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Can bus privacy? 


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Bus privacy is a critical concern in various contexts such as in-vehicle networks, public WiFi systems, and customized-bus sharing services. In the realm of in-vehicle networks, the lack of authentication and encryption in Controller Area Network (CAN) buses poses a risk of compromise by untrusted agents . Similarly, public WiFi spots on buses raise privacy concerns due to open access, with studies showing high probabilities of users being uniquely re-identified from leaked information . Moreover, in customized-bus sharing services, ride clustering for optimal bus routes can inadvertently expose users' locations and travel patterns, necessitating privacy-preserving schemes like fog computing and cryptographic techniques to safeguard user data without compromising clustering quality . These diverse scenarios highlight the importance of addressing bus privacy to ensure data security and user confidentiality in various transportation settings.

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Papers (4)Insight
Privacy-preserving ride clustering in customized-bus sharing is achieved through fog-assisted approach, ensuring user privacy by utilizing Paillier cryptosystem and randomization techniques.
Bus privacy can be compromised in large-scale bus WiFi systems, with high re-identification risks for users' connection and location data, but can be protected using the PB-HIDE algorithm.
ImageFed proposes a privacy-preserving IDS for CAN bus, utilizing federated CNN to protect vehicle data. It ensures robustness with high accuracy, low latency, and 99.54% f1-score.
Yes, bus privacy can be preserved in power systems using a distributed economic dispatch method based on KKT optimality conditions and iteration functions, as outlined in the paper.

Related Questions

CAN bus in electric vehicles?5 answersThe Controller Area Network (CAN) bus plays a crucial role in electric vehicles, serving as a legacy protocol for in-vehicle network communication. It is known for its simplicity, robustness, and real-time system suitability. However, the CAN bus protocol lacks a message authentication mechanism, making it vulnerable to cyberattacks. To address this issue, a new anomaly detection model based on a modified one-class support vector machine has been proposed, showcasing superior performance in detecting anomalies compared to other existing algorithms. Additionally, the concept of a modular bus has been introduced to overcome limitations in conventional automotive architectures, enabling users to easily upgrade vehicles, change option packages, and interchange components across different vehicle models. This highlights the importance of CAN bus technology in enhancing the functionality and adaptability of electric vehicles.
HOW TO PROTECT personal PRIVACY FROM gps tracker?5 answersTo protect personal privacy from GPS trackers, several methods have been proposed. One approach is to obfuscate the Point of Interest (POI) by generating a pseudo location identifier that represents the semantic meaning of the POI without revealing its geographic location. Another method involves generalizing and suppressing GPS tracks in sparsely populated areas, concealing stay points, and limiting the amount of information that could leak if re-identification occurs. Additionally, a framework for Location-Based Services Management (LBSM) has been proposed, which provides multi-level location accuracy (LA) to different apps based on their properties and user preferences. Anonymization of car GPS traces can also be achieved by preserving the anonymity of the road graph while accurately projecting GPS locations onto graph edges. It is important to note that traditional access-control schemes may not be sufficient in protecting privacy, as unauthorized users can predict future movements based on previous GPS traces.
Can bus attacks?5 answersCAN bus attacks are a significant concern in the security of in-vehicle communication systems. The deterministic nature of Controller Area Networks (CAN) exposes timing information about task executions and message transmissions, making them vulnerable to schedule-based attacks and denial-of-service attacks. To address this, researchers have proposed various security measures, including the use of Intrusion Detection Systems (IDS) specifically designed for CAN networks. These IDSs utilize statistical characteristics and anomaly detection techniques to identify and mitigate attacks, such as fuzzy, merge, and denial-of-service attacks, with low false-positive rates. Additionally, an improved isolation forest method with data mass (MS-iForest) has been proposed for data tampering attack detection in the CAN bus network. This method shows promising results in terms of detecting anomalies and can be used as part of an intrusion detection system for in-vehicle security.
Can bus safety?5 answersCAN bus safety is a critical concern in various domains such as automobiles, vehicle-mounted networks, trains, and charging piles. Several methods and devices have been proposed to ensure the safety of CAN bus communication. These include safety test methods for identifying and analyzing bus data, protection methods for interface and gateway safety, encryption methods for data messages, and safety access methods for vehicle-mounted communication systems. These approaches aim to prevent bus faults, ensure data integrity, enhance encryption security, and detect safety problems such as tampering and denial of service attacks. The use of advanced algorithms and protocols, such as ant colony algorithms, has also been explored to improve the efficiency of safety detection in charging pile CAN protocols.
“privacy calculus” of self-driving cars?5 answersThe "privacy calculus" of self-driving cars is an important consideration in the development and implementation of autonomous vehicles. The use of big data from onboard vehicular systems can help determine liability in accidents, streamline insurance pricing, motivate better driving practices, and improve safety, while minimizing the impact on privacy. However, the evolution of road safety and traffic management through information technology raises concerns about security and privacy that have been overlooked by the research community. Vehicular ad hoc networks (VANETs) in future vehicles, including autonomous cars, may expose motorists to surveillance and privacy breaches. Understanding the cultural intricacies of SNS users is vital for motivating self-disclosure, but existing research offers limited insights into the role of culture in self-disclosure decisions. Overall, the privacy calculus of self-driving cars involves balancing the benefits of data utilization with the need to protect privacy and security.
What are the challenges to implementing a safety-related privacy scheme for VANET data?0 answersImplementing a safety-related privacy scheme for VANET data faces several challenges. One challenge is ensuring the reliability and security of shared data. Another challenge is protecting the privacy of participants, including their location and identity information. Additionally, there is a need to establish proper authentication and security associations for vehicles to prevent compromise of message confidentiality. Moreover, the openness of the wireless channel and the sensitivity of traffic information make data transmission in VANET vulnerable to leakage and attack. Finally, there is a need to balance geographical location protection and semantic location protection in order to effectively protect vehicle trajectory in VANET.

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