臺灣博碩士論文加值系統

鑑於3C產品的普及與人工智慧的發展，造就了現代車輛本質上即為一行動電腦裝置，汽車就是一台行動自如的電腦，其功能從交通工具，儼然成為有配備輪胎之智慧型手機，而傳統以車輛為犯罪工具，嫌犯湮滅證據的方法為擦拭指紋或破壞殘留於車輛之相關生物跡證，然而，車輛中更記錄了可作為佐證的資料，如最近的目的地、我的最愛地點、路線；個人資料如通話記錄、通訊錄、簡訊、照片和影片。可想而知車輛所蘊含之數位證據更加豐富，故車輛如為犯罪工具，其車載數據之證據價值的詮釋至關重要。數據存檔這些車載娛樂系統上，此殘留數據因而反映了駕駛的活動和潛在的個人訊息，嫌犯認知到這些數據資料有可能成為證明其犯行之犯罪證據，故其湮滅證據之方式已從破壞生物跡證演化成以實體或邏輯之方式破壞車載娛樂系統之數據資料達成掩飾其犯行之結果。
本論文主要針對車載娛樂系統與OBD-Ⅱ車輛診斷系統如何擷取數據以及收集的數據對刑案偵查的影響和貢獻，並探討因各家汽車廠商數位資料格式不一造成執法機關鑑識挑戰，並提出解釋嫌犯可能破壞車載數據之方法，進一步提出一套針對車聯網鑑識資料擷取標準作業程序，協助第一線執法人員有效地辨識出具證據價值的車載數位證據，假設犯罪者試圖故意利用實體與邏輯方式破壞車載娛樂系統中數位證據時，資料還原方法。
關鍵詞:車聯網、反鑑識、車載娛樂系統（In-Vehicle Infotainment，IVI）

The new generation of car functions has evolved into mobile computer devices. The car as a mobile computer, the function is from a vehicle to a smart phone equipped with tires. Then the traditional method of using vehicles as a criminal tool, the suspect destruct the evidence by wiping fingerprints or destroy the relevant trace evidence of remaining in the vehicle. As the vehicle has IVI (In-Vehicle Infotainment), via the GPS system, media player device and APP function to achieve driving convenience. Therefore, mobile phone and laptops can be connected to various APP devices by Bluetooth and Wi-Fi also further implement the data traffic with Infotainment. Data is saved on these built-in devices, and this residual data reflects driving activities and potential personal messages, the suspect recognizes that these data may become evidence of the value which contained in his crime, so the way of destroy the evidence has evolved from the destruction of the trace evidence to the physical or logical way at destroy the remaining data in the Infotainment. Furthermore, self-driving cars will become a trend in the future, and vehicles will become criminal tools, such as terrorists using self-driving cars to attack large gatherings. In-vehicle data can be used to explain crime and make up for the insufficiency of traditional biomarker evidence. The main purpose of this study is to propose a forensics strategy, explain the suspects may destroy vehicle data, and provide a set of Internet of Vehicle (IoV) forensic standard procedures to assist frontline law enforcement personnel identify the evidence value of In-Vehicle data, also assuming while criminal tried to deliberately use physical and logical methods to destroy the digital evidence in the Infotainment then how to restore data
Keywords: Internet of Vehicle (IoV), anti-forensics, IVI (In-Vehicle Infotainment)

誌謝 I
摘要 II
Abstract III
目錄 IV
圖目錄 VIII
表目錄 X
第一章 緒論 1
1.1 研究背景與動機 1
1.2 研究目的 2
1.3 研究範圍與研究限制 3
1.4 研究架構 4
第二章 文獻綜覽及基礎背景知識 5
2.1 車聯網 5
2.1.1 V2V 通訊方法 6
2.1.2 DSRC特徵及用途 7
2.1.3 DSRC 車輛追蹤 8
2.1.4 PKI的安全措施 9
2.2 車載內部網路定義及架構 12
2.2.1 CAN匯流排 14
2.2.2 MOST 協定 15
2.3 車載診斷系統 16
2.3.1 OBD-II 17
2.3.2 OBD-III 18
2.3.3 OBD-II故障診斷代碼 18
2.3.4事件日誌記錄 19
2.4 車載娛樂系統（In-Vehicle-Infotainment，IVI） 21
2.4.1識別車載娛樂系統類型 22
2.4.2常見系統偵錯改造方法 23
2.4.3 APP 和外掛程式 24
2.4.4常見攻擊方式 25
2.5 Android系統概述 27
2.6 數位鑑識取證模型 30
2.7 行動裝置鑑識與傳統電腦鑑識比較 31
第三章 車聯網鑑識現行困難與挑戰 34
3.1 車聯網鑑識實務取證挑戰如下： 34
3.1.1汽車取證的安全和隱私 35
3.1.2實務車載資料取證常見問題 35
3.2 文獻汽車數據取證方式 36
3.2.1車聯網取證方法 36
