scholarly journals Detection and Identification of Malicious Cyber-Attacks in Connected and Automated Vehicles’ Real-Time Sensors

2020 ◽  
Vol 10 (21) ◽  
pp. 7833
Author(s):  
Elvin Eziama ◽  
Faroq Awin ◽  
Sabbir Ahmed ◽  
Luz Marina Santos-Jaimes ◽  
Akinyemi Pelumi ◽  
...  
Keyword(s):  
Real Time ◽  
Information Exchange ◽  
Information Dissemination ◽  
Transportation Systems ◽  
Cyber Attacks ◽  
Security And Privacy ◽  
Discrete Wavelet ◽  
Automated Vehicles ◽  
Sensor Reading ◽  
Detection And Identification

Connected and automated vehicles (CAVs) as a part of Intelligent Transportation Systems (ITS) are projected to revolutionise the transportation industry, primarily by allowing real-time and seamless information exchange of vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I). However, these connectivity and automation are expected to offer vast numbers of benefits, new challenges in terms of safety, security and privacy also emerge. CAVs continue to rely heavily on their sensor readings, the input obtained from other vehicles and the road side units to inspect roadways. Consequently, anomalous reading of sensors triggered by malicious cyber attacks may lead to fatal consequences. Hence, like all other safety-critical applications, in CAVs also, reliable and secure information dissemination is of utmost importance. As a result, real time detection of anomaly along with identifying the source is a pre-requisite for mass deployment of CAVs. Motivated by this safety concerns in CAVs, we develop an efficient anomaly detection method through the combination of Bayesian deep learning (BDL) with discrete wavelet transform (DWT) to improve the safety and security in CAVs. In particular, DWT is used to smooth sensor reading of a CAV and then feed the data to a BDL module for analysis of the detection and identification of anomalous sensor behavior/data points caused by either malicious cyber attacks or faulty vehicle sensors. Our numerical experiments show that the proposed method demonstrates significant improvement in detection anomalies in terms of accuracy, sensitivity, precision, and F1-score evaluation metrics. For these metrics, the proposed method shows an average performance gain of 7.95%, 9%, 8.77% and 7.33%, respectively when compared with Convolutional Neural Network (CNN-1D), and when compared with BDL, the corresponding numbers are 5%, 7.9%, 7.54% and 4.1% respectively.

A Virtual Reality Approach for Minimizing Information Loss in Multi-User, Scalable Environments

2015 ◽  
Author(s):  
Bryan Dickens ◽  
Steven Sellers ◽  
Gabe Harms ◽  
Owen Shartle ◽  
Conrad S. Tucker
Keyword(s):  
Virtual Reality ◽  
Real Time ◽  
Information Exchange ◽  
Visual Information ◽  
Information Dissemination ◽  
Research Question ◽  
Information Loss ◽  
Sound Waves ◽  
Brick And Mortar

The authors of this work propose a virtual reality approach that overcomes two fundamental challenges experienced in physical learning environments; i) variations in audial quality, and ii) variations in visual quality, in an effort to achieve individual customization of information content. In physical brick and mortar environments, the dissemination of information is influenced by the medium that the information travels through, which is typically distorted by line of sight constraints and constraints that distort sound waves. The fundamental research question is how to achieve consistent quality of information being disseminated, as the number of audience members increases? There exists a knowledge gap relating to the creation of a scalable, networked, system for enabling real time, information exchange. The authors propose a virtual reality approach to address these limitations of physical learning spaces that minimizes the variability in audial and visual information dissemination. A real time, networked architecture is proposed that enables multiple individuals to simultaneously experience the same quality of audial and visual information, based on the optimal geospatial position for audial and visual exposure determined. A case study is introduced that first quantifies simulations of the audial and visual information loss experienced by audience members receiving information at different geospatial locations in a brick and mortar environment. This information loss is compared against the proposed virtual reality architecture that minimizes the variation in information dissemination. The authors demonstrate that the proposed solution is an improved, scalable multi-user system, unlike brick and mortar environments that are constrained by size and geospatial positioning.

scholarly journals On the Assessment of Cyber Risks and Attack Surfaces in a Real-Time Co-Simulation Cybersecurity Testbed for Inverter-Based Microgrids

Energies ◽  
2021 ◽  
Vol 14 (16) ◽  
pp. 4941
Author(s):  
Kirti Gupta ◽  
Subham Sahoo ◽  
Bijaya Ketan Panigrahi ◽  
Frede Blaabjerg ◽  
Petar Popovski
Keyword(s):  
Real Time ◽  
Information Exchange ◽  
Communication Systems ◽  
Research Work ◽  
Cyber Attacks ◽  
Future Research ◽  
Monitoring And Control ◽  
Physical Layers ◽  
Attack Surfaces ◽  
And Control

