scholarly journals Advanced Temperature-Varied ECU Fingerprints for Source Identification and Intrusion Detection in Controller Area Networks

2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Miaoqing Tian ◽  
Ruobing Jiang ◽  
Haipeng Qu ◽  
Qian Lu ◽  
Xiaoyun Zhou
Keyword(s):  
Intrusion Detection ◽  
Source Identification ◽  
Experimental Studies ◽  
Physical Feature ◽  
Area Network ◽  
Temperature Changes ◽  
Controller Area Networks ◽  
Control Units ◽  
And Performance ◽  
Wireless Interfaces

External wireless interfaces and the lack of security design of controller area network (CAN) standards make it vulnerable to CAN-targeting attacks. Unfortunately, various defense solutions have been proposed merely to detect CAN intrusion attacks, while only a few works are devoted to intrusion source identification. Demonstrated by our experimental studies, the most advanced IDS with intrusion source identification, which is based on the physical feature fingerprints of the in-vehicle Electronic Control Units (ECUs), will fail when the temperature changes. In this paper, we innovatively propose temperature-varied fingerprinting, called TVF, for CAN intrusion detection and intrusion source identification. Motivated by the remarkable observation that the physical feature of an ECU, i.e., its clock offset, changes linearly with the temperature of ECUs, the concept of temperature-varied fingerprints is proposed. Then, for a severe intrusion case, we provide an advanced TVF for further supplemented and expanded. The proposed advanced temperature-varied fingerprinting is implemented, and extensive performance evaluation experiments are conducted in both CAN bus prototype and real vehicles. The experimental results illustrate the effectiveness and performance of advanced TVF.

scholarly journals A Real-time Anomaly-based Intrusion Detection System for Automotive Controller Area Networks

2020 ◽  
Author(s):  
Luís Felipe Prado D'Andrada ◽  
Paulo Freitas de Araujo-Filho ◽  
Divanilson Rodrigo Campelo
Keyword(s):  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Detection System ◽  
True Positive Rate ◽  
Detection Algorithm ◽  
Cyber Attacks ◽  
Area Network ◽  
Controller Area Networks ◽  
Positive Rate ◽  
Promising Solution

The Controller Area Network (CAN) is the most pervasive in-vehiclenetwork technology in cars. However, since CAN was designed with no securityconcerns, solutions to mitigate cyber attacks on CAN networks have been pro-posed. Prior works have shown that detecting anomalies in the CAN networktraffic is a promising solution for increasing vehicle security. One of the mainchallenges in preventing a malicious CAN frame transmission is to be able todetect the anomaly before the end of the frame. This paper presents a real-timeanomaly-based Intrusion Detection System (IDS) capable of meeting this dead-line by using the Isolation Forest detection algorithm implemented in a hardwaredescription language. A true positive rate higher than 99% is achieved in testscenarios. The system requires less than 1μs to evaluate a frame’s payload, thusbeing able to detect the anomaly before the end of the frame.

Towards an Integrated Vehicle Management System in DriveOS

2021 ◽  
Vol 20 (5s) ◽  
pp. 1-24
Author(s):  
Soham Sinha ◽  
Richard West
Keyword(s):  
Real Time ◽  
Low Cost ◽  
Sensor Data ◽  
Area Network ◽  
Driver Assistance ◽  
Separation Kernel ◽  
Control Units ◽  
Embedded Pc ◽  
And Performance ◽  
Vehicle Management

