A Novel Pseudonym Assignment and Encryption Scheme for Preserving the Privacy of Military Vehicles

Tandon, Righa; Gupta, Praveen

doi:10.14429/dsj.71.15534

Cited by 6 publications

(2 citation statements)

References 8 publications

(3 reference statements)

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“…The authors (Farman et al , 2022) propose source location privacy preservation algorithm for VANET. The authors propose location privacy preservation scheme for military vehicles using pseudonym and encryption schemes (Tandon and Gupta, 2021). Arivarasi and Ramesh (2021) uses trust-based authentication and encryption algorithm to address source location privacy protection.…”

Section: Related Workmentioning

confidence: 99%

Source location privacy preservation in IoT-enabled event-driven WSNs

Sharma

Bhatt

2022

IJPCC

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Purpose Privacy preservation is a significant concern in Internet of Things (IoT)-enabled event-driven wireless sensor networks (WSNs). Low energy utilization in the event-driven system is essential if events do not happen. When events occur, IoT-enabled sensor network is required to deal with enormous traffic from the concentration of demand data delivery. This paper aims to explore an effective framework for safeguarding privacy at source in event-driven WSNs. Design/methodology/approach This paper discusses three algorithms in IoT-enabled event-driven WSNs: source location privacy for event detection (SLP_ED), chessboard alteration pattern (SLP_ED_CBA) and grid-based source location privacy (GB_SLP). Performance evaluation is done using simulation results and security analysis of the proposed scheme. Findings The sensors observe bound events or sensitive items within the network area in the field of interest. The open wireless channel lets an opponent search traffic designs, trace back and reach the start node or the event-detecting node. SLP_ED and SLP_ED_CBA provide better safety level results than dynamic shortest path scheme and energy-efficient source location privacy protection schemes. This paper discusses security analysis for the GB_SLP. Comparative analysis shows that the proposed scheme is more efficient on safety level than existing techniques. Originality/value The authors develop the privacy protection scheme in IoT-enabled event-driven WSNs. There are two categories of occurrences: nominal events and critical events. The choice of the route from source to sink relies on the two types of events: nominal or critical; the privacy level required for an event; and the energy consumption needed for the event. In addition, phantom node selection scheme is designed for source location privacy.

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Section: Related Workmentioning

confidence: 99%

Source location privacy preservation in IoT-enabled event-driven WSNs

Sharma

Bhatt

2022

IJPCC

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“…The inspiration for the attacker may rise from different intentions. The most attractive ones would be system vulnerabilities and valuable information [9,25,29]. The number of attacks over a network and other mediums has enlarged radically in recent years.…”

Section: Introductionmentioning

confidence: 99%

Predictive machine learning-based integrated approach for DDoS detection and prevention

Kebede

Tiwari

et al. 2021

Multimed Tools Appl

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Distributed Denial of Service attack has been a huge threat to the Internet and may carry extreme losses to systems, companies, and national security. The invader can disseminate Distributed denial of service (DDoS) attacks easily, and it ends up being significantly harder to recognize and forestall DDoS attacks. In recent years, many ITbased companies are attacked by DDoS attacks. In this view, the primary concern of this work is to detect and prevent DDoS attacks. To fulfill the objective, various data mining techniques such that Jrip, J48, and k-NN have been employed for DDoS attacks detection. These algorithms are implemented and thoroughly evaluated individually to validate their performance in this domain. The presented work has been evaluated using the latest dataset CICIDS2017. The dataset characterizes different DDoS attacks viz. brute force SSH, brute force FTP, Heartbleed, infiltration, botnet TCP, UDP, and HTTP with port scan attack. Further, the prevention method takes place in progress to block the malicious nodes participates in any of the said attacks. The proposed DDoS prevention works in a proactive mode to defend all these attack types and gets evaluated concerning various parameters such as Throughput, PDR, End-to-End Delay, and NRL. This study claimed that the proposed technique outperforms with respect to the AODV routing algorithm.

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TrafC‐AnTabu: AnTabu routing algorithm for congestion control and traffic lights management using fuzzy model

Verma

Tandon

Gupta

2021

Internet Technology Letters

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Traffic congestion is becoming one of the severe problems around the globe. The rate at which vehicles are increasing is exponentially proportional to more complex issues. Therefore, it becomes necessary to efficiently manage traffic flow to avoid congestion on the roads and other complex problems. In this paper, we have proposed a system model that uses the AnTabu routing algorithm to overcome the severe problem of traffic congestion. We have also implemented a fuzzy model for managing the traffic lights on the road intersections. From the obtained results, it is found that the proposed system model has minimized the average travel time of vehicles and has increased the throughput of vehicles on the road intersections.

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A Novel Pseudonym Assignment and Encryption Scheme for Preserving the Privacy of Military Vehicles

Cited by 6 publications

References 8 publications

Source location privacy preservation in IoT-enabled event-driven WSNs

Source location privacy preservation in IoT-enabled event-driven WSNs

Predictive machine learning-based integrated approach for DDoS detection and prevention

TrafC‐AnTabu: AnTabu routing algorithm for congestion control and traffic lights management using fuzzy model

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