A non-device specific framework for the development of forensic locational data analysis procedure for consumer grade small and embedded devices

Portable and wearable computing devices such as smart watches, navigation units, mobile phones, and tablet computers commonly ship with Global Navigation Satellite System (GNSS) supported locational awareness. Locational functionality is no longer limited to navigation specific devices such as satellite navigation devices and location tracking systems. Instead the use of these technologies has extended to become secondary functionality on many devices, including mobile phones, cameras, portable computers, and video game consoles. The increase in use of location aware technology is of use to forensic investigators as it has the potential to provide historic locational information. The evidentiary value of these devices to forensic investigators is currently limited due to the lack of available forensic tools and published methods to properly acquire and analyse these data sources. This research addresses this issue through the synthesis of common processes for the development of forensic procedure to acquire and interpret historic locational data from embedded, locationally aware devices. The research undertaken provides a framework for the generation of forensic procedure to enable the forensic extraction of historical locational data. The framework is device agnostic, relying instead on differential analysis and structured testing to produce a validated method for the extraction of locational history. This framework was evaluated against five devices, selected on a basis of market penetration, availability and a stage of deduplication. The examination of the framework took place in a laboratory developed specifically for the research. This laboratory replicates all identified sources of location data for the devices selected. In this case the laboratory is able to simulate cellular (2G and 3G), GNSS (NAVSTAR and GLONASS), and Wi-Fi locationing services. The laboratory is a closed-sky facility, meaning that the laboratory is contained within a faraday cage and all signals are produced and broadcast internally. Each selected device was run through a series of simulations. These simulations involved the broadcast of signals, replicating the travel of a specific path. Control data was established through the use of appropriate data recording systems, for each of the simulated location signals. On completion of the simulation, each device was forensically acquired and analysed in accordance with the proposed framework. For each experiment carried out against the five devices, the control and experimental data were compared. In this examination any divergence less than those expected for GNSS were ignored. Any divergence greater than this was examined to establish cause. Predictable divergence was accepted and non-predictable divergence would have been noted as a limitation. In all instances where data was recovered, all divergences were found to be predictable. Post analysis, the research found that the proposed framework was successful in producing locational forensic procedure in a non-device specific manner. This success was confirmed for all the devices tested

Cyber Threats Facing Autonomous and Connected Vehicles: Future Challenges

Vehicles are currently being developed and sold with increasing levels of connectivity and automation. As with all networked computing devices, increased connectivity often results in a heightened risk of a cyber security attack. Furthermore, increased automation exacerbates any risk by increasing the opportunities for the adversary to implement a successful attack. In this paper, a large volume of publicly accessible literature is reviewed and compartmentalised based on the vulnerabilities identified and mitigation techniques developed. This review highlighted that the majority of research is reactive and vulnerabilities are often discovered by friendly adversaries (white-hat hackers). Many gaps in the knowledge base were identified. Priority should be given to address these knowledge gaps to minimise future cyber security risks in the connected and autonomous vehicle sector

Driving whilst using in-vehicle information systems (IVIS): benchmarking the impairment to alcohol

Using the lane change task (LCT) a comparison of driving performance was made between normal (baseline) driving, driving whilst using an in-vehicle information system (IVIS) and driving while intoxicated at the UK blood alcohol level (80 mg per 100 ml). The results provided clear evidence for impaired performance of the LCT when performing an IVIS task in comparison to both baseline (LCT alone) and alcohol conditions. However, the LCT was found to be insensitive to the effects of alcohol in the absence of a secondary task. It is concluded that LCT performance can be impaired more when undertaking certain IVIS tasks than by having a blood alcohol level at the UK legal limit but the LCT requires further development before it can be used as a convincing proxy for the driving task

A systematic literature review on the relationship between autonomous vehicle technology and traffic-related mortality.