Modern automotive systems feature dozens of electronic control units (ECUs) for chassis, body and powertrain functions. These systems are costly and inflexible to upgrade, requiring ever increasing numbers of ECUs to support new features such as advanced driver assistance (ADAS), autonomous technologies, and infotainment. To counter these challenges, we propose DriveOS, a safe, secure, extensible, and timing-predictable system for modern vehicle management in a centralized platform. DriveOS is based on a separation kernel, where timing and safety-critical ECU functions are implemented in a real-time OS (RTOS) alongside non-critical software in Linux or Android. The system enforces the separation, or partitioning, of both software and hardware among different OSes. DriveOS runs on a relatively low-cost embedded PC-class platform, supporting multiple cores and hardware virtualization capabilities. Instrument cluster, in-vehicle infotainment and advanced driver assistance system services are implemented in a Yocto Linux guest, which communicates with critical real-time services via secure shared memory. The RTOS manages a real-time controller area network (CAN) interface that is inaccessible to Linux services except via well-defined and legitimate communication channels. In this work, we integrate three Qt-based services written for Yocto Linux, running in parallel with a real-time longitudinal controller task and multiple CAN bus concentrators, for vehicular sensor data processing and actuation. We demonstrate the benefits and performance of DriveOS with a hardware-in-the-loop CARLA simulation using a real car dataset.

scholarly journals A Scalable Security Protocol for Intravehicular Controller Area Network

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Zi-An Zhao ◽  
Yu Sun ◽  
Dawei Li ◽  
Jian Cui ◽  
Zhenyu Guan ◽  
...  
Keyword(s):  
Secure Communication ◽  
Large Scale ◽  
Controller Area Network ◽  
Security Protocol ◽  
Area Network ◽  
Computation Efficiency ◽  
Control Units ◽  
Security Properties ◽  
New Type ◽  
Wireless Interfaces

Intravehicular communication relies on controller area network (CAN) protocol to deliver messages and instructions among different electronic control units (ECU). Unfortunately, inherent defects in CAN include the absence of confidentiality and integrity mechanism, enabling adversaries to launch attacks from wired or wireless interfaces. Although various CAN cryptographic protocols have been proposed for entity authentication and secure communication, the redundancy in the key establishment phase weakens their availability in large-scale CAN. In this paper, we propose a scalable security protocol suite for intravehicular networks and reduce the communication costs significantly. A new type of attack, suspension attack, is identified for the existing protocols and mitigated in our protocol by leveraging a global counter scheme. We formally verify the security properties of the proposed protocol suite through the AVISPA tool. The simulation results indicate that the communication and computation efficiency are improved in our protocol.

Extracellular Proteins as Enterobacterial Thermometers

2003 ◽  
Vol 86 (1-2) ◽  
pp. 139-156 ◽  
Author(s):  
Robin J. Rowbury
Keyword(s):  
Thermal Stress ◽  
Heat Shock ◽  
Stress Responses ◽  
Direct Evidence ◽  
Experimental Studies ◽  
Extracellular Proteins ◽  
Temperature Changes ◽  
Induction Components ◽  
Cellular Components ◽  
Thermal Stimuli

Biological thermometers are cellular components or structures which sense increasing temperatures, interaction of the thermometer and the thermal stress bringing about the switching-on of inducible responses, with gradually enhanced levels of response induction following gradually increasing temperatures. In enterobacteria, for studies of such thermometers, generally induction of heat shock protein (HSP) synthesis has been examined, with experimental studies aiming to establish (often indirectly) how the temperature changes which initiate HSP synthesis are sensed; numerous other processes and responses show graded induction as temperature is increased, and how the temperature changes which induce these are sensed is also of interest. Several classes of intracellular component and structure have been proposed as enterobacterial thermometers, with the ribosome and the DnaK chaperone being the most favoured, although for many of the proposed intracellular thermometers, most of the evidence for their functioning in this way is indirect. In contrast to the above, the studies reviewed here firmly establish that for four distinct stress responses, which are switched-on gradually as temperature increases, temperature changes are sensed by extracellular components (extracellular sensing components, ESCs) i.e. there is firm and direct evidence for the occurrence of extracellular thermometers. All four thermometers described here are proteins, which appear to be distinct and different from each other, and on sensing thermal stress are activated by it to four distinct extracellular induction components (EICs), which interact with receptors on the surface of organisms to induce the appropriate responses. It is predicted that many other temperature-induced processes, including the synthesis of HSPs, will be switched-on following the activation of similar extracellular thermometers by thermal stimuli.

