Automotive Communication Security Methods and Recommendations for Securing In-vehicle and V2X Communications

Today’s vehicles contain approximately more than 100 interconnected computers (ECUs), several of which will be connected to the Internet or external devices and networks around the vehicle. In the near future vehicles will extensively communicate with their environment via Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2I), together called V2X communications. Such level of connectivity enables car manufacturers to implement new entertainment systems and to provide safety features to decrease the number of road accidents. Moreover, authorities can deploy the traffic information provided by vehicular communications to improve the traffic management. Despite the great benefits that comes with vehicular communications, there are also risks associated with exposing a safety-critical integrated system to external networks. It has already been proved that vehicles can be remotely hacked and the safety critical functions such as braking system and steering wheel can be compromised to endanger the safety of passengers. This putshigh demands on IT security and car manufacturers to secure vehicular communications. This thesis proposes methods and recommendations for improving the security of internal and external vehicular communications.The main contributions of this thesis are contained in six included papers, and cover the following research areas of automotive security: (i) secure network architecture design, (ii) attack protection, (iii) attack detection, and (iv) V2X security. The first two papers in the collection are on the topic of secure network architecture design and propose an automated approach for grouping in-vehicle ECUs into security domains which facilitate the implementation of security measures in in-vehicle networks. The third paper is on the topic of attack protection and evaluates the applicability of existing Controller Area Network (CAN) bus authentication solutions to a vehicular context. In particular, this paper identifies five critical requirements for an authentication solution to be used in such a context. The fourth paper deals with the issue of attack detection in in-vehicle networks and proposes a specification agnostic method for detecting intrusion in vehicles. The fifth paper identifies weaknesses or deficiencies in the design of the ETSI V2X security standard and proposes changes to fix the identified weaknesses or deficiencies. The last paper investigates the security implications of adopting 5G New Radio (NR) for V2X communications

The Four-C Framework for High Capacity Ultra-Low Latency in 5G Networks: A Review

Network latency will be a critical performance metric for the Fifth Generation (5G) networks expected to be fully rolled out in 2020 through the IMT-2020 project. The multi-user multiple-input multiple-output (MU-MIMO) technology is a key enabler for the 5G massive connectivity criterion, especially from the massive densification perspective. Naturally, it appears that 5G MU-MIMO will face a daunting task to achieve an end-to-end 1 ms ultra-low latency budget if traditional network set-ups criteria are strictly adhered to. Moreover, 5G latency will have added dimensions of scalability and flexibility compared to prior existing deployed technologies. The scalability dimension caters for meeting rapid demand as new applications evolve. While flexibility complements the scalability dimension by investigating novel non-stacked protocol architecture. The goal of this review paper is to deploy ultra-low latency reduction framework for 5G communications considering flexibility and scalability. The Four (4) C framework consisting of cost, complexity, cross-layer and computing is hereby analyzed and discussed. The Four (4) C framework discusses several emerging new technologies of software defined network (SDN), network function virtualization (NFV) and fog networking. This review paper will contribute significantly towards the future implementation of flexible and high capacity ultra-low latency 5G communications

In-band Emission Interference in D2D-enabled Cellular Networks: Modelling, Analysis, and Mitigation

Next generation network is considered as a device to device (D2D)-enabled system. The overlay in-band scheme can be used by the cellular user equipments (CUEs) and D2D user equipments (DUEs) to send data. The cellular and D2D links experience the in-band emission interference (IEI) from the DUEs that use the adjacent frequencies. This paper models the IEI impact by using the stochastic geometry and analytically investigates this impact on cellular and D2D links. The IEI intercell and IEI intra-cell are separately assessed, and the expected D2D resource block (DRB) reuse factor is evaluated. Further, distance-density based (DDB) strategy is proposed to mitigate the IEI by controlling the number and location of served DUEs for each DRB. Also, optimal power allocation (OPA) algorithm is proposed by calculating the optimal DUEs transmission power profile that mitigates IEI and maximizes the DUEs sum rate. The performance is improved significantly for the proposed methods. The application scenario is identified for each mitigation method