학위논문(석사) -- 서울대학교대학원 : 행정대학원 글로벌행정전공, 2023. 2. 최태현.The society is anticipated to gain a lot from Autonomous Vehicles (AV), such as improved traffic flow and a decrease in accidents. They heavily rely on improvements in various Artificial Intelligence (AI) processes and strategies. Though some researchers in this field believe AV is the key to enhancing safety, others believe AV creates new challenges when it comes to ensuring the security of these new technology/systems and applications. The article conducts a systematic literature review on the relationship between autonomous vehicle technology and traffic-related mortality. According to inclusion and exclusion criteria, articles from EBSCO, ProQuest, IEEE Explorer, Web of Science were chosen, and they were then sorted. The findings reveal that the most of these publications have been published in advanced transport-related journals. Future improvements in the automobile industry and the development of intelligent transportation systems could help reduce the number of fatal traffic accidents. Technologies for autonomous cars provide effective ways to enhance the driving experience and reduce the number of traffic accidents. A multitude of driving-related problems, such as crashes, traffic, energy usage, and environmental pollution, will be helped by autonomous driving technology. More research is needed for the significant majority of the studies that were assessed. They need to be expanded so that they can be tested in real-world or computer-simulated scenarios, in better and more realistic scenarios, with better and more data, and in experimental designs where the results of the proposed strategy are compared to those of industry standards and competing strategies. Therefore, additional study with improved methods is needed. Another major area that requires additional research is the moral and ethical choices made by AVs. Government, policy makers, manufacturers, and designers all need to do many actions in order to deploy autonomous vehicles on the road effectively. The government should develop laws, rules, and an action plan in particular. It is important to create more effective programs that might encourage the adoption of emerging technology in transportation systems, such as driverless vehicles. In this regard, user perception becomes essential since it may inform designers about current issues and observations made by people. The perceptions of autonomous car users in developing countries like Azerbaijan haven't been thoroughly studied up to this point. The manufacturer has to fix the system flaw and needs a good data set for efficient operation. In the not-too-distant future, the widespread use of highly automated vehicles (AVs) may open up intriguing new possibilities for resolving persistent issues in current safety-related research. Further research is required to better understand and quantify the significant policy implications of Avs, taking into consideration factors like penetration rate, public adoption, technological advancements, traffic patterns, and business models. It only needs to take into account peer-reviewed, full-text journal papers for the investigation, but it's clear that a larger database and more documents would provide more results and a more thorough analysis.자율주행차(AV)를 통해 교통 흐름이 개선되고 사고가 줄어드는 등 사회가 얻는 것이 많을 것으로 예상된다. 그들은 다양한 인공지능(AI) 프로세스와 전략의 개선에 크게 의존한다. 이 분야의 일부 연구자들은 AV가 안전성을 향상시키는 열쇠라고 믿지만, 다른 연구자들은 AV가 이러한 새로운 기술/시스템 및 애플리케이션의 보안을 보장하는 것과 관련하여 새로운 문제를 야기한다고 믿는다. 이 논문은 자율주행차 기술과 교통 관련 사망률 사이의 관계에 대한 체계적인 문헌 검토를 수행한다. 포함 및 제외 기준에 따라 EBSCO, ProQuest, IEEE Explorer 및 Web of Science의 기사를 선택하고 분류했다.연구 결과는 이러한 출판물의 대부분이 고급 운송 관련 저널에 게재되었음을 보여준다. 미래의 자동차 산업의 개선과 지능형 교통 시스템의 개발은 치명적인 교통 사고의 수를 줄이는 데 도움이 될 수 있다. 자율주행 자동차 기술은 운전 경험을 향상시키고 교통 사고의 수를 줄일 수 있는 효과적인 방법을 제공한다. 충돌, 교통, 에너지 사용, 환경 오염과 같은 수많은 운전 관련 문제들은 자율 주행 기술에 의해 도움을 받을 것이다. 평가된 대부분의 연구에 대해 더 많은 연구가 필요하다. 실제 또는 컴퓨터 시뮬레이션 시나리오, 더 좋고 현실적인 시나리오, 더 좋고 더 많은 데이터, 그리고 제안된 전략 결과가 산업 표준 및 경쟁 전략의 결과와 비교되는 실험 설계에서 테스트될 수 있도록 확장되어야 한다. 따라서 개선된 방법에 대한 추가 연구가 필요하다. 추가 연구가 필요한 또 다른 주요 분야는 AV의 도덕적, 윤리적 선택이다. 정부, 정책 입안자, 제조업체 및 설계자는 모두 자율 주행 차량을 효과적으로 도로에 배치하기 위해 많은 조치를 취해야 한다. 정부는 특히 법, 규칙, 실행 계획을 개발해야 한다. 운전자 없는 차량과 같은 운송 시스템에서 새로운 기술의 채택을 장려할 수 있는 보다 효과적인 프로그램을 만드는 것이 중요하다. 이와 관련하여, 설계자에게 현재 이슈와 사람에 의한 관찰을 알려줄 수 있기 때문에 사용자 인식이 필수적이 된다.제조업체는 시스템 결함을 수정해야 하며 효율적인 작동을 위해 좋은 데이터 세트가 필요하다. 멀지 않은 미래에, 고도로 자동화된 차량(AV)의 광범위한 사용은 현재의 안전 관련 연구에서 지속적인 문제를 해결하기 위한 흥미로운 새로운 가능성을 열어줄 수 있다. 보급률, 공공 채택, 기술 발전, 교통 패턴 및 비즈니스 모델과 같은 요소를 고려하여 Avs의 중요한 정책 영향을 더 잘 이해하고 정량화하기 위한 추가 연구가 필요하다. 조사를 위해 동료 검토를 거친 전문 저널 논문만 고려하면 되지만, 데이터베이스가 커지고 문서가 많아지면 더 많은 결과와 더 철저한 분석이 제공될 것이 분명하다.Abstract 3 Table of Contents 6 List of Tables 7 List of Figures 7 List of Appendix 7 CHAPTER 1: INTRODUCTION 8 1.1. Background 8 1.2. Purpose of Research 13 CHAPTER 2: AUTONOMOUS VEHICLES 21 2.1. Intelligent Traffic Systems 21 2.2. System Architecture for Autonomous Vehicles 22 2.3. Key components in AV classification 27 CHAPTER 3: METHODOLOGY AND DATA COLLECTION PROCEDURE 35 CHAPTER 4: FINDINGS AND DISCUSSION 39 4.1. RQ1: Do autonomous vehicles reduce traffic-related deaths 40 4.2. RQ2: Are there any challenges to using autonomous vehicles 63 4.3. RQ3: As a developing country, how effective is the use of autonomous vehicles for reducing traffic mortality 72 CHAPTER 5: CONCLUSION 76 5.1. Summary 76 5.2. Implications and Recommendations 80 5.3. Limitation of the study 91 Bibliography 93 List of Tables Table 1: The 6 Levels of Autonomous Vehicles Table 2: Search strings Table 3: Inclusion and exclusion criteria List of Figures Figure 1: Traffic Death Comparison with Europe Figure 2: Research strategy and study selection process List of Appendix Appendix 1: List of selected articles석