3.2.2車聯網鑑識偵查模型架構—以iVe為例 37
3.2.3以福特(Focus／Fiesta)為例使用Berla iVe所擷取數據類型 38
第四章 車聯網鑑識解決方案 40
4.1 車載數據鑑識過程 40
4.1.1識別 40
4.1.2獲得數據 40
4.1.3分析 40
4.2 解決方案 41
4.3 車聯網鑑識與傳統數位鑑識異同 44
4.3.1辨識、收集車聯網中車載數據 44
4.3.2比對與個化車載數據 44
4.3.3歸責對象 44
4.3.4資料授權權限 45
4.3.5車載數據隱私 45
第五章 實驗設計與模擬案例 47
5.1 車載娛樂系統實驗目的與模擬案例 47
5.1.1檔案系統結構 49
5.1.2刪除網站搜尋紀錄 52
5.1.3刪除車行軌跡 53
5.1.4日曆備忘錄之載客記錄 55
5.1.5Wi-Fi熱點連結紀錄 56
5.1.6藍牙連線紀錄 56
5.1.7 Garmin Nuvi4695特殊功能證據價值 57
5.1.8 其他車載數據證據價值 58
5.2 OBD-II系統證據價值探討 60
第六章 結論與未來展望 68
參考文獻 69

[1] Cheng, Ho Ting; Shan, Hangguan; Zhuang, Weihua ;, "Infotainment and road safety service support in vehicular networking: From a communication perspective," Mechanical Systems and Signal Processing, pp. 2020-2038, 8 2011.
[2] C. Smith, The Car Hacker’s Handbook A Guide for the Penetration Tester, San Francisco: William Pollock, 2016, pp. 144-159 118-119.
[3] Wikipedia, “Wikipedia,” 2 4 2020. [Online]. Available: https://en.wikipedia.org/wiki/LoJack.
[4] 杜靜；李博；敖富江,汽車駭客大曝光, 清華大學出版社, 2017, pp. 144-150 163-165 24-25.
[5] Silva , Ricardo; Iqba, Razi;, "Ethical Implications of Social Internet of Vehicles Systems," IEEE Internet of Things Journal, . vol 6, no. 1, 2019.
[6] Hossain, Mahmud; Hasan, Ragib ; Zawoad, Shams;, "Trust-IoV: A Trustworthy Forensic Investigation Framework for the Internet of Vehicles (IoV)," in 2017 IEEE International Congress on Internet of Things (ICIOT), Honolulu, 2017.
[7] 邱翊晉, 結合雲端服務與OBD-II之Android車載資通訊平台設計與實作, 樹德科技大學資訊工程系碩士班學位論文, 2013, pp. 3-4.
[8] “ITREAD01.COM,” 16 12 2018. [Online] Available: https://www.itread01.com/content/1544925184.html.
[9] “Android系統架構分層及每層詳細介紹,” 05 11 2018. [線上]. Available: https://kknews.cc/zh-tw/code/o9ngqaq.html.
[10] 鄧思源; 林育梨, “運用Android仿真器做為數位犯罪工具之研究,” 資訊安全通訊,第二十二卷, 編號 3, pp. 49-70, 1 7 2016.
[11] Reith, Mark; Carr, Clint ; Gunsch, Gregg H. ;, "An Examination of Digital Forensic Models," International Journal of Digital Evidence, vol. 1, no. 3, 1 1 2002.
[12] Le-Khac, Nhien-An; Jacobs, Daniël; Nijhoff, John ; Bertens, Karsten; Choo , Kim-Kwang Raymond;, "Smart vehicle forensics: Challenges and case study," Future Generation Computer Systems, 7 6 2018.
[13] Whelan, Celia J.; Sammon, John; McManus, Brian; Fenger, Terry W.;, "Retrieval of Infotainment System Artifacts from Vehicles Using iVe," Journal of Applied Digital Evidence, vol. 1, no. 1, 7 2018.
[14] 陳詰昌, “數位鑑識「原件不可變動原則」之適用—由行動裝置鑑識與電腦鑑識差異探討,” 司法新聲季刊, 編號 119, 2016.
[15] L. Jesse, Vehicular infotainment forensics: collecting data and putting it into perspective, University of Ontario Institute of Technology, 2017.
[16] Nilsson, Dennis K.;Phung, Phu H. ; Larson, Ulf E.; , "Vehicle ECU classification based on safety-security characteristics," in IET Road Transport Information and Control - RTIC 2008 and ITS United Kingdom Members' Conference, Manchester, 2008.
[17] Berla, "Berla Corporation," 2020. [Online]. Available: http://www.berla.co.
[18] Mansor, Hafizah; Markantonakis, Konstantinos; Akram, Raja Naeem; Mayes, Keith ; Gurulian, Iakovos, “Log your car: The non-invasive vehicle forensics,” in 2016 IEEE Trustcom/BigDataSE/ISPA, Tianjin, China, 2016.
