Posted: April 26th, 2022

Self-Driving Vehicles

Computer Sciences and Information Technology
Topic: Self-Driving Vehicles.
Abstract
Self-driving vehicles are the future of transportation as they offer benefits such as timeliness, and increased safety. However, these benefits are faced with threats as attackers try to compromise the security services offered by vehicular ad hoc technology standards. This paper gives background and overview of self-driving cars according to related works by other authors. It is vital that readers first understand the underlying architecture, the components and challenges facing the network. Henceforth, attacks of various kinds are discussed to show how security services may fail. There is need to mitigate the issues that face integrity, availability, authenticity, non-repudiation, and confidentiality of information to have a successful venture across self-driving vehicles.

Introduction
Self-driving vehicles, also known as vehicular cloud computing technology is a new and emerging technology that aims at improving the transport system to give users comfort and traffic safety. The technology enables vehicles to connect to a communication network through the nodes that are linked to each other as they move (Hedge, 2019). However, the integration with the cloud may prove beneficial to some level, but it possesses a danger to the security services offered by vehicular ad hoc network (VANET). The changes in topology and lack of a decentralized system, as is the nature of ad hoc systems makes the network a challenge to the reliable delivery of safety applications (Abubakar et al. 2019). It is essential to consider the possibilities of malicious people who may want to attack the network for their gain and take measures accordingly. The connection with the cloud, notwithstanding the possibility that it will be useful on some level, presents a risk to the security services provided by automobile ad hoc networks (VANET). The network poses a barrier to the reliable supply of safety applications as a result of its constantly shifting topology and inherent absence of a decentralized system, which is typical of ad hoc computer networks (Abubakar et al. 2019). It is absolutely necessary to take appropriate precautions after taking into account the likelihood that some dishonest individuals may attempt to breach the network in order to advance their own interests. This paper addresses the benefits, architecture, challenges, and possible security attacks targeting self-driving vehicles to gain an in-depth understanding of the improvements of the system to ensure continued progress in the automotive industry.
Benefits
The reason self-driving vehicles are becoming more popular is their ability to reduce delays in traffic since the network is able to determine speeds, locations, and road conditions beforehand. The New York Transport department is an example of a city that has implemented the use of self-driving vehicular networks to give drivers and vehicles the information they needs. Through the implementation of intelligent transportation systems and 13,000 devices, self-driving vehicles are more equipped to serve their functions (Talas, 2018). Besides that, self-driving vehicles are more informed at decision-making hence the probability of reduced traffic incidents. Self-driving vehicles are most likely the future of transportation as they hold the potential to fully operate without human beings in control. Those set to benefit the most are delivery businesses and online shopping. Complaints such as delivery delays will be reduced since it is possible to schedule for drop-offs and meetings beforehand. The ability for these vehicles to react in a real-time manner shows that they can be more reliable than human cognitive senses (Rathee, 2019). Self-driving vehicles will ensure increased safety and timeliness due to proper movement plans.

Architecture
The VANET is composed of three central units, which are the Onboard Units (OBU), Roadside Unit (RSUs), and Trusted Authority (TA) (Muhammad, 2019). The following are the functions of these components:
Onboard Unit: OBUs are the mounted links on vehicles that act as tracking devices. These OBUs share vehicular information with other OBUs or roadside units. The primary function of OBUs is to maintain this information as they record events, sense movements and implement the use of GPS. A normal OBU has a user interface, sensor devices, RW storage, and resource command processor.
Roadside Unit: an RSU is a computing device or beacon that is stationed along the roads that CCVs use. These devices connect to the passing cars and log them into the network to enable communication to take place. However, RSUs cover a small range of distance as they are devices for dedicated short-range communication (DSRC). The same RSU could be used to communicate with other devices within the vicinity, such as infrastructure devices, to give driver a clear view of the surrounding.
Trusted Authority: this is the heart of VANET and is responsible for holding the whole system together. It registers the users of the vehicle and the roadside units and onboard units. The TA maintains security as it authorizes the user for the OBU ID to prevent malicious attacks. The TA identifies any threats in case suspicious behavior is noticed over the network. With the high power it possesses and the large memory size, the TA records all the information that passes through it for retrieval when needed.
The architecture of VANET enables vehicles to communicate with each other through the wireless links that are mounted on the cars. A VANET node acts as a receiver and router within the network since each node relies on the others to transmit information. This causes a self-organizing system, which makes it difficult to claim that VANET has a specific architecture (Irshad, 2018). However, there are three types of architecture in which VANET could be classified. These are:
Pure ad hoc network: This is the most common architecture, and it enables vehicles to communicate with other cars depending on proximity. The ad hoc network collects information about the road and relays the information to the vehicles. As the vehicles move about, there is a need for the network topology to change to fit their new location. This makes routing the information harder as the network experiences fragmentation due to the changes in topology (Irshad, 2018). This system is more popular as it lowers costs by not having a fixed station.
Pure cellular WLAN: this involves the use of the internet or the cloud whereby vehicles access the network through gateways and WLAN points. Through this architecture, drivers are provided with several resources and services that make their driving easier. Due to information provided by other drivers, the driver can view a map of the road in terms of congestion or accidents. This method is more efficient but costly as cellular services depend on the ISP or cloud service provider.
Hybrid Networks: the hybrid architecture combines both the ad hoc system and infrastructure system to make use of the V2I and V2V. Through this communication, drivers can communicate with other cars and at the same time, view infrastructure. This makes their driving more reliable and flexible.

