Jyoti Grover

Dr. Jyoti Grover

orcid

Research Focus & Metrics

Academic Career Length

17Years (2010-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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2 February 2022 in Vehicular Communications
Verified
Journal Article
Closed access
JGJyoti Grover
Jyoti Grover

1 January 2011
Verified
Book Chapter
Closed access
PDF file
JGJyoti Grover
Jyoti Grover
NPNitesh Kumar Prajapati
Nitesh Kumar Prajapati
VLVijay Laxmi
Vijay Laxmi
MGManoj Singh Gaur
Manoj Singh Gaur

19 March 2022 in Computers and Electrical Engineering
Verified
Journal Article
Closed access
SGSubham Kumar Gupta
Subham Kumar Gupta
MTMeenakshi Tripathi
Meenakshi Tripathi
JGJyoti Grover
Jyoti Grover

31 October 2022 in Computer Communications
Verified
Journal Article
Closed access
GSGirish Sharma
Girish Sharma
JGJyoti Grover
Jyoti Grover
AVAbhishek Verma
Abhishek Verma

1 January 2021 in Vehicular Communications
Verified
Journal Article
Closed access
RSRukhsar Sultana
Rukhsar Sultana
JGJyoti Grover
Jyoti Grover
MTMeenakshi Tripathi
Meenakshi Tripathi

14 November 2011
Verified
Conference Paper
Open access
PDF file
JGJyoti Grover
Jyoti Grover
MGManoj Singh Gaur
Manoj Singh Gaur
VLVijay Laxmi
Vijay Laxmi
NPNitesh Kumar Prajapati
Nitesh Kumar Prajapati
Vehicular Ad Hoc Network (VANET) is vulnerable to many security threats. One severe attack is Sybil attack, in which a malicious node forges a large number of fake identities in order to disrupt the proper functioning of VANET applications. In this paper, a distributed and robust approach is presented to defend against Sybil attack. Proposed scheme localizes the fake identities of malicious vehicles by analyzing the consistent similarity in neighborhood information of neighbors of these fake identities. Beacon packets are exchanged periodically by all the vehicles to announce their presence and get aware of neighboring nodes. Each node periodically keep a record of its neighboring nodes. In proposed approach, each node exchange groups of its neighboring nodes periodically and perform the intersection of these groups. If some nodes observe that they have similar neighbors for a significant duration of time, these similar neighbors are identified as Sybil nodes. Proposed approach is able to locate Sybil nodes quickly without the requirement of secret information exchange and special hardware support. We evaluate our proposed approach on the realistic traffic scenario. Experiment results demonstrate that detection rate increases when optimal numbers of Sybil nodes are forged by the attacker.