A Systematic Literature Review on Automotive Digital Forensics: Challenges, Technical Solutions and Data Collection

A modern vehicle has a complex internal architecture and is wirelessly connected to the Internet, other vehicles, and the infrastructure. The risk of cyber attacks and other criminal incidents along with recent road accidents caused by autonomous vehicles calls for more research on automotive digital forensics. Failures in automated driving functions can be caused by hardware and software failures and cyber security issues. Thus, it is imperative to be able to determine and investigate the cause of these failures, something which requires trustable data. However, automotive digital forensics is a relatively new field for the automotive where most existing self-monitoring and diagnostic systems in vehicles only monitor safety-related events. To the best of our knowledge, our work is the first systematic literature review on the current research within this field. We identify and assess over 300 papers published between 2006 - 2021 and further map the relevant papers to different categories based on identified focus areas to give a comprehensive overview of the forensics field and the related research activities. Moreover, we identify forensically relevant data from the literature, link the data to categories, and further map them to required security properties and potential stakeholders. Our categorization makes it easy for practitioners and researchers to quickly find relevant work within a particular sub-field of digital forensics. We believe our contributions can guide digital forensic investigations in automotive and similar areas, such as cyber-physical systems and smart cities, facilitate further research, and serve as a guideline for engineers implementing forensics mechanisms