Challenges Facing the Technology behind Self-Driving Vehicles
Bandwidth limitation: there is an issue with communication since an increase in cars means that there will be an increase of signals sent to the server. Hence, delays, interferences and affected delivery ratios will be experienced. Since VANET processes information in real-time, large amounts of data will be dispersed each second over the network.
Dynamic speed and topology: ad hoc technology takes after a dynamic nature where there is no fixed topology. This is to ensure that vehicles can change beacons as they move. However, with the speed of cars, it takes time for generation of beacons to take place and verify the vehicles, which could lead to accidents and congestion.
Sparse and dense scenarios: there is a need for beacons to work efficiently in both sparse and dense traffic when vehicles enter and exit the VANET. This is because, in dense scenarios, more cars trying to access the network while in sparse situations few cars try to access the system. The technology must find smart means of mitigating both scenarios to offer the same quality of information.
Malicious attackers: due to lack of a fixed centralized system, attackers may use imposter beacons to target innocent vehicles for their gain. Since the network is wireless and dynamic, it is more prone to attacks.

Network security Attacks

Availability, Confidentiality, Authentication, Integrity, and non-repudiation are the most attacked aspects of self-driving vehicles.
Availability: as the most critical aspect of security, availability is mostly compromised as it is highly associated with all the functions of self-driving vehicles. A well-known attack on availability includes Denial of Service Attacks, spamming, jamming, and malware.
Confidentiality: when data is passed between two network nodes, it should reach the receiver without anyone else reading the contents of the file. Self-driving vehicles face the danger of message interceptions where an attacker accesses the message and learns the details. Attacks towards confidentiality include eavesdropping, man-in-the-middle and social attacks
Authentication: authentication allows for users to be given a certain identity that gives access. Such an approach discourages attackers from accessing the network with ease. Attacks on access include masquerading, free-riding, spoofing, and Sybil.
Data Integrity: information technology relies on integrity to retain the reliable data. Information loses its integrity when tampered and altered from its original form. Some of the security attacks against integrity include replays and illusions. They can be mitigated or prevented by the use of cryptographic keys.
Non-repudiation: This is the assurance that a receiver does not deny information in case there is a dispute with the sender. With every data that is sent from a sender to a receiver, signatures are involved in proving the authenticity of the information. Due to non-repudiation, information can be traced back to its origin to confirm who sent it. A case of an attack on non-repudiation is a repudiation attack when the attacker refuses to involve themselves in the case of sending and receiving information in case of a dispute

Conclusion
In conclusion, the technology behind self-driving vehicles is promising and most likely the future of transportation. Despite the challenges and attacks towards the technology, the benefits outweigh the risks. Like any information technology, attacks can be prevented, controlled, and mitigated to maintain functionality. Self-driving vehicles like any technology reduce the burden on humans to constantly stay alert while driving and make proper decisions on the routes to follow. With such kind of technology, most industries will benefit on automated deliveries and scheduling appointments beforehand. It is encouraging to think of what humanity can achieve with self-driving vehicles. Traffic delays will decrease enabling people to get to their destinations faster. Businesses will be able to accomplish the most in one day due to improved traffic and delay complaints will decrease. Self-driving vehicles are a future in technology that would benefit every sector of operations.

References
Abubakar, B. T., RafidahNoor, Salleh, R., Chembe, C., & Oche, M. (2019). Enhanced weight-based clustering algorithm to provide reliable delivery for VANET safety applications. PLoS One, 14(4) doi:http://dx.doi.org.proxy.cecybrary.com/10.1371/journal.pone.0214664
Hegde, N., & Manvi, S. S. (2019). A novel key management protocol for vehicular cloud security. TELKOMNIKA, 17(2), 857-865. doi:http://dx.doi.org.proxy.cecybrary.com/10.12928/TELKOMNIKA.V17i2.9278
Irshad, A. A., & Adnan, S. K. (2018). A review of vehicle to vehicle communication protocols for VANETs in the urban environment. Future Internet, 10(2), 14. doi:http://dx.doi.org.proxy.cecybrary.com/10.3390/fi10020014
Muhammad, S. S., Liang, J., & Wang, W. (2019). A survey of security services, attacks, and applications for vehicular ad hoc networks (VANETs). Sensors, 19(16) doi:http://dx.doi.org.proxy.cecybrary.com/10.3390/s19163589
Rathee, G., Sharma, A., Iqbal, R., Aloqaily, M., Jaglan, N., & Kumar, R. (2019). A blockchain framework for securing connected and autonomous vehicles.Sensors, 19(14) doi:http://dx.doi.org.proxy.cecybrary.com/10.3390/s19143165
Talas, Mohamad,P.E., P.H.D., Rausch, R., P.E., & Van Duren, D. (2018). Connected vehicle challenges for the dense urban environment. Institute of Transportation Engineers.ITE Journal, 88(12), 30-35. Retrieved from https://proxy.cecybrary.com/login?url=https://search-proquest-com.proxy.cecybrary.com/docview/2154026223?accountid=144778

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