Keywords

1 Introduction

In recent years, the research interest in intelligent transportation systems (ITSs) has increased in industry and academia [1]. ITSs’ primary goal, in addition to providing entertainment services in automobiles, is to improve road safety and driving conditions [2]. Vehicular ad hoc network (VANET) is built using two forms of communication, namely vehicle-to-vehicle (V to V) communication and vehicles-to-infrastructure (V to I or RSU) communication to transmit the essential driving information [3]. The larger bandwidth and high data rate show better results in traffic control and monitoring since the number of vehicles on roads continually increasing. Vehicles interact with adjacent vehicles to replace the data in V to V communication, whereas the vehicles communicate directly with roadside units (RSUs) in V2I communication [4]. For V to V and V to I communications in VANETs, a dedicated short-range communication (DSRC) radio [5] and a handful of IEEE standards can be utilized. VANETs’ unique properties, such as their great mobility and instability, have rendered them to be more vulnerable to many types of external and internal assaults [6]. These assaults have given rise security, privacy, and trust challenge in the design of safe VANETs. The major goal of VANETs is to enhance the road safety for drivers. VANETs will transmit different types of information, such as traffic signal violation warnings, precrash sensing, traffic jam warnings, curve speed warnings, and many more. Since mobility is a primary element of VANETs, any relevant simulation model should consider the consequences of mobility with the varied mobility patterns, and a suitable mobility model that depicts various facets of the experienced movement [7]. The VANET uses IEEE 802.11 standard Industrial, Scientific, and Medical band (ISM) band, and it is useful for many real-time implementation with the ad hoc nature. One of the vital features of such networks is flexibility, and it can be implemented without pre-existing infrastructures. Therefore, these networks are appropriate for an emergency application. The example of V to V and V to RSU is mentioned in Fig. 1. Here, the vehicles are also exchanging the traffic information with other vehicles and RSU. The prominent role of RSU is to control the traffic, check the traffic information of vehicles, and monitor the vehicle's activities.

Fig. 1
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Example of V to V and V to RSU communication

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When dealing with mobility models, it is also important to understand mobility, which is divided into macro- and micromobility. Macromobility defines and addresses motion limitations such as road topology, street features, traffic signals and signs, node flow, density, and distribution, i.e., any street element that may limit or impact mobility. On the other hand, micromobility refers to the movement of individual vehicles and their interactions with other vehicles, such as overtaking and acceleration/deceleration [8]. The 6G network will certainly improve the network service when compared to previous generations. The 6G vision is expected to be developed between 2022 and 2023 in order to define the 6G requirement, and it assesses 6G development, technologies, standards, and so on. The International Telecommunication Union (ITU) and the Third Generation Partnership Project (3GPP) are anticipated to develop the standards for 6G by 2026–2027 [9 ,10].

The presence of a black hole attacker causes harmful activity in the network [11]. Without security guarantees, some misbehaving or malevolent vehicles render the system to be susceptible for offering low-quality services or even put user vehicles in unsafe circumstances in 6G-VANET. As a result, identifying the misbehaving or malicious vehicles has become a critical task in VANET security. The security method of finding an attacker's vehicle is based on the information identified about the traffic network. The scheme detects the attacker's presence and estimates the total number of packets dropped by the black hole attacker in the network.

2 Network Model

In VANET, network model for vehicles can be separated into three groups [12]. These groups include servers for application and authorization, facilities on the road side, and nodes/vehicles in 6G-VANET.

2.1 Application and Authorization Servers

These are powerful workstations, which are, respectively, responsible for managing and providing service data. The authority knows all the keys and is accountable for maintenance planning. For cars, device servers provide the operation details. The government or foreign operators will fund them. We assume that there are powerful processing capabilities for authorization and application servers. So, here we ignored the computation time.

2.2 Road Side Infrastructure

Road infrastructure consists of power supplies located near roads, and it is also responsible for the collection and dissemination of data. Through wired networks, RSUs are connected to power and it will communicate via radio signals with vehicle but for vehicle-to-vehicle wireless communication radio or microwave signals are used.

2.3 Nodes/Vehicles

Nodes or vehicles move in the road and communication with the RSU or also their information exchange information is received by RSU in network. Every vehicle is presumed to be fitted with a differential GPS receiver with an order accuracy and On-Board Unit (OBU) responsible for all communication and computing tasks [13].

