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Detection adn Prevention of Security attack in VANET simulation using SUMO, NS3

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Detection and Prevention of Security Attacks in VANET.

Abstract

In the current generation, road accidents and security problems increase dramatically worldwide in our day to day life. In order to overcome this, Vehicular Ad-hoc Network (VANETs) is considered as a key element of future Intelligent Transportation Systems (ITS). With the advancement in vehicular communications, the attacks have also increased, and such architecture is still exposed to many weaknesses which led to numerous security threats that must be addressed before VANET technology is practically and safely adopted. Distributed Denial of Service (DDoS) attack, replay attacks and Sybil attacks are the significant security threats that affect the communication and privacy in VANET. As simulators are being used in our work, we have discussed OMNET++ which is a new modernized latest mobility and network simulators as well as data network simulator. This is also integrated with the road traffic simulator SUMO with Veins, an open-source framework for VANET simulation. The objective of our work is to design an algorithm to detect and prevent various kinds of attacks using Java Security and Cryptography libraries. An analysis has also been done by applying four protocols on an existing scenario of real traffic simulator using OpenStreetMap and the best suitable protocol has been selected for further application.

Introduction

In the current generation, road accidents and security problems increase dramatically worldwide in our day to day life. In order to overcome this, Vehicular Ad-hoc Network (VANETs) is considered as a key element of future Intelligent Transportation Systems (ITS). With the advancement in vehicular communications, the attacks have also increased, and such architecture is still exposed to many weaknesses which led to numerous security threats that must be addressed before VANET technology is practically and safely adopted. Distributed Denial of Service (DDoS) attack, replay attacks and Sybil attacks are the significant security threats that affect the communication and privacy in VANET. As simulators are being used in our work, we have discussed OMNET++ which is a new modernized latest mobility and network simulators as well as data network simulator. This is also integrated with the road traffic simulator SUMO with Veins, an open-source framework for VANET simulation. The objective of our work is to design an algorithm to detect and prevent various kinds of attacks using Java Security and Cryptography libraries. An analysis has also been done by applying four protocols on an existing scenario of real traffic simulator using OpenStreetMap and the best suitable protocol has been selected for further application.

Vehicular Ad-hoc Network (VANET) provides a smart transportation system owing to Vehicle to Infrastructure (V2I) and Vehicle to Vehicle (V2V) message dissemination with an objective to provide safety on roads. Nearly 1.25 million people die each year and on an average 3,287 deaths, a day is observed according to the world health organization.

Proposed System

This paper proposes the methods for detecting and preventing security attacks for both V2V and V2I communication in VANETs. More specifically we are going to address security in VANET “beaconing messages”, i.e., messages sent from a vehicle to its neighbours with information of location, speed, braking and other sensorial data that aid safe decision making. The main contribution of the paper has been given in the following points:   Detecting some major security attacks which are highly probable and that exploit the both V2V and V2I communication by sending the false information to other vehicles and RSU in VANET communication as listed in the following. Sybil Attack Reply Attack DDOS Attack Design of an Algorithm for detecting the Sybil nodes by considering the timestamp and velocity parameter of the beacon messages sent from the vehicle nodes which estimates the distance and predict the current position. Provided various measures to prevent the attackers in VANET communication. Implemented a system which detect the best routing protocol for the VANET communication by considering the realistic scenario generated from OSM and simulation has been done using SUMO and NS3.

Implementation

Firstly we addressed the identification requirement. To uniquely identify a vehicle we provided the Vehicle Identification Number(VIN) using CA authority which distributes unique key for each node.

To solve the Problem of authentication and ensure message integrity and non-repudiation of the sender we implemented digital signature for each vehicle and the messages.

Being a critical system we have also have to ensure high availability of the system. For that we intend to detect if a user is sending messages too frequently at the communication unit level, only passing them to the OBU after a minimum delta time between messages has passed. We can’t ignore all future messages because they can be critical, but we drop the excess ones that won't affect road safety. How it all works shown in Fig. 2.

Replay Attack

Detection: We have to guarantee that messages are fresh, making it impossible for an attacker to replay them later on. To accomplish this we decided to attach a timestamp to every messages from vehicle nodes. RSU stores the first 20 messages from each vehicle for certain period, within that time if same vehicle tries to re-send the same messages, we then calculate the time stamp of the messages, if the timestamp is above the given threshold, RSU will drop the messages sent by vehicle and detect it as Replay attack nodes. Prevention: When RSU detects the vehicle as Replay Node attacker, it will not let any messages from attacker to vehicle nodes by checking in the cache memory and dropping messages with a timestamp above a certain threshold when compared to the current time.

Sybile Attack

Detection: Sybil attack is an identity spoofing attack that is based on creating a forged identity in a network and misusing it for his needs Proposed system first RSU checks if message sent from vehicle is authenticated and signed by CA, then estimates the speed of the node by predicting the timestamp of the last message sent from the node. The after RSU predicts the Position of the vehicle by considering estimated speed and last speed recorded in the RSU table. If the response comes below the certain threshold RSU detect it as a Sybille Node. Prevention: After detecting the Sybille node, RSU sends request to CA to revoke the certificate and identity of the Sybille node. After getting response from CA, RSU stores the information of the Sybille node in RSU Cache to make verification easy next time. Finally, RSU informs the vehicle about the Sybille node and drops the messages.

DDOS Attack

Detection: The attacker attacks the communication medium to create channel jam. The channel will not be available anymore to the nodes and they are not able to access it. Hence Proposed system, RSU calculate the frequency and velocity of the messages coming from vehicle, then RSU checks with upper and lower bound of the threshold, if the Result is Higher than the certain threshold, RSU detects those as the DDOS attackers nodes. Prevention: After detecting the DDOS nodes, RSU sends request to CA to revoke the certificate and identity of the Sybille node. After getting response from CA, RSU stores the information of the Sybille node in RSU Cache to make verification easy next time. Finally, RSU informs the vehicle about the Sybille node and drops the messages

Best Routing Protocol: the best reliable routing protocol is required for the transmission in the real-world scenario. To achieve that, we have implemented system which generates the real-world scenario by selecting the specified area from the OpenStreetMap Framework. where number of vehicles, Trucks, Traffic Signals and pedestrians were selected. Then, we analysed the generated scenario in Urban simulator called SUMO.

MIT License

Copyright (c) 2020 Naveen R

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.


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