M
Mayank Dave
Researcher at National Institute of Technology, Kurukshetra
Publications - 183
Citations - 2805
Mayank Dave is an academic researcher from National Institute of Technology, Kurukshetra. The author has contributed to research in topics: Wireless sensor network & Digital watermarking. The author has an hindex of 25, co-authored 177 publications receiving 2271 citations. Previous affiliations of Mayank Dave include Shiv Nadar University.
Papers
More filters
Posted Content
Mobile Agent as an Approach to Improve QoS in Vehicular Ad Hoc Network
Rakesh Kumar,Mayank Dave +1 more
TL;DR: This paper has proposed mobile agent as a mechanism to handle the traffic problem on road to provide the better QoS (Quality of Service) in vehicular ad hoc network to improve the safety application and driver comfort.
Proceedings Article
Implementing a Speech Recognition System Interface for Indian Languages
TL;DR: In this paper the implementation of one issue Speech Recognition for Indian Languages is presented and the main challenges that are to be faced are Speech to Text conversion & Text To Speech (TTS) conversion.
Journal ArticleDOI
Voting‐based intrusion detection framework for securing software‐defined networks
TL;DR: An intrusion detection framework is proposed to detect DDoS attacks against SDN and relies on voting‐based ensemble model for the attack detection, which achieves better performance in terms of accuracy as compared with other existing models.
Journal ArticleDOI
An attack resistant key predistribution scheme for wireless sensor networks
Priyanka Ahlawat,Mayank Dave +1 more
TL;DR: A secure hybrid key predistribution scheme (HKP-HD) for wireless sensor networks (WSN) that combines the robustness of the q-composite scheme with threshold resistant polynomial scheme to make the network more resistant against the node capture attacks.
Journal ArticleDOI
Kohonen neural network classifier for voltage collapse margin estimation
Sushil Chauhan,Mayank Dave +1 more
TL;DR: In this paper, an artificial neural network based method for on-line voltage collapse margin estimation is presented, in which the distance of operating point from critical point, measured in terms of system loading may be regarded as margin to voltage collapse.