3 6G Overview

The sixth-generation (6G) communication technology provides faster data rate for communication among or between the vehicles. 6G operates at a higher frequency to obtain a broader bandwidth, i.e., in Terahertz. The huge amount of bandwidth is available for users for sharing traffic information. The responses of RSU to V and V to V also improved. Compared to 5G, 6G can boost data rates by up to a hundred times, sustaining Tb/s highest data rate and 1000 Gb/s data rate experienced by user [9, 14]. Furthermore, 6G may employ flexible frequency sharing technologies to improve frequency reuse efficiency. 6G is a customized intelligent network because broad area for communication here is available to vehicles. 6G should be a ubiquitous and integrated network with more extensive and deeper coverage, covering terrestrial communication, satellite communication, short-range device-to-device communication, and so on. 6G is intellectual mobility management technology that can operate in various situations, including airspace, land, and water, resulting in a worldwide ubiquitous mobile broadband communication system. When combined with artificial intelligence technologies, 6G will enable virtualized personal mobile communication, with the network transitioning from a classic function centralized type for user centralized, data centralized, and completely content centralized. The main drawback in centralization is dependency on centralized unit for communication. It is also supports decentralized networks like WSN, MANET, and VANET. The 6G commutation is also very helpful for sustaining the current location of vehicles. It is same as location information of nodes in MANET [15, 16]. The 6G network will feature an endogenous security scheme or function security integrated design.

Furthermore, by incorporating trust and safety mechanisms, 6G can self-awareness, real-time dynamic analysis, and adaptive risk and confidence evaluation, all of which will aid in the realization of cyberspace security. Furthermore, 6G will combine processing, sensing with communications and navigation. For example, 6G will incorporate with satellite communication systems, satellite navigation, and positioning systems, as well as radar sensing systems. Finally, 6G might have a more efficient structure that includes software-defined core networks and radio access networks. 6G will be capable of rapid and self-intelligent expansion and quick dynamic exploitation of network functionalities. 6G can generate massive amounts of data via the Internet of Everything; 6G can also combine with novel technologies such as artificial intelligence, block chain, cloud computing, edge computing, and so on [9].

4 Routing in VANET

Routing protocols may be divided into several types based on their characteristics [14, 15]. Most popular method for differentiating VANET routing protocols depends on obtained and preserved routing information. The routing protocols are classified as follows:- (Table 1).

Table 1 Routing protocols of VANET
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5 Literature Survey

This section discussed the previous work on security with its drawbacks. The different author’s contribution provides different security approaches for securing vehicular communication.

Li et al. [11] proposed an approach that maintains the reliable and safe communication between vehicles and improves the functioning of routing protocol in presence of threats in vehicular ad hoc networks. When a vehicle receives an AODV control message requesting that it establishes or modifies a route for a specific destination, it searches its routing database for an entry that leads to the location. AODV control messages are sent to vehicles to establish or change routes for specific destinations. The system produces a route entry with the sequence number specified in the control packet if there is no route entry; otherwise, the sequence number is flagged as invalid. The most significant flaw in the study is that the author restricts his attention to comparing the performance of various routing protocols. As a result, there is nothing unique about this work. The vehicle's speed is likewise indicated in kilometers per hour (km/h), but in milliseconds per second (m/s) is mentioned in Fig. 2 [11].

Fig. 2
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Security architecture of PPDM

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Soni et al. [17] proposed the PSO method for V to RSU communication to ensure security and communicate information about the attacker's vehicle to all RSU at rest and the vehicles near the attacker. The suggested preventive technique is intended to thwart the harmful acts of the attacker while still ensuring a secure connection in the VANET environment. However, the most significant flaw in this work is that it fails to specify the range of pheromones and the dropping behavior of the attacker.

Dhaya et al. [18] proposed an ACO scheme to find the shortest path among several possible paths. Accordingly, the probability of street consistency can be calculated using the expression given in the previous sentence. The buses are employed as a way of transporting the packages and directing them to their intended destinations. In each path connecting the two ends, streets are used as connecting points, and the relay bus that corresponds to the specified street is picked along with the path. Its primary weakness is that the ACO method by default supports the multipath approach, which is not ideal. Even in the presence of traffic congestion, the multipath routing condition will not function well. ACO approach is based on pheromone values but not mentioned.

Hu et al. [19] proposed a REPLACE trust-based platoon service recommendation approach, to rank platoon head vehicles by developing a trust and reputation system. They also recommended that based on feedback from user vehicles, the server computes platoon head vehicle reputation rankings for the platoon head vehicle. This allows the server to clearly distinguish between well-behaved platoon head vehicles and poorly behaved platoon head vehicles based on their reputation ratings. The malicious functioning of vehicles is based on bad and good behavior. The network's overhead increases because the server-side first verifies the traffic information and then declares it is a normal or malicious vehicle. It increases overhead in the network.

