1,259 research outputs found

    Advancement in infotainment system in automotive sector with vehicular cloud network and current state of art

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    The automotive industry has been incorporating various technological advancement on top-end versions of the vehicle order to improvise the degree of comfortability as well as enhancing the safer driving system. Infotainment system is one such pivotal system which not only makes the vehicle smart but also offers abundance of information as well as entertainment to the driver and passenger. The capability to offer extensive relay of service through infotainment system is highly dependent on vehicular adhoc network as well as back end support of cloud environment. However, it is know that such legacy system of vehicular adhoc network is also characterized by various problems associated with channel capacity, latency, heterogeneous network processing, and many more. Therefore, this paper offers a comprehensive insight to the research work being carried out towards leveraging the infotainment system in order to obtain the true picture of strength, limitation, and open end problems associated with infotainment system

    Design and implement WSN/IoT smart parking management system using microcontroller

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    With the dramatic expansion of new networks such as Wireless Sensor Network (WSN) and Internet-of-Things (IoT), tremendous opportunities have been emerged to incorporate such technologies for valuable tasks. One of these tasks is the smart car parking where there is an imperative demand to manage the parkings in various facilities which may help drivers to save their time. Several research studies have addressed this task using wide range of approaches. However, the energy consumption is still a serious concern. This paper proposes a smart car parking based on cloud-based approach along with variety of sensors. Passive Infrared Sensors (PIRs) have been used to sense the object motion. While Light Dependent Resistor (LDR) sensors have been utilized to sense the light of the parking alarm and display inmformation regarding the occupied and non-occupied parking lots. Finally, multi-micro controller of Arduino have been exploited in order to transmit the information collected to the server. Finally, a prototype Android application has been developed in order to recieve the infromation from the server. Results of simulation showed the efficacy of the proposed method

    Cross-domain self-authentication based consortium blockchain for autonomous valet parking system

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    This paper proposed a cross-domain self-authentication scheme to address the “information isolated island” problem of users’ identities storage in servers and the “redundant registration problem” of users’ identities for Autonomous Valet Parking (AVP). This scheme adopts a decentralized anonymous authentication method to relieve the authentication center’s service load. Users are segregated into two categories to increase authentication efficiency: inexperienced and regular users. For the former, the paper explores a self-authentication mechanism based on verification parameters. Then, its valid personal information, pseudonym and public key, were stored in a consortium blockchain (PseIDChain) as the transaction records so that they can be securely shared among servers located in different domains. For the latter (regular users), an efficient authentication mechanism, searching users’ personal information on PseIDChain by the smart contract, was proposed. Security proof and simulation results show that the designed scheme has superior security to the existing schemes. Its authentication efficiency is 80.29% and 50.45% higher than the traditional anonymous and batch authentication schemes

    From Smart Parking Towards Autonomous Valet Parking: A Survey, Challenges and Future Works

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    Recently, we see an increasing number of vehicles coming into our lives, which makes finding car parks a difficult task. To overcome this challenge, efficient and advanced parking techniques are required, such as finding the proper parking slot, increasing users’ experience, dynamic path planning and congestion avoidance. To this end, this survey provides a detailed overview starting from Smart Parking (SP) towards the emerging Autonomous Valet Parking (AVP) techniques. Specially, the SP includes digitally enhanced parking, smart routing, high density parking and vacant slot detection solutions. Moreover, the AVP involves Short-range Autonomous Valet Parking (SAVP) and Long-range Autonomous Valet Parking (LAVP). Finally, open issues and future work are provided