[19] Zhang, Xiaolu; Baggili, Ibrahim; Breitinger, Frank, "Breaking into the vault: Privacy, security and forensic analysis of Android vault applications," Computers & Security, vol. 70, pp. 516-531, 9 2017.
[20] Baek, Sung-Hyun; Jeong, Da-Woon; Park, You-Sin ; Kim, Hwa-Su; Kim, Mi-Jin; Jang, Jong-Wook, “Implementation Vehicle Driving State System with OBD-II, MOST network,” in The 17th Asia Pacific Conference on Communications, Sabah, 2011.
[21] 中央警察大學資訊密碼暨建構實驗室, “反鑑識工具抹除數位足跡 立即採證記憶體才能救,” 網管人, 27 8 2015.
[22] 王旭正, 數位鑑識之平板應用程式-玩與完, 台北市: information cryptology & construction lab, 2012.
[23] Distefano, Alessandro; Me, Gianluig; Pace, Francesco, "Android anti-forensics through a local paradigm," Digital Investigation, vol.7, pp. 83-94, 8 2010.
[24] R. Parag, "Steganography on Android Based Smart Phones," International Journal of Mobile & Adhoc, vol. 3, pp. 150-152, 1 5 2012.
[25] Karlsson, Karl Johan; Glisson, William Bradley, "Android Anti-forensics: Modifying CyanogenMod," in 2014, IEEE Computer Society Press, Hawaii, 2014.
[26] Mambodza, Walter T; NagoorMeeran, A R.;, "Android mobile forensic analyzer for stegno data," in 2015 International Conference on Circuits, Power and Computing Technologies, Nagercoil, 2015.
[27] R. Macfarlane, A. Smales and A. Arbelet, "Garmin satnavs forensic methods and artefacts: An exploratory study," Edinburgh Napier University for the Degree of Master of Science in Advanced Security and Digital Forensics, 2014.
[28] 余祥銘, “導航手機與GPS軌跡記錄在供應鏈運輸之稽核角色探討,” 東海大學, 2011.
[29] W. Bortles, S. McDonough, C. Smith and M. Stogsdill, "An Introduction to the Forensic Acquisition of Passenger Vehicle Infotainment and Telematics Systems Data," in WCX™ 17: SAE World Congress Experience, 2017.
[30] M. Nahri, A. Boulmakoul, L. Karim A. Lbath, “IoV distributed architecture for real-time traffic data analytics,” Procedia Computer Science, vol. 130, pp. 480-487, 24 8 2018.
[31] 周政旭, 整合雲端計算的OBD-II車輛線上診斷系統實作, 樹德科技大學資訊工程系(研究所), 2013.
[32] A. X. Albert Sim and B. Sitohang, “OBD-II standard car engine diagnostic software development,” in 2014 International Conference on Data and Software Engineering (ICODSE), Bandung, 2014.
[33] B. Dharaskar, R. V. Dharaskar and V. M. Thakare, “GLOBAL POSITIONING SYSTEM FORENSICS IN VEHICULAR AD-HOC NETWORKS,” International Journal of Advances in Electronics and Computer Science, vol 2, 4, 8 2015.
[34] M. Cebe, E. Erdin, K. Akkaya, H. Aksu and S. Uluagac, "Block4Forensic: An Integrated Lightweight Blockchain Framework for Forensics Applications of Connected Vehicles," IEEE Communications Magazine, vol. 56, pp. 50-57, 16 10 2018.
[35] J. H. Lim, K. H. Choi, L. Kim and H. K. Lee, “Land vehicle positioning in urban area by integrated GPS/BeiDou/OBD-II/MEMS IMU,” in 2016 IEEE International Conference on Intelligent Transportation Engineering (ICITE), Singapore, 2016.
[36] T. Jia, W. Luo, H. Jia, H. Zhu and X. Li, "Research on remote diagnosis system based on baidumap API and OBD II diagnosis technology," in 2016 International Conference On Communication Problem-Solving (ICCP), Taipei, 2016.
[37] A. H. Sodhro, Z. Luo, G. H. Sodhro, M. Muzammal, J. J. Rodrigues and V. H. C. d. Albuquerque, “Future Generation Computer Systems,” Future Generation Computer Systems, vol 95, pp. 667-680, 6 2019.
[38] S. Liu, A. Liu, Z. Yan and W. Feng, “Efficient LBS queries with mutual privacy preservation in IoV,” Wei, vol 16, pp. 62-71, 4 2019.
[39] K. Fan, W. Jiang, Q. Luo and H. Li, “Cloud-based RFID Mutual Authentication Scheme for Efficient Privacy Preserving in IoV,” Journal of the Franklin Institute, 3 2019.
[40] H. H. R. Sherazi, R. Iqbal, F. Ahmad, Z. A. Khan and M. H. Chaudary, “DDoS attack detection: A key enabler for sustainable communication in internet of vehicles,” Sustainable Computing: Informatics and Systems, vol 23, pp. 13-20, 9 2019.