Qureshi et al. [20] proposed an Intelligent Secure Routing Scheme (ISRS) to assure data security during data transfer while transferring large amounts of data. This technology protects traffic information data in the network during data transfer from potentially damaging attacks and guarantees it remains secure. Forging, modification, and replay attacks are the three most serious security concerns that the proposed solution in VANET is designed to address. The main drawback of the paper is that the clustering mechanism is used but it is better for stationary or slow speed vehicles scenarios. That is why the delay is showing in seconds but it is better in milliseconds.

Memon [21] describes developing an authentication key setup approach based on IPv6 road networks. Using this technique, each neighboring car or RSU provides an unique address to a mobile vehicle, which prevents the mobile vehicle from receiving duplicate addresses. It includes a cryptographic authentication technique based on zero-knowledge proof, which each node may use to convince another node of the presence of a given secret without revealing it. The drawback of research is that the speed of vehicles is considered in meters/seconds but practically, it is measured in km/hour. Duplicate address identification procedure is complex. Not mentioned the specific use of IPv6 in research.

6 Problem Identification

Malicious vehicles might act both positively and negatively. The attackers have the ability to produce false information in the network and delete all traffic packets. Since packets are heavily lost on the network, the attacker cars increase network overhead. Because of the packet dropping attacker, retransmission of packets increases network latency even further. It is impossible to secure vehicle connection and deliver traffic status appropriately. In recent trends, it is observed that continuously the number of vehicles on the road increases. So the main problem is how to manage the traffic efficiently. The 6G communication technology provides a faster data rate for communication. The vehicles are continuously moving on roads but have no information of traffic on routes. The 6G communication support provides larger bandwidth and high data rate, i.e., the primary requirement of VANET. Although no significant research is being conducted in this area, it has been discovered that the offered solutions are not comprehensive in terms of effective and efficient routing security. All solutions have limits. They may have a substantial computational or communication overhead.

7 Privacy-Preserving Under Denser Traffic Management (PPDM)

VANET is highly dynamic and may expose internal and external attackers, posing significant technological problems in dependability and safe routing. Compared to the way roads are built, the attacker driving pattern is a less sustainable and more expensive approach to alleviate network load and increases the risk of routing misbehavior. The novel PPDM algorithm offers a security method against black hole attacks using an RSU unit to gather and evaluate audit data for the whole network. So, based on the above description, we infer that VANET is dispersed in nature and that we cannot trust any of the vehicles, since we cannot manage the network's topology as it changes. The PPDM secures routing from malicious attacks in VANET. The proposed PPDM allows for the safe transmission of data packets in a multihop way for identifying and blocking malicious vehicles.

7.1 Proposed Algorithm

  • Input:

  • Vn: nth vehicles in network.

  • Tm: m traffic monitoring system.

  • RSUi: no. of ith road side unit.

  • Bla: black hole attacker.

  • Mr: monitoring and preventer node ∀ RSUi.

  • Si: message sender ∀Vn.

  • Rk: message receiver ∀ Vn.

  • Ml: intermediate vehicle ∀ Vn.

  • Rreq: route request.

  • Rrep: route reply.

  • hseq: higher sequence number.

  • Yp: capture packet.

  • Ep: drop packet.

  • abh: abnormal behavior (hseq, Yp, Ep).

  • Proto: AODV for routing.

  • \(\psi \): RUi control range.

  • dr: 6G data_rate(Tbps).

  • Output: Throughput, drop analysis, PDR, end-to-end delay.

  • figure a
    figure b

The black hole attacker has degraded the network's routing performance, and the attacker infection is measured in forty node density scenarios. After detecting the malicious vehicles, the proposed security mechanism is also prevented from an attacker by denying the possibility of routing through hostile vehicles. The PPDM approach employs V to V and V to RSU communication to preserve security and forwards attacker vehicle information to all RSU and their surrounding vehicles.

7.2 Propose PPDM Architecture

The architecture of privacy-preserving scheme is mentioned in Fig. 2. In this architecture, all vehicle-controlled vehicles are controlled by the Tm base station. If any vehicle wants to communicate with another vehicle, then Vi calls AODV routing and broadcasts routing packets to search the route. At the same time, route is found through the Vk node in between source to destination and using 6G data rate. The step-by-step description of secure routing in 6G mentioned in Fig. 2.

Data privacy is not guaranteed due to the intermediary vehicle that facilitates communication from source to destination. Various man-in-the-middle attacks exist in network communication. The cross (X) in between Vj receiver and discard/capture block means attacker functioning. Black hole attackers generate a high sequence number, and false route information is given and captured and drop the data packet. To handle this situation, a PPDM module is proposed that periodically watches every active node. If any node drops the data by false routing behavior, block the particular vehicle from the communication and provide a new path from source to destination and preserve privacy during transmission. Proposed PPDM mechanism is considered as a more secured routing mechanism when compared to existing mechanism.

