Scheme: Other
• キーワード / 主題: [特集：Society 5.0を実現するコンピュータセキュリティ技術（推薦論文）] phishing, QR code, fake, detection, error-correcting code
• 資源タイプ / 資源タイプ識別子: http://purl.org/coar/resource_type/c_6501
• 資源タイプ: journal article
• 著者所属: Tokai University
• 著者所属: Tokai University
• 著者所属: Tokai University
• 著者所属: Tokai University
• 著者所属: University of Tsukuba
• 著者所属: Tokai University
• 著者所属: Tokai University
• 著者所属: Tokai University
• 著者所属: FUJITSU Ltd.
• 著者所属: FUJITSU Ltd.
• 著者所属: FUJITSU Ltd.
• 著者所属: FUJITSU Ltd.
• 著者所属(英): en
• 著者所属(英): Tokai University
• 著者所属(英): en
• 著者所属(英): Tokai University
• 著者所属(英): en
• 著者所属(英): Tokai University
• 著者所属(英): en
• 著者所属(英): Tokai University
• 著者所属(英): en
• 著者所属(英): University of Tsukuba
• 著者所属(英): en
• 著者所属(英): Tokai University
• 著者所属(英): en
• 著者所属(英): Tokai University
• 著者所属(英): en
• 著者所属(英): Tokai University
• 著者所属(英): en
• 著者所属(英): FUJITSU Ltd.
• 著者所属(英): en
• 著者所属(英): FUJITSU Ltd.
• 著者所属(英): en
• 著者所属(英): FUJITSU Ltd.
• 著者所属(英): en
• 著者所属(英): FUJITSU Ltd.
• 著者名: Toshihiro, Ohigashi; Shuya, Kawaguchi; Kai, Kobayashi; Hayato, Kimura; Tatsuya, Suzuki; Daichi, Okabe; Takuya, Ishibashi; Hiroshi, Yamamoto; Maki, Inui; Ryo, Miyamoto; Kazuyoshi, Furukawa; Tetsuya, Izu
• 著者名(英): Toshihiro, Ohigashi; Shuya, Kawaguchi; Kai, Kobayashi; Hayato, Kimura; Tatsuya, Suzuki; Daichi, Okabe; Takuya, Ishibashi; Hiroshi, Yamamoto; Maki, Inui; Ryo, Miyamoto; Kazuyoshi, Furukawa; Tetsuya, Izu
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: In 2018, Takita et al. proposed a construction method of a fake QR code by adding stains to a target QR code, that probabilistically leads users to a malicious website. The construction abused the error-correction of error-correcting code used in the QR code, namely, the added stains induce decoding errors in black and white detection by a camera, so that the decoded URL leads to the malicious website. Also, the same authors proposed a detection method against such fake QR codes by comparing decoded URLs among multiple QR code readings since the decoded URLs may differ because of its probabilistic property. However, the detection method cannot work well over a few readings. Moreover, the proposed detection method does not consider the environmental or accidental changes such as sudden sunshine or reflection, nor recognizes the fake QR code as non-fake when the probability is low. This paper proposes new detection methods for such fake QR codes by analyzing information obtained from the error-correcting process. This paper also reports results from implementing the new detection methods on an Android smartphone. Results show that a combination of these detection methods works very well compared to when using only a single detection method.; ------------------------------; This is a preprint of an article intended for publication Journal of; Information Processing(JIP). This preprint should not be cited. This; article should be cited as: Journal of Information Processing Vol.29(2021) (online); DOI http://dx.doi.org/10.2197/ipsjjip.29.548; ------------------------------
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: In 2018, Takita et al. proposed a construction method of a fake QR code by adding stains to a target QR code, that probabilistically leads users to a malicious website. The construction abused the error-correction of error-correcting code used in the QR code, namely, the added stains induce decoding errors in black and white detection by a camera, so that the decoded URL leads to the malicious website. Also, the same authors proposed a detection method against such fake QR codes by comparing decoded URLs among multiple QR code readings since the decoded URLs may differ because of its probabilistic property. However, the detection method cannot work well over a few readings. Moreover, the proposed detection method does not consider the environmental or accidental changes such as sudden sunshine or reflection, nor recognizes the fake QR code as non-fake when the probability is low. This paper proposes new detection methods for such fake QR codes by analyzing information obtained from the error-correcting process. This paper also reports results from implementing the new detection methods on an Android smartphone. Results show that a combination of these detection methods works very well compared to when using only a single detection method.; ------------------------------; This is a preprint of an article intended for publication Journal of; Information Processing(JIP). This preprint should not be cited. This; article should be cited as: Journal of Information Processing Vol.29(2021) (online); DOI http://dx.doi.org/10.2197/ipsjjip.29.548; ------------------------------
• 書誌レコードID / 収録物識別子タイプ: NCID
• 書誌レコードID / 収録物識別子: AN00116647
• 書誌情報: 情報処理学会論文誌; 巻 62, 号 9, 発行日 2021-09-15
• ISSN / 収録物識別子タイプ: ISSN
• ISSN / 収録物識別子: 1882-7764