Visible to the public Biblio

Filters: Keyword is V2X  [Clear All Filters]
2022-06-09
Karim, Hassan, Rawat, Danda B..  2021.  Evaluating Machine Learning Classifiers for Data Sharing in Internet of Battlefield Things. 2021 IEEE Symposium Series on Computational Intelligence (SSCI). :01–07.
The most widely used method to prevent adversaries from eavesdropping on sensitive sensor, robot, and war fighter communications is mathematically strong cryptographic algorithms. However, prevailing cryptographic protocol mandates are often made without consideration of resource constraints of devices in the internet of Battlefield Things (IoBT). In this article, we address the challenges of IoBT sensor data exchange in contested environments. Battlefield IoT (Internet of Things) devices need to exchange data and receive feedback from other devices such as tanks and command and control infrastructure for analysis, tracking, and real-time engagement. Since data in IoBT systems may be massive or sparse, we introduced a machine learning classifier to determine what type of data to transmit under what conditions. We compared Support Vector Machine, Bayes Point Match, Boosted Decision Trees, Decision Forests, and Decision Jungles on their abilities to recommend the optimal confidentiality preserving data and transmission path considering dynamic threats. We created a synthesized dataset that simulates platoon maneuvers and IED detection components. We found Decision Jungles to produce the most accurate results while requiring the least resources during training to produce those results. We also introduced the JointField blockchain network for joint and allied force data sharing. With our classifier, strategists, and system designers will be able to enable adaptive responses to threats while engaged in real-time field conflict.
2022-03-01
Pollicino, Francesco, Ferretti, Luca, Stabili, Dario, Marchetti, Mirco.  2021.  Accountable and privacy-aware flexible car sharing and rental services. 2021 IEEE 20th International Symposium on Network Computing and Applications (NCA). :1–7.
The transportation sector is undergoing rapid changes to reduce pollution and increase life quality in urban areas. One of the most effective approaches is flexible car rental and sharing to reduce traffic congestion and parking space issues. In this paper, we envision a flexible car sharing framework where vehicle owners want to make their vehicles available for flexible rental to other users. The owners delegate the management of their vehicles to intermediate services under certain policies, such as municipalities or authorized services, which manage the due infrastructure and services that can be accessed by users. We investigate the design of an accountable solution that allow vehicles owners, who want to share their vehicles securely under certain usage policies, to control that delegated services and users comply with the policies. While monitoring users behavior, our approach also takes care of users privacy, preventing tracking or profiling procedures by other parties. Existing approaches put high trust assumptions on users and third parties, do not consider users' privacy requirements, or have limitations in terms of flexibility or applicability. We propose an accountable protocol that extends standard delegated authorizations and integrate it with Security Credential Management Systems (SCMS), while considering the requirements and constraints of vehicular networks. We show that the proposed approach represents a practical approach to guarantee accountability in realistic scenarios with acceptable overhead.
2021-06-28
Dahiya, Rohan, Jiang, Frank, Doss, Robin Ram.  2020.  A Feedback-Driven Lightweight Reputation Scheme for IoV. 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom). :1060–1068.
Most applications of Internet of Vehicles (IoVs) rely on collaboration between nodes. Therefore, false information flow in-between these nodes poses the challenging trust issue in rapidly moving IoV nodes. To resolve this issue, a number of mechanisms have been proposed in the literature for the detection of false information and establishment of trust in IoVs, most of which employ reputation scores as one of the important factors. However, it is critical to have a robust and consistent scheme that is suitable to aggregate a reputation score for each node based on the accuracy of the shared information. Such a mechanism has therefore been proposed in this paper. The proposed system utilises the results of any false message detection method to generate and share feedback in the network, this feedback is then collected and filtered to remove potentially malicious feedback in order to produce a dynamic reputation score for each node. The reputation system has been experimentally validated and proved to have high accuracy in the detection of malicious nodes sending false information and is robust or negligibly affected in the presence of spurious feedback.
2021-05-13
Camenisch, Jan, Drijvers, Manu, Lehmann, Anja, Neven, Gregory, Towa, Patrick.  2020.  Zone Encryption with Anonymous Authentication for V2V Communication. 2020 IEEE European Symposium on Security and Privacy (EuroS P). :405—424.