Evaluation of the utility and performance of an autonomous surface vehicle for mobile monitoring of waterborne biochemical agents

Real-time water quality monitoring is crucial due to land utilization increases which can negatively impact aquatic ecosystems from surface water runoff. Conventional monitoring methodologies are laborious, expensive, and spatio-temporally limited. Autonomous surface vehicles (ASVs), equipped with sensors/instrumentation, serve as mobile sampling stations that reduce labor and enhance data resolution. However, ASV autopilot navigational accuracy is affected by environmental forces (wind, current, and waves) that can alter trajectories of planned paths and negatively affect spatio-temporal resolution of water quality data. This study demonstrated a commercially available solar powered ASV equipped with a multi-sensor payload ability to operate autonomously to accurately and repeatedly maintain established A-B line transects under varying environmental conditions, where lateral deviation from a planned linear route was measured and expressed as cross-track error (XTE). This work provides a framework for development of spatial/temporal resolution limitations of ASVs for real-time monitoring campaigns and future development of in-situ sampling technologies

Garmin satnav forensic methods and artefacts: an exploratory study.

Over ten years ago, major changes in the Global Positioning System (GPS) technology led to its explosion in popularity. GPS devices are now ubiquitous, escorting their users everywhere they go, and potentially recording the entirety of their whereabouts. As such, they represent invaluable assets to forensic practitioners. Amongst the different brands, Garmin and Tom-Tom are by far the most widespread, and are regularly encountered as part of investigations. GPS forensics is a relatively new field of study, in which tools and methodologies are very reliant upon the device itself. Whereas several tools and methodologies have been developed to address Tom-Tom devices, the lack of knowledge concerning Garmin devices may lead to investigators missing evidence. This thesis aims to explore forensic methods applicable to Garmin devices, and highlight locational artefacts located on them, which may be of use in a digital investigation. To do so, three series of experiments have been designed and performed, intending to document the behaviour of the device, the methods to acquire and analyse its content efficiently, and the reliability of the data recovered. This thesis shows successful acquisition of data from a range of Garmin devices. It also demonstrates that various forensic artefacts can be recovered from Garmin devices, with the results compared to similar research into Tom-Tom GPS devices. This highlights that Garmin devices potentially have a greater forensic potential than Tom-Tom devices, as it was found they typically hold up to 6 month of their user’s daily locations, regardless of whether the navigation was in use or not. Using carving techniques and file signatures discovered through the project, this thesis shows how to recover further location tracking data from unallocated clusters. However, it also highlights that such information should be considered carefully, since the work also demonstrates that the data can be manipulated using anti-forensic techniques

Garmin satnav forensic methods and artefacts: an exploratory study.

Over ten years ago, major changes in the Global Positioning System (GPS) technology led to its explosion in popularity. GPS devices are now ubiquitous, escorting their users everywhere they go, and potentially recording the entirety of their whereabouts. As such, they represent invaluable assets to forensic practitioners. Amongst the different brands, Garmin and Tom-Tom are by far the most widespread, and are regularly encountered as part of investigations. GPS forensics is a relatively new field of study, in which tools and methodologies are very reliant upon the device itself. Whereas several tools and methodologies have been developed to address Tom-Tom devices, the lack of knowledge concerning Garmin devices may lead to investigators missing evidence. This thesis aims to explore forensic methods applicable to Garmin devices, and highlight locational artefacts located on them, which may be of use in a digital investigation. To do so, three series of experiments have been designed and performed, intending to document the behaviour of the device, the methods to acquire and analyse its content efficiently, and the reliability of the data recovered. This thesis shows successful acquisition of data from a range of Garmin devices. It also demonstrates that various forensic artefacts can be recovered from Garmin devices, with the results compared to similar research into Tom-Tom GPS devices. This highlights that Garmin devices potentially have a greater forensic potential than Tom-Tom devices, as it was found they typically hold up to 6 month of their user’s daily locations, regardless of whether the navigation was in use or not. Using carving techniques and file signatures discovered through the project, this thesis shows how to recover further location tracking data from unallocated clusters. However, it also highlights that such information should be considered carefully, since the work also demonstrates that the data can be manipulated using anti-forensic techniques