scholarly journals Deep Transfer Learning Based Intrusion Detection System for Electric Vehicular Networks

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4736
Author(s):  
Sk. Tanzir Mehedi ◽  
Adnan Anwar ◽  
Ziaur Rahman ◽  
Kawsar Ahmed
Keyword(s):  
Machine Learning ◽  
Deep Learning ◽  
Intrusion Detection ◽  
Real Time ◽  
Transfer Learning ◽  
Security Requirements ◽  
Detection Accuracy ◽  
Area Network ◽  
Complex Data ◽  
Network Intrusion

The Controller Area Network (CAN) bus works as an important protocol in the real-time In-Vehicle Network (IVN) systems for its simple, suitable, and robust architecture. The risk of IVN devices has still been insecure and vulnerable due to the complex data-intensive architectures which greatly increase the accessibility to unauthorized networks and the possibility of various types of cyberattacks. Therefore, the detection of cyberattacks in IVN devices has become a growing interest. With the rapid development of IVNs and evolving threat types, the traditional machine learning-based IDS has to update to cope with the security requirements of the current environment. Nowadays, the progression of deep learning, deep transfer learning, and its impactful outcome in several areas has guided as an effective solution for network intrusion detection. This manuscript proposes a deep transfer learning-based IDS model for IVN along with improved performance in comparison to several other existing models. The unique contributions include effective attribute selection which is best suited to identify malicious CAN messages and accurately detect the normal and abnormal activities, designing a deep transfer learning-based LeNet model, and evaluating considering real-world data. To this end, an extensive experimental performance evaluation has been conducted. The architecture along with empirical analyses shows that the proposed IDS greatly improves the detection accuracy over the mainstream machine learning, deep learning, and benchmark deep transfer learning models and has demonstrated better performance for real-time IVN security.

scholarly journals Impact of eating disorders on paid or unpaid work participation and performance: a systematic review and meta-analysis protocol

2022 ◽  
Vol 10 (1) ◽  
Author(s):  
Fatima Safi ◽  
Anna M. Aniserowicz ◽  
Heather Colquhoun ◽  
Jill Stier ◽  
Behdin Nowrouzi-Kia
Keyword(s):  
Systematic Review ◽  
Eating Disorders ◽  
Meta Analysis ◽  
Experimental Studies ◽  
Work Participation ◽  
Unpaid Work ◽  
Cochrane Library ◽  
And Performance ◽  
The Impact

Abstract Background Eating disorders (ED) can reduce quality of life by limiting participation and performance in social and occupational roles, including paid or unpaid work. The association between ED pathologies and work participation and performance must be well understood to strengthen vocational rehabilitation programmes and prevent occupational disruptions in the ED population. The aims of this study are: (1) to examine the degree of association between ED pathologies and work participation and performance in 15-year-olds and older; (2) to highlight the specific ED symptoms that are most correlated with changes in work performance and participation; (3) to compile the most common metrics and assessments used to measure work participation and performance with ED. Methods Medline, Embase, CINAHL, Web of Science, PsycINFO, and Cochrane Library will be searched for observational and experimental studies that meet the following criteria: (1) a clinical sample of typical or atypical ED; (2) paid or unpaid employment or training; (3) an association between ED pathologies and work participation or performance. Unpublished data will also be examined. Title and abstract, and full-text screening will be conducted in duplicate. Risk of bias and quality of evidence assessments will be completed. A random-effect meta-analysis will be performed. Discussion This synthesis can clarify knowledge and gaps around the impact of ED on work functioning, thereby allowing better evaluation, improvements and development of current workplace assessments, interventions, and policies. Trial registration The registration number for this systematic review on PROSPERO is CRD42021255055.

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