Vehicle-to-vehicle (V2V) communication systems are currently being prepared for real-world deployment, but they face strong opposition over privacy concerns. Position beacon messages are the main culprit, being broadcast in cleartext and pseudonymously signed up to 10 times per second. So far, no practical solutions have been proposed to encrypt or anonymously authenticate V2V messages. We propose two cryptographic innovations that enhance the privacy of V2V communication. As a core contribution, we introduce zone-encryption schemes, where vehicles generate and authentically distribute encryption keys associated to static geographic zones close to their location. Zone encryption provides security against eavesdropping, and, combined with a suitable anonymous authentication scheme, ensures that messages can only be sent by genuine vehicles, while adding only 224 Bytes of cryptographic overhead to each message. Our second contribution is an authentication mechanism fine-tuned to the needs of V2V which allows vehicles to authentically distribute keys, and is called dynamic group signatures with attributes. Our instantiation features unlimited locally generated pseudonyms, negligible credential download-and-storage costs, identity recovery by a trusted authority, and compact signatures of 216 Bytes at a 128-bit security level.

2020-11-02
Ivanov, I, Maple, C, Watson, T, Lee, S.  2018.  Cyber security standards and issues in V2X communications for Internet of Vehicles. Living in the Internet of Things: Cybersecurity of the IoT – 2018. :1—6.

Significant developments have taken place over the past few years in the area of vehicular communication systems in the ITS environment. It is vital that, in these environments, security is considered in design and implementation since compromised vulnerabilities in one vehicle can be propagated to other vehicles, especially given that V2X communication is through an ad-hoc type network. Recently, many standardisation organisations have been working on creating international standards related to vehicular communication security and the so-called Internet of Vehicles (IoV). This paper presents a discussion of current V2X communications cyber security issues and standardisation approaches being considered by standardisation bodies such as the ISO, the ITU, the IEEE, and the ETSI.

2018-09-05
Kang, K., Baek, Y., Lee, S., Son, S. H..  2017.  An Attack-Resilient Source Authentication Protocol in Controller Area Network. 2017 ACM/IEEE Symposium on Architectures for Networking and Communications Systems (ANCS). :109–118.

While vehicle to everything (V2X) communication enables safety-critical automotive control systems to better support various connected services to improve safety and convenience of drivers, they also allow automotive attack surfaces to increase dynamically in modern vehicles. Many researchers as well as hackers have already demonstrated that they can take remote control of the targeted car by exploiting the vulnerabilities of in-vehicle networks such as Controller Area Networks (CANs). For assuring CAN security, we focus on how to authenticate electronic control units (ECUs) in real-time by addressing the security challenges of in-vehicle networks. In this paper, we propose a novel and lightweight authentication protocol with an attack-resilient tree algorithm, which is based on one-way hash chain. The protocol can be easily deployed in CAN by performing a firmware update of ECU. We have shown analytically that the protocol achieves a high level of security. In addition, the performance of the proposed protocol is validated on CANoe simulator for virtual ECUs and Freescale S12XF used in real vehicles. The results show that our protocol is more efficient than other authentication protocol in terms of authentication time, response time, and service delay.

2018-03-05
Khan, J..  2017.  Vehicle Network Security Testing. 2017 Third International Conference on Sensing, Signal Processing and Security (ICSSS). :119–123.

In-vehicle networks like Controller Area Network, FlexRay, Ethernet are now subjected to huge security threats where unauthorized entities can take control of the whole vehicle. This can pose very serious threats including accidents. Security features like encryption, message authentication are getting implemented in vehicle networks to counteract these issues. This paper is proposing a set of novel validation techniques to ensure that vehicle network security is fool proof. Security validation against requirements, security validation using white box approach, black box approach and grey box approaches are put forward. Test system architecture, validation of message authentication, decoding the patterns from vehicle network data, using diagnostics as a security loophole, V2V V2X loopholes, gateway module security testing are considered in detail. Aim of this research paper is to put forward a set of tools and methods for finding and reporting any security loopholes in the in-vehicle network security implementation.