Internet of Vehicles (IoV)

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Onstar Passenger Airbag sensor

In IoV, vehicles with various sensors are the primary nodes that connect to other resources. A complex, heterogeneous network of sensors, actuators, computing, routing and personal or roadside devices to communicate with other Wireless Sensor Networks (WSN), IoV is a dynamic mobile communication system which communicates between vehicles and public networks using vehicle-to-vehicle (V2V), vehicle-to-road (V2R), vehicle-to-human (V2H), and vehicle-to-sensor(V2S) interactions to improve safety on road, traffic management, and provide convenience to drivers by gathering and sharing information on vehicles, roads, drivers and their surroundings and effectively guiding vehicles based on the data.[1][2]

History

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A terminology sometimes used synonymously with the Connected Car, Internet of Vehicles (IoV) is an emerging paradigm of Internet of Things (IoT) and was the result of the collection and integration of different types of information available in the newer vehicles that were manufactured over the last decade with components to monitor different conditions (i.e. driver monitoring, tire pressure, oil pressure, vehicle speed, acceleration and global positioning).[2] Not to be confused with VANET which turns vehicles on the road into moving wireless access points, IoV expands on this concept to turn every vehicle into a smart node on the highway, with its own computing, storage and networking capability gathering and sharing information among vehicles, roads and their surroundings, the system can effectively guide vehicles, and provide mobile Internet application services [3].

Uses

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Chevy Volt Sensor Displays

Many public transportation companies already utilize IoV to check routes bus drivers use to provide practical information such as the expected arrival time of buses to a particular stop. The long-term goal of IoV is a system of interconnected cars that will eventually drive autonomously as well as self-park by using data from the roads and other cars on the road (i.e. Apple’s Carplay and Google’s Android Auto) --otherwise known as Intelligent Connected Vehicles (ICV).[4][5]

Combined with the concept of cloud computing for driving status, traffic data analysis, and vehicle dynamic data recording (i.e. map and weather data), high-precision location service and integrated intelligent transportation systems are now possible to enhance traffic efficiency, avoid accidents, ensure road safety, and improve driving experiences by using new IoT technologies.[1]

Challenges

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A heterogeneous network of dynamic topological structures of huge network scale and non-uniform distribution of nodes, coupled with mobile limitations and lack of secure protocols and mechanisms, IoV systems are more vulnerable to various types of computer and network attacks, such as authentication and identification attacks, availability attacks, confidentiality attacks, routing attacks, data authenticity attacks, etc. [1]

Authentication Attacks

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Sybil attack

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A malicious device or node appears in the wireless system with multiple illegal identities. Because IoVis dynamic, the vehicles always access in IoV temporarily and unstably, which makes it easy for Sybil nodes to find chance to attack.[5]

GPS deception

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GPS deception can provide a node with fake information about its location, speed, and some other GPS information that is subsequently accepted by IoV applications about safety or financial issues without being tracked. Because GPS information plays an important role in many applications such as navigation tools and payment applications, any inaccurate information could cause fake evidence and unpredictable property damage.[1] 

Masquerading attack

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Masquerading attacks can threaten chaos by allowing more than one node in such circumstance to have identical Identities. Subsequently, the IoV systems would not work properly and would not know what to do next.[1]

Wormhole attack

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Two or more malicious nodes hide within the network and entice legitimate nodes to route across them to absorb dataflow and compromise the network. This kind of attack always has fatal influences on IoV system due to its characteristics of change and high dependence on efficient routing algorithm.[1]

Routing / Availability Attacks

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Denial of Service (DoS) and channel interference leverages IoV's limitations of bandwidth and transmission power. Most components of IoV are exposed to attackers due to deficient protection mechanisms and protocols, and thus, are vulnerable to interference, control, information leakage and outage.[1]

Eavesdropping

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Due to the openness of wireless links, routing nodes can easily be eavesdropped without being detected because this type of attack has no disruption for original data.[1]

Denial of Service (DoS)

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Malicious nodes send large number of repeating requests or invalid data to other nodes and make them too busy to provide normal services properly.[1]

Masquerading

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Malicious nodes obstruct routing processes and obtain vital information by masquerading as a legitimate node, introducing threats to the network and attackers can hide their identity with the help of impersonated objects.[1]

Route modification

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IoV's limitations of bandwidth, transmission power, and mobility allows malicious nodes (once in the network) to easily modify routing information or change the number of hops in forwarding routing request packets to disrupt normal routing process, resulting in incorrect or non-delivery of data.[1]

Secrecy Attacks

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Sensitive resources and data are compromised by eavesdropping or intercepting either the vehicle or a road side unit (RSU), resulting in leakage of users’ privacy.[1]

Data Authenticity Attacks

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Replay attack

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Conducted by illegitimate nodes, a large amount of message replays suck up precious bandwidth, resulting in dropping of priority messages from the queue and decreased efficiency of the system due to constant replaying and deleting.[1]

Camouflage attack

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A malicious node hides itself under a false identity and utilizes this appearance from a legitimately authenticated node, and spreads fake and harmful messages, or executes blackhole attacks, or other fatal attacks.[1]

Fabricating and tampering

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Fake messages and false information are disseminated by attackers to masquerade and hide evidence of other kinds of vehicle attacks. Routine message distribution nodes will also be broken and vehicles will be prevented from joining in the traffic normally or bring false reaction of traffic emergencies.[1]

Illusion attack

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Malicious sensors that are placed in the network to generate false or meaningless information in the network to leverage the current weak authentication IoV mechanisms. [1]

References

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  1. ^ a b c d e f g h i j k l m n o p Sun, Yunchuan; Wu, Lei; Wu, Shizhong; Li, Shoupeng; Zhang, Tao; Zhang, Li; Xu, Junfeng; Xiong, Yongping; Cui, Xuegang (2017-06-01). "Attacks and countermeasures in the internet of vehicles". Annals of Telecommunications. 72 (5–6): 283–295. doi:10.1007/s12243-016-0551-6. ISSN 0003-4347.
  2. ^ a b "Internet of Vehicles: Your next connection". www1.huawei.com. Retrieved 2018-02-25.
  3. ^ "What's the difference between the Internet of Vehicles (IoV) and Vehicular Ad-Hoc Network (VANET), if any? - Quora". www.quora.com. Retrieved 2018-02-25.
  4. ^ Molina, Karoly G (2016-09-28). "From the IoT to the IoV". Parking Network. Retrieved 2018-02-25.
  5. ^ a b Kuang, Xu (06/23/2017). "Intelligent connected vehicles: the industrial practices and impacts on automotive value-chains in China". Taylor and Francis Online. Retrieved 02/25/2018. {{cite web}}: Check date values in: |access-date= and |date= (help)