8 Result Description

A number of nodes 10, 20, 30, 40, and 50 are taken for simulation having 550 m radio range. The grid layout is about 800 m*800 m and propagation is two-ray ground. The simulator version is employed for simulation is Network Simulator version 2.31 (NS-2.31) [22]. The performance of PPDM security scheme routing is measured with previous SAODV and black hole AODV (BAODV). The number of nodes scenarios is same in all modules.

8.1 Throughput Analysis

When the throughput performance is high, the data reception in the network will be improved. In this graph (Fig. 3), the throughput performance measurement of the existing scheme, black hole attack, and PPDM is measured in high 6G data rate. In SAODV existing approach, the throughput performance reaches about a maximum of 20,000 Kbps in the network. Still, in the case of black hole assault, the throughput performance is negligible or about 500 bits/sec in all different vehicle density but after applying the proposed PPDM scheme, the throughput is enhanced up to 27000Kbps. Thus, the proposed PPDM scheme improves the network performance and provides the attacker-free background of communication between sender and receiver through intermediate vehicles.

Fig. 3
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Throughput performance analysis

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8.2 Packet Drop Analysis

The attacker's presence in the network will degrade the routing performance. The vehicles in the attacker's range can send the fake message to the sender or send the wrong information of traffic to the sender vehicle. The number of vehicles directly connected to the assailant and attacker receives the packets from the sender and drops the whole packets mentioned in Fig. 4. The data dropping also increases due to delay in response of leading vehicles. The vehicles OBU used 6G standard for communication. The traffic status sharing using 6G improves the traffic controlling and examines traffic information. The performance data drop will decrease due to malicious vehicles mentioned in all different vehicle density scenarios. The number of attacker vehicles in the network is in different quantities in other vehicles density scenarios. The data dropping in the network is more than 30,000 in the presence of an attacker. That is, the attacker consumes the data packets in the network as well as the remainder of the data received at the destination, but the data received is much less.

Fig. 4
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Packets dropping analysis

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8.3 PDR Analysis

The packets percentage performance is measured through of delivery ratio (PDR). This graph (Fig. 5) evaluated the PDR analysis in black hole attack, previous security scheme, and privacy-preserving under denser traffic management (PPDM). The standard routing performance is only evaluated to stint the network performance after applying the proposed PPDM scheme. The PDR of black hole attack in the network is only 20%, which means an 80% data drop in 20 vehicles density and the rest of scenarios PDR performance showing in between 5 and 10%. The PPDM scheme improves the network performance and provides secure routing. The network's performance almost provides 80% PDR minimum in 50 vehicles, 91% maximum in 10 vehicles, and 20 vehicle scenarios. After applying a security scheme against attack, PDR performance is improved and better than SAODV. The proposed security scheme has enhanced the performance in the presence of malicious vehicles. The performance of the proposed method reduces the overhead that improves receiving.

Fig. 5
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PDR performance analysis

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8.4 End-to-End Delay Analyses

The end-to-end delay analysis is measured in the presence of the attacker, in the existing security scheme and in PPDM proposed scheme mentioned in Fig. 6. The performance is measured in a scenario of five different vehicles density, and 6G high data rate quick response improves communication capability. The main reason for the delay is re-establishing the connection frequently due to link breakage or successful not receiving the data at the destination. The end-to-end delay in attacker presence is high and the delay is minimized by applying the existing security scheme. The proposed PPDM scheme minimizes the delay by providing strong connection establishment in between source to destination. The delay in the network degrades the routing performance due to the presence of a black hole attacker.

Fig. 6
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Delay performance analysis

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9 Conclusion and Future Scope

The privacy-preserving under denser traffic management for the 6G-VANET (PPDM) security algorithm provides security from black hole attack/s, which is to be a part of a fake path established for loss data packets. The 6G existence in the network also reduces the possibility of delay in communication because a sufficient bandwidth is available for proper traffic status delivery. The performance metrics show the difference in the performance of attacker, previous SAODV, and novel PPDM. It is clearly shown that proposed scheme is providing secure communication and prevent network from attacker. The PDR is about 92% evaluated in novel PPDM scheme, and it is about to 5% more than the existing SAODV. The presence of an attacker is atrocious because packet dropping is really more than 30,000 packets (50 vehicles scenario). The PPDM reduces the packet dropping and enhances receiving of data packets, i.e., also enhances throughput in 6G communication. The attacker's presence is confirmed by detecting the loss of data and fake route information in a dynamic network. The PPDM minimizes overhead and delay, i.e., the leading cause degrades the routing performance because more packets are drooping that enhancing the delay.

In future, the same concept also simulates with MP-DSR multipath routing protocols and also using a security concept with a location tracker system that traces attackers easily in a dynamic network. The location tracker system maintains the separate table for attacker and normal nodes with its mobility speed.