Browsing by Author "Deepa V"

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A NOVEL NETWORK INTRUSION DETECTION SYSTEM FOR PREVENTING FLOODING ATTACKS PACKET DROPPING ATTACKS IN MANETS USING DEEP LEARNING ALGORITHM (Conference Paper)
(Springer Science and Business Media Deutschland GmbH, 2024-04-30) Deepa V; Radha N
The network intrusion detection System (NIDS) is more required for maintaining security in the networks. On the other hand it faces more challenges in wireless network than compared to wired network. A wireless network with several nodes connected to one another via wireless components like transmitters and receivers is termed as Mobile Ad Hoc Network (MANET). The characteristics of MANETs are unique pattern, bandwidth, energy, unstable topology, and security. Because of this, MANETs are susceptible to an extensive collection of extortions and assaults, including denial of service (DoS), flooding, impersonation, black holes, and gray holes attacks. This research concentrates on attacks in MANET. This study introduces a novel Enhanced Generative Adversarial Network with Bidirectional Long Short-Term Memory and Cross-correlated Convolutional Neural Network (EGAN-BiLSTM-CCNN) model in MANET. This model was deployed in cluster heads (CHs) for IDS based on the local information of nodes. First this work uses network simulator (NS2) to simulate the flooding, packet dropping in MANET environment. The parameters derived from the nodes must be capable to accurately depict network behavior and distinguish the typical and anomalous network activity. Every sampling interval time results in the creation of a training dataset that includes every training instance, network activity during the designated interval, and an indication of the types of attacks that occurred during this interval. The EGAN-BiLSTM-CCNN IDS model deployed within each CH for intrusion detection, achieving a balance between security and performance in MANETs. Next, the developed model is utilized in the cluster header to identify malicious nodes, hence preventing MANET attacks and improving network speed.
CANDIDATE GENE IDENTIFICATION APPROACH: PROGRESS AND CHALLENGES
(International Journal for Scientific Research and Developement (IJSRD)., 2020-01) Deepa V; Varsha N; Varshinee M
Gene expression profile analysis is the study of the way in which genes are transcribed to produce functional gene products (functional RNA species or protein products). There has been tremendous innovation in gene expression technologies, including high-throughput assays such as microarrays, and sequence-based techniques such as RNA-Seq. The Gene expressions are collected and analyzed for normal or disease genes. Using this project the system can diagnose types of diseases and abnormalities which may affect the user.
A SURVEY: IOT BASED HOME SECURITY AND AUTOMATION SYSTEM
(Kalahari Journals, 2022-01) Vijayalakshmi K; Rasika S; Ponmalar S; Deepa V
Advance in knowledge from last few decades opens doors to various threats to human and his environments. Individuals with the progression in security had taken numerous measures to control the bullying for protecting their properties. From time to time numerous interruption finding systems conventional for earmark intruders from home environment and provide tangible benefits to users, but can also expose users to significant security risk. Smart home security system is gaining popularity for industry, government, and academia as well as for distinct that has the potential to bring significant private, specialized and economic benefits. This paper signifies smart home security system and response rapidly to alarm incidents and has a friendly user interface. Special emphasis is placed on the experimental security analysis of such developing smart home platform by separating into two case scenarios. The paper will conclude by discussing future perspective and challenges associated with the development of security system for home.