The integration of variable distributed generations (DGs) and loads in microgrids (MGs) has made the reliance on communication systems inevitable for information exchange in both control and protection architectures to enhance the overall system reliability, resiliency and sustainability. This communication backbone in turn also exposes MGs to potential malicious cyber attacks. To study these vulnerabilities and impacts of various cyber attacks, testbeds play a crucial role in managing their complexity. This research work presents a detailed study of the development of a real-time co-simulation testbed for inverter-based MGs. It consists of a OP5700 real-time simulator, which is used to emulate both the physical and cyber layer of an AC MG in real time through HYPERSIM software; and SEL-3530 Real-Time Automation Controller (RTAC) hardware configured with ACSELERATOR RTAC SEL-5033 software. A human–machine interface (HMI) is used for local/remote monitoring and control. The creation and management of HMI is carried out in ACSELERATOR Diagram Builder SEL-5035 software. Furthermore, communication protocols such as Modbus, sampled measured values (SMVs), generic object-oriented substation event (GOOSE) and distributed network protocol 3 (DNP3) on an Ethernet-based interface were established, which map the interaction among the corresponding nodes of cyber-physical layers and also synchronizes data transmission between the systems. The testbed not only provides a real-time co-simulation environment for the validation of the control and protection algorithms but also extends to the verification of various detection and mitigation algorithms. Moreover, an attack scenario is also presented to demonstrate the ability of the testbed. Finally, challenges and future research directions are recognized and discussed.

Real-Time Sensor Anomaly Detection and Identification in Automated Vehicles

2020 ◽  
Vol 21 (3) ◽  
pp. 1264-1276 ◽  
Author(s):  
Franco van Wyk ◽  
Yiyang Wang ◽  
Anahita Khojandi ◽  
Neda Masoud
Keyword(s):  
Anomaly Detection ◽  
Real Time ◽  
Automated Vehicles ◽  
Detection And Identification

scholarly journals Secure Trust-Based Blockchain Architecture to Prevent Attacks in VANET

Sensors ◽  
2019 ◽  
Vol 19 (22) ◽  
pp. 4954 ◽  
Author(s):  
Adnan Shahid Khan ◽  
Kuhanraj Balan ◽  
Yasir Javed ◽  
Seleviawati Tarmizi ◽  
Johari Abdullah
Keyword(s):  
Information Exchange ◽  
Denial Of Service ◽  
Computational Cost ◽  
Transportation Systems ◽  
Security And Privacy ◽  
Delivery Ratio ◽  
Mac Layer ◽  
Dos Attacks ◽  
Malicious Nodes ◽  
On The Road

Vehicular ad hoc networks (VANET) are also known as intelligent transportation systems. VANET ensures timely and accurate communications between vehicle to vehicle (V2V) and vehicle to infrastructure (V2I) to improve road safety and enhance the efficiency of traffic flow. Due to its open wireless boundary and high mobility, VANET is vulnerable to malicious nodes that could gain access into the network and carry out serious medium access control (MAC) layer threats, such as denial of service (DoS) attacks, data modification attacks, impersonation attacks, Sybil attacks, and replay attacks. This could affect the network security and privacy, causing harm to the information exchange within the network by genuine nodes and increase fatal impacts on the road. Therefore, a novel secure trust-based architecture that utilizes blockchain technology has been proposed to increase security and privacy to mitigate the aforementioned MAC layer attacks. A series of experiment has been conducted using the Veins simulation tool to assess the performance of the proposed solution in the terms of packet delivery ratio (PDR), end-to-end delay, packet loss, transmission overhead, and computational cost.

scholarly journals Design of a dynamic and self-adapting system, supported with artificial intelligence, machine learning and real-time intelligence for predictive cyber risk analytics in extreme environments – cyber risk in the colonisation of Mars

2021 ◽  
Author(s):  
Petar Radanliev ◽  
David De Roure ◽  
Kevin Page ◽  
Max Van Kleek ◽  
Omar Santos ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Real Time ◽  
Cyber Security ◽  
Extreme Environments ◽  
Learning Technologies ◽  
Cyber Attacks ◽  
Edge Computing ◽  
Mathematical Formulas ◽  
Cyber Risk

