BOTVEILLANCE: A Vehicular Botnet Surveillance Attack against Pseudonymous Systems in VANETs

Garip, Mevlut Turker; Reiher, Peter; Gerla, Mário

doi:10.23919/wmnc.2018.8480909

Cited by 12 publications

(3 citation statements)

References 16 publications

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“…This communication protocol called "Ghost" allows the hacker to hide its remote communication with the infected vehicle. The authors considered two bot malware attacks feasible against vehicular networks: Botveillance [52], and congestion attacks [53]. Botveillance is an adaptive cooperative surveillance attack against pseudonymous systems in vehicular networks, which is based on vehicular botnet and performed by vehicles themselves without depending on any additional hardware.…”

Section: Related Workmentioning

confidence: 99%

AntibotV: A Multilevel Behaviour-Based Framework for Botnets Detection in Vehicular Networks

et al. 2021

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Connected cars offer safety and efficiency both for individuals as well as for fleets of vehicles, companies and public transportation. However, equipping vehicles with information and communication technologies also raises privacy and security concerns, which significantly threaten the user's data and life. Using a bot malware, a hacker may compromise a vehicle and control it remotely, for instance he can disable breaks or start the engine remotely. In this paper, besides in-vehicle attacks existing in the literature, we consider new zero-day bot malware attacks specific to vehicular context, WSMP-Flood and Geo-WSMP Flood. Then, we propose AntibotV, a multilevel behaviour-based framework for vehicular botnets detection in vehicular networks. The proposed framework combines two main modules for attacks detection, the first one monitors the vehicles activity at the network level, whereas the second one monitors the in-vehicle activity. The two intrusion detection modules have been trained on historical network and in-vehicle communication using decision tree algorithms. The experimental results showed that the proposed framework outperforms existing solutions, it achieves a detection rate higher than 97% and a false positive rate lower than 0.14%.

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Section: Related Workmentioning

confidence: 99%

AntibotV: A Multilevel Behaviour-Based Framework for Botnets Detection in Vehicular Networks

et al. 2021

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“…Vehicular bots that are compromised, hacked, or rogue nodes penetrate the network and perform DDoS attacks on the connected vehicles networks infrastructure. The bots overload the network resources and hinder connection with other legitimate nodes, thus disrupting the function and operation of connected vehicle applications [20]. The bots can also inject, alter, remove, or send fake messages to other nodes in the network, which may be hazardous to road users [21].…”

Section: Introductionmentioning

confidence: 99%

Simulation of Vehicular Bots-Based DDoS Attacks in Connected Vehicles Networks

Abdul Razak,

Fang,

Kamis

et al. 2023

HighTech. Innov. J.

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Connected vehicles are more vulnerable to attacks than wired networks since they involve rapid mobility, continuous data flow across connected nodes, and dynamic network design in a distributed network environment. Distributed Denial of Service (DDOS) is one of the most common and dangerous security attacks on connected vehicle networks. Attackers can remotely control malicious nodes that are programmed to attack other nodes known. The compromised nodes are known as botnets, which will constantly flood the target nodes with User Datagram Protocol (UDP) packets, disrupting the target nodes data flow and operation. Hence, the goal of this research is to create and simulate a vehicular bot-based Distributed Denial of Service (DDoS) assault in connected vehicle networks. A simulation-based methodology is implemented to observe the impact of the number of bots, DDoS rate, and maximum bulk packet size on network performance. Using the NS-3 network simulator, 73 random mobile vehicle nodes with up to 100 vehicle bots were simulated, and the results are discussed. Regardless of the computational constraints, the findings from this study adds to understanding the risks and problems associated with data transmission by analyzing the impact of vehicular bot-based DDoS attacks on connected vehicle performance. Doi: 10.28991/HIJ-2023-04-04-014 Full Text: PDF

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“…The safety together with nonsafety services was included in these. In reality, there are numerous services, say the surveillance [12] together with route planning services [13]. Yet, several challenges still present for the VANET's management and it's deployment in the instance of secured DC [14].…”

Section: Introductionmentioning

confidence: 99%

Improving The Security Of Data Communication in Vanets Using ASCII-ECC Algorithm

Sajini

Anita

Janet³

2021

Preprint

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Now-a-days, with the augmenting accident statistics, Vehicular Ad-hoc Networks (VANET) are turning out to be more popular, which in-turn eradicates accidents in addition to damage to the vehicles together with populace. In a VANET, message can well be transmitted within a pre-stated region to attain safety of a system and also its efficacy. Next, it is challenge to ensure authenticity of messages in such a dynamic environment. Though some researchers have already worked on this, security has not been much focussed. Thus, secured data communication with enhanced security on the VANET environment utilizing the American Standard Code for Information Interchange centred Elliptic Curve Cryptography (ASCII-ECC) is proposed. The proposed scheme allows all vehicles to register with the Trusted Authority (TA) and uses Median-centred K-Means (MKM) to find out the cluster head among all cluster and at the last phase verification is done by TA. The performance of the proposed algorithm ASCII-ECC is analysed and proved that the system renders better performance when it is weighed against the top-notch methods.

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BOTVEILLANCE: A Vehicular Botnet Surveillance Attack against Pseudonymous Systems in VANETs

Cited by 12 publications

References 16 publications

AntibotV: A Multilevel Behaviour-Based Framework for Botnets Detection in Vehicular Networks

AntibotV: A Multilevel Behaviour-Based Framework for Botnets Detection in Vehicular Networks

Simulation of Vehicular Bots-Based DDoS Attacks in Connected Vehicles Networks

Improving The Security Of Data Communication in Vanets Using ASCII-ECC Algorithm

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