Sensor Technologies for Intelligent Transportation Systems

Modern society faces serious problems with transportation systems, including but not limited to traffic congestion, safety, and pollution. Information communication technologies have gained increasing attention and importance in modern transportation systems. Automotive manufacturers are developing in-vehicle sensors and their applications in different areas including safety, traffic management, and infotainment. Government institutions are implementing roadside infrastructures such as cameras and sensors to collect data about environmental and traffic conditions. By seamlessly integrating vehicles and sensing devices, their sensing and communication capabilities can be leveraged to achieve smart and intelligent transportation systems. We discuss how sensor technology can be integrated with the transportation infrastructure to achieve a sustainable Intelligent Transportation System (ITS) and how safety, traffic control and infotainment applications can benefit from multiple sensors deployed in different elements of an ITS. Finally, we discuss some of the challenges that need to be addressed to enable a fully operational and cooperative ITS environment

HUMIDITY EFFECT TO 5G PERFORMANCES UNDER PALEMBANG CHANNEL MODEL AT 28 GHZ

The telecommunication has a tremendous improvement in terms of data rates and bandwidth requiring sufficient frequency allocation and wideband spectrum availability. The millimeter-wave frequency band is one of the solution to these requirements, however communications in this band is facing new challenges on the climate effect to the channel propagation  In this paper, we propose a 5G channel model considering the effect of humidity based on the characteristic of the natural environment of Palembang city. The channel model is represented by power levels and delay called a Power Delay Profile (PDP and is derived based on a series of computer simulations using parameters of nature in Palembang. The 5G channel model is important to further derive the outage performance to be used as the theoretical performance of 5G in Palembang since the the Shannon Channel Capacity Theorem is involved in the derivation. We conduct a series of computer simulations to evaluate the validity of the proposed channel model and its characteristics. We found that humidity affect to the performances, where high humidity makes the performances of outage and BER slightly worse, although the effect may be ignored for some applications. The results of this paper are expected to be the references for the development and implementation of 5G Networks especially at the mm-Wave band in Palembang. 

A Survey of Blind Modulation Classification Techniques for OFDM Signals

Blind modulation classification (MC) is an integral part of designing an adaptive or intelligent transceiver for future wireless communications. Blind MC has several applications in the adaptive and automated systems of sixth generation (6G) communications to improve spectral efficiency and power efficiency, and reduce latency. It will become a integral part of intelligent software-defined radios (SDR) for future communication. In this paper, we provide various MC techniques for orthogonal frequency division multiplexing (OFDM) signals in a systematic way. We focus on the most widely used statistical and machine learning (ML) models and emphasize their advantages and limitations. The statistical-based blind MC includes likelihood-based (LB), maximum a posteriori (MAP) and feature-based methods (FB). The ML-based automated MC includes k-nearest neighbors (KNN), support vector machine (SVM), decision trees (DTs), convolutional neural networks (CNNs), recurrent neural networks (RNNs), and long short-term memory (LSTM) based MC methods. This survey will help the reader to understand the main characteristics of each technique, their advantages and disadvantages. We have also simulated some primary methods, i.e., statistical- and ML-based algorithms, under various constraints, which allows a fair comparison among different methodologies. The overall system performance in terms bit error rate (BER) in the presence of MC is also provided. We also provide a survey of some practical experiment works carried out through National Instrument hardware over an indoor propagation environment. In the end, open problems and possible directions for blind MC research are briefly discussed

Measurement-Based Analysis on Vehicle-to-Vehicle Connectivity in Tunnel Environment

Vehicular ad hoc network (VANET) brings an excellent solution to ensure road safety and transportation efficiency in critical environment like tunnel. Particularly, radio link connectivity of vehicle-to-vehicle (V2V) significantly influences the performance of VANETs. The communication range of the radio systems is a random variable in reality due to the channel fading effect. Therefore, the connectivity model between vehicles in realistic environment is a key for accurate evaluation of system performances. In this paper, we study the V2V connectivity performance in the presence of channel randomness for tunnel environment. Firstly, based on channel measurement campaign, empirical path loss (PL) and small-scale fading channel models are established. Secondly, we study the influence of large-scale fading parameters on V2V connectivity. Thirdly, based on real small-scale fading characteristics, we derive the V2V connectivity probability between any two vehicles under Nakagami fading channel for one-dimensional VANET, and give the closed-form of V2V connectivity probability. Finally, we study the influences of various parameters (i.e., Nakagami fading factor, vehicle density, and neighbor order) on V2V connectivity performance. Results show that with the Nakagami fading shape factor increases, the connectivity probability increases. The shadowing fading can improve connectivity in the VANET; the path loss exponent, transmission distance, and signal-to-noise ratio (SNR) threshold have a negative impact on connectivity probability. The transmit power, vehicle density, and path loss threshold value have a positive impact on connectivity