AbstractMultiple governmental agencies and private organisations have made commitments for the colonisation of Mars. Such colonisation requires complex systems and infrastructure that could be very costly to repair or replace in cases of cyber-attacks. This paper surveys deep learning algorithms, IoT cyber security and risk models, and established mathematical formulas to identify the best approach for developing a dynamic and self-adapting system for predictive cyber risk analytics supported with Artificial Intelligence and Machine Learning and real-time intelligence in edge computing. The paper presents a new mathematical approach for integrating concepts for cognition engine design, edge computing and Artificial Intelligence and Machine Learning to automate anomaly detection. This engine instigates a step change by applying Artificial Intelligence and Machine Learning embedded at the edge of IoT networks, to deliver safe and functional real-time intelligence for predictive cyber risk analytics. This will enhance capacities for risk analytics and assists in the creation of a comprehensive and systematic understanding of the opportunities and threats that arise when edge computing nodes are deployed, and when Artificial Intelligence and Machine Learning technologies are migrated to the periphery of the internet and into local IoT networks.

scholarly journals Security of Blockchain-Based Supply Chain Management Systems: Challenges and Opportunities

2021 ◽  
Vol 11 (12) ◽  
pp. 5585
Author(s):  
Sana Al-Farsi ◽  
Muhammad Mazhar Rathore ◽  
Spiros Bakiras
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Information Exchange ◽  
Cyber Attacks ◽  
Management Systems ◽  
Chain Management ◽  
Counter Measures ◽  
Starting Point ◽  
Challenges And Opportunities ◽  
Unique Approach

Blockchain is a revolutionary technology that is being used in many applications, including supply chain management. Although, the primary motive of using a blockchain for supply chain management is to reduce the overall production cost while providing the comprehensive security to the system. However, current blockchain-based supply-chain management (BC-SCM) systems still hold the possibility of cyber attacks. Therefore, the goal of this study is to investigate practical threats and vulnerabilities in the design of BC-SCM systems. As a starting point, we first establish key requirements for the reliability and security of supply chain management systems, i.e., transparency, privacy and traceability, and then discern a threat model that includes two distinctive but practical threats including computational (i.e., the ones that threaten the functionality of the application) and communication (i.e., the ones that threaten information exchange among interconnected services of the application). For investigation, we follow a unique approach based on the hypothesis that reliability is pre-requisite of security and identify the threats considering (i) design of smart contracts and associated supply chain management applications, (ii) underlying blockchain execution environment and (iii) trust between all interconnected supply management services. Moreover, we consider both academic and industry solutions to identify the threats. We identify several challenges that hinder to establish reliability and security of the BC-SCM systems. Importantly, we also highlight research gaps that can help to establish desired security of the BC-SCM. To the best of our knowledge, this paper is the first effort that identifies practical threats to blockchain-based supply chain management systems and provides their counter measures. Finally, this work establishes foundation for future investigation towards practical security of BC-SCM system.

scholarly journals The Way Forward for Indirect Structural Health Monitoring (iSHM) Using Connected and Automated Vehicles in Europe

2021 ◽  
Vol 6 (3) ◽  
pp. 43
Author(s):  
Konstantinos Gkoumas ◽  
Kyriaki Gkoktsi ◽  
Flavio Bono ◽  
Maria Cristina Galassi ◽  
Daniel Tirelli
Keyword(s):  
Intelligent Transportation Systems ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Transport Infrastructure ◽  
Policy Framework ◽  
Strategic Decisions ◽  
Automated Vehicles ◽  
Civil Infrastructures ◽  
Vehicle Automation ◽  
Labor Requirements

Europe’s aging transportation infrastructure requires optimized maintenance programs. However, data and monitoring systems may not be readily available to support strategic decisions or they may require costly installations in terms of time and labor requirements. In recent years, the possibility of monitoring bridges by indirectly sensing relevant parameters from traveling vehicles has emerged—an approach that would allow for the elimination of the costly installation of sensors and monitoring campaigns. The advantages of cooperative, connected, and automated mobility (CCAM), which is expected to become a reality in Europe towards the end of this decade, should therefore be considered for the future development of iSHM strategies. A critical review of methods and strategies for CCAM, including Intelligent Transportation Systems, is a prerequisite for moving towards the goal of identifying the synergies between CCAM and civil infrastructures, in line with future developments in vehicle automation. This study presents the policy framework of CCAM in Europe and discusses the policy enablers and bottlenecks of using CCAM in the drive-by monitoring of transport infrastructure. It also highlights the current direction of research within the iSHM paradigm towards the identification of technologies and methods that could benefit from the use of connected and automated vehicles (CAVs).

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