    Effective Privacy-Preserving Mechanisms for Vehicle-to-Everything Services

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    Owing to the advancement of wireless communication technologies, drivers can rely on smart connected vehicles to communicate with each other, roadside units, pedestrians, and remote service providers to enjoy a large amount of vehicle-to-everything (V2X) services, including navigation, parking, ride hailing, and car sharing. These V2X services provide different functions for bettering travel experiences, which have a bunch of benefits. In the real world, even without smart connected vehicles, drivers as users can utilize their smartphones and mobile applications to access V2X services and connect their smartphones to vehicles through some interfaces, e.g., IOS Carplay and Android Auto. In this way, they can still enjoy V2X services through modern car infotainment systems installed on vehicles. Most of the V2X services are data-centric and data-intensive, i.e., users have to upload personal data to a remote service provider, and the service provider can continuously collect a user's data and offer personalized services. However, the data acquired from users may include users' sensitive information, which may expose user privacy and cause serious consequences. To protect user privacy, a basic privacy-preserving mechanism, i.e, anonymization, can be applied in V2X services. Nevertheless, a big obstacle arises as well: user anonymization may affect V2X services' availability. As users become anonymous, users may behave selfishly and maliciously to break the functions of a V2X service without being detected and the service may become unavailable. In short, there exist a conflict between privacy and availability, which is caused by different requirements of users and service providers. In this thesis, we have identified three major conflicts between privacy and availability for V2X services: privacy vs. linkability, privacy vs. accountability, privacy vs. reliability, and then have proposed and designed three privacy-preserving mechanisms to resolve these conflicts. Firstly, the thesis investigates the conflict between privacy and linkability in an automated valet parking (AVP) service, where users can reserve a parking slot for their vehicles such that vehicles can achieve automated valet parking. As an optional privacy-preserving measure, users can choose to anonymize their identities when booking a parking slot for their vehicles. In this way, although user privacy is protected by anonymization, malicious users can repeatedly send parking reservation requests to a parking service provider to make the system unavailable (i.e., "Double-Reservation Attack"). Aiming at this conflict, a security model is given in the thesis to clearly define necessary privacy requirements and potential attacks in an AVP system, and then a privacy-preserving reservation scheme has been proposed based on BBS+ signature and zero-knowledge proof. In the proposed scheme, users can keep anonymous since users only utilize a one-time unlinkable token generated from his/her anonymous credential to achieve parking reservations. In the meantime, by utilizing proxy re-signature, the scheme can also guarantee that one user can only have one token at a time to resist against "Double-Reservation Attack". Secondly, the thesis investigates the conflict between privacy and accountability in a car sharing service, where users can conveniently rent a shared car without human intervention. One basic demand for car sharing service is to check the user's identity to determine his/her validity and enable the user to be accountable if he/she did improper behavior. If the service provider allows users to hide their identities and achieve anonymization to protect user privacy, naturally the car sharing service is unavailable. Aiming at this conflict, a decentralized, privacy-preserving, and accountable car sharing architecture has been proposed in the thesis, where multiple dynamic validation servers are employed to build decentralized trust for users. Under this architecture, the thesis proposes a privacy-preserving identity management scheme to assist in managing users' identities in a dynamic manner based on a verifiable secret sharing/redistribution technique, i.e. the validation servers who manage users' identities are dynamically changed with the time advancing. Moreover, the scheme enables a majority of dynamic validation servers to recover the misbehaving users' identities and guarantees that honest users' identities are confidential to achieve privacy preservation and accountability at the same time. Thirdly, the thesis investigates the conflict between privacy and reliability in a road condition monitoring service, where users can report road conditions to a monitoring service provider to help construct a live map based on crowdsourcing. Usually, a reputation-based mechanism is applied in the service to measure a user's reliability. However, this mechanism cannot be easily integrated with a privacy-preserving mechanism based on user anonymization. When users are anonymous, they can upload arbitrary reports to destroy the service quality and make the service unavailable. Aiming at this conflict, a privacy-preserving crowdsourcing-based road condition monitoring scheme has been proposed in the thesis. By leveraging homomorphic commitments and PS signature, the scheme supports anonymous user reputation management without the assistance of any third-party authority. Furthermore, the thesis proposes several zero-knowledge proof protocols to ensure that a user can keep anonymous and unlinkable but a monitoring service provider can still judge the reliability of this user's report through his/her reputation score. To sum up, with more attention being paid to privacy issues, how to protect user privacy for V2X services becomes more significant. The thesis proposes three effective privacy-preserving mechanisms for V2X services, which resolve the conflict between privacy and availability and can be conveniently integrated into current V2X applications since no trusted third party authority is required. The proposed approaches should be valuable for achieving practical privacy preservation in V2X services

    Software Protection and Secure Authentication for Autonomous Vehicular Cloud Computing

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    Artificial Intelligence (AI) is changing every technology we deal with. Autonomy has been a sought-after goal in vehicles, and now more than ever we are very close to that goal. Vehicles before were dumb mechanical devices, now they are becoming smart, computerized, and connected coined as Autonomous Vehicles (AVs). Moreover, researchers found a way to make more use of these enormous capabilities and introduced Autonomous Vehicles Cloud Computing (AVCC). In these platforms, vehicles can lend their unused resources and sensory data to join AVCC. In this dissertation, we investigate security and privacy issues in AVCC. As background, we built our vision of a layer-based approach to thoroughly study state-of-the-art literature in the realm of AVs. Particularly, we examined some cyber-attacks and compared their promising mitigation strategies from our perspective. Then, we focused on two security issues involving AVCC: software protection and authentication. For the first problem, our concern is protecting client’s programs executed on remote AVCC resources. Such a usage scenario is susceptible to information leakage and reverse-engineering. Hence, we proposed compiler-based obfuscation techniques. What distinguishes our techniques, is that they are generic and software-based and utilize the intermediate representation, hence, they are platform agnostic, hardware independent and support different high level programming languages. Our results demonstrate that the control-flow of obfuscated code versions are more complicated making it unintelligible for timing side-channels. For the second problem, we focus on protecting AVCC from unauthorized access or intrusions, which may cause misuse or service disruptions. Therefore, we propose a strong privacy-aware authentication technique for users accessing AVCC services or vehicle sharing their resources with the AVCC. Our technique modifies robust function encryption, which protects stakeholder’s confidentiality and withstands linkability and “known-ciphertexts” attacks. Thus, we utilize an authentication server to search and match encrypted data by performing dot product operations. Additionally, we developed another lightweight technique, based on KNN algorithm, to authenticate vehicles at computationally limited charging stations using its owner’s encrypted iris data. Our security and privacy analysis proved that our schemes achieved privacy-preservation goals. Our experimental results showed that our schemes have reasonable computation and communications overheads and efficiently scalable

    When Things Matter: A Data-Centric View of the Internet of Things

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    With the recent advances in radio-frequency identification (RFID), low-cost wireless sensor devices, and Web technologies, the Internet of Things (IoT) approach has gained momentum in connecting everyday objects to the Internet and facilitating machine-to-human and machine-to-machine communication with the physical world. While IoT offers the capability to connect and integrate both digital and physical entities, enabling a whole new class of applications and services, several significant challenges need to be addressed before these applications and services can be fully realized. A fundamental challenge centers around managing IoT data, typically produced in dynamic and volatile environments, which is not only extremely large in scale and volume, but also noisy, and continuous. This article surveys the main techniques and state-of-the-art research efforts in IoT from data-centric perspectives, including data stream processing, data storage models, complex event processing, and searching in IoT. Open research issues for IoT data management are also discussed
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