Hardware Security Primitives for Vehicles

Labrado, Carson; Thapliyal, Himanshu

doi:10.1109/mce.2019.2941392

Cited by 16 publications

(3 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The idea of the PUF is to generate a unique identifier from a challenge response pair (CRP) that is derived from the unique features inherited by the circuitry over the fabrication process. The complexity and the secureness of the PUF based schemes are reliant on the number of CRPs associated with them [88]. In addition to authentication, PUFs can be employed for secure storing.…”

Section: • Device Authenticationmentioning

confidence: 99%

See 1 more Smart Citation

Security Considerations for Internet of Things: A Survey

et al. 2020

View full text Add to dashboard Cite

Interconnecting "things" and devices that takes the form of wearables, sensors, actuators, mobiles, computers, meters, or even vehicles is a critical requirement for the current era. These inter-networked connections are serving the emerging applications home and building automation, smart cities and infrastructure, smart industries, and smart-everything. However, the security of these connected Internet of things (IoT) plays a centric role with no margin for error. After a review of the relevant, online literature on the topic and after looking at the market trends and developments, one can notice that there are still concerns with regard to security in IoT products and services. This paper is focusing on a survey on IoT security and aims to highlight the most significant problems related to safety and security in the IoT ecosystems. This survey identifies the general threat and attack vectors against IoT devices while highlighting the flaws and weak points that can lead to breaching the security. Furthermore, this paper presents solutions for remediation of the compromised security, as well as methods for risk mitigation, with prevention and improvement suggestions.

show abstract

Section: • Device Authenticationmentioning

confidence: 99%

“…In addition to authentication, PUFs can be employed for secure storing. New directives on PUFs can be found in [48,59,88,100,153].…”

Section: Security By Designmentioning

confidence: 99%

Security Considerations for Internet of Things: A Survey

et al. 2020

View full text Add to dashboard Cite

show abstract

“…This approach is constrained by the limited computing power of ECUs and the small payload size of CAN messages (8 Bytes). Proposed solutions include: adding hardware coprocessors to offload computation-intensive cryptographic algorithms from the ECU [31]; selectively adding coprocessors to a partial set of ECUs to meet timing constraints while minimizing cost [21]; truncating the MAC to reduce its length and performing successful authentication of several consecutively received messages [21,47]; dynamically adjusting the MAC size to maximize it while meeting timing constraints [54]; security-aware obfuscated priority assignment for CAN with Flexible Data-rate (CAN-FD) [16,53], and others. Despite these research advances, MA on the CAN bus is not yet widely adopted in the automotive industry due to its high cost or high complexity.…”

Section: Introductionmentioning

confidence: 99%

CAN Bus Intrusion Detection Based on Auxiliary Classifier GAN and Out-of-distribution Detection

Zhao

Chen

et al. 2022

ACM Trans. Embed. Comput. Syst.

View full text Add to dashboard Cite

The Controller Area Network (CAN) is a ubiquitous bus protocol present in the Electrical/Electronic (E/E) systems of almost all vehicles. It is vulnerable to a range of attacks once the attacker gains access to the bus through the vehicle’s attack surface. We address the problem of Intrusion Detection on the CAN bus, and present a series of methods based on two classifiers trained with Auxiliary Classifier Generative Adversarial Network (ACGAN) to detect and assign fine-grained labels to Known Attacks, and also detect the Unknown Attack class in a dataset containing a mixture of (Normal + Known Attacks + Unknown Attack) messages. The most effective method is a cascaded two-stage classification architecture, with the multi-class Auxiliary Classifier in the first stage for classification of Normal and Known Attacks, passing Out-of-Distribution (OOD) samples to the binary Real-Fake Classifier in the second stage for detection of the Unknown Attack class. Performance evaluation demonstrate that our method achieves both high classification accuracy and low runtime overhead, making it suitable for deployment in the resource-constrained in-vehicle environment.

show abstract

Distributed Intelligence in the Internet of Things: Challenges and Opportunities

et al. 2021

View full text Add to dashboard Cite

Widespread adoption of smart IoT devices is accelerating research for new techniques to make IoT applications secure, scalable, energy-efficient, and capable of working in mission-critical use cases, which require an ability to function offline. In this context, the novel combination of distributed ledger technology (DLT) and distributed intelligence (DI) is seen as a practical route towards the decentralisation of IoT architectures. This paper surveys DI techniques in IoT and commences by briefly explaining the need for DI, by proposing a comprehensive taxonomy of DI in IoT. This taxonomy is then used to review existing techniques and to investigate current challenges that require careful attention and consideration. Based on the taxonomy, IoT DI techniques can be classified into five categories based on the factors that support distributed functionality and data acquisition: cloud-computing, mist-computing, distributed-ledger-technology, service-oriented-computing and hybrid. Existing techniques are compared and categorized mainly based on related challenges, and the level of intelligence supported. We evaluate more than thirty current research efforts in this area. We define many significant functionalities that should be supported by DI frameworks and solutions. Our work assists system architects and developers to select the correct low-level communication techniques in an integrated IoT-to-DLT-to-cloud system architecture. The benefits and shortcomings of different DI approaches are presented, which will inspire future work into automatic hybridization and adaptation of DI mechanisms. Finally, open research issues for distributed intelligence in IoT are discussed.

show abstract

Hardware Security Primitives for Vehicles

Cited by 16 publications

References 9 publications

Security Considerations for Internet of Things: A Survey

Security Considerations for Internet of Things: A Survey

CAN Bus Intrusion Detection Based on Auxiliary Classifier GAN and Out-of-distribution Detection

Distributed Intelligence in the Internet of Things: Challenges and Opportunities

Contact Info

Product

Resources

About