THILAGAM T

EDUCATION

M.E (CSE)
Ph.D (PUSUING)

RESEARCH, TEACHING, or OTHER INTERESTS

Computer Engineering, Artificial Intelligence, Computer Science, Computer Networks and Communications

Scopus Publications

LM-GA: A Novel IDS with AES and Machine Learning Architecture for Enhanced Cloud Storage Security
Thilagam T and Aruna R
Anapub Publications
Cloud Computing (CC) is a relatively new technology that allows for widespread access and storage on the internet. Despite its low cost and numerous benefits, cloud technology still confronts several obstacles, including data loss, quality concerns, and data security like recurring hacking. The security of data stored in the cloud has become a major worry for both Cloud Service Providers (CSPs) and users. As a result, a powerful Intrusion Detection System (IDS) must be set up to detect and prevent possible cloud threats at an early stage. Intending to develop a novel IDS system, this paper introduces a new optimization concept named Lion Mutated-Genetic Algorithm (LM-GA) with the hybridization of Machine Learning (ML) algorithms such as Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM). Initially, the input text data is preprocessed and balanced to avoid redundancy and vague data. The preprocessed data is then subjected to the hybrid Deep Learning (DL) models namely the CNN-LSTM model to get the IDS output. Now, the intruded are discarded and non-intruded data are secured using Advanced Encryption Standard (AES) encryption model. Besides, the optimal key selection is done by the proposed LM-GA model and the cipher text is further secured via the steganography approach. NSL-KDD and UNSW-NB15 are the datasets used to verify the performance of the proposed LM-GA-based IDS in terms of average intrusion detection rate, accuracy, precision, recall, and F-Score.


Intrusion detection for network based cloud computing by custom RC-NN and optimization
T. Thilagam and R. Aruna
Elsevier BV



Effective offline handwritten text recognition model based on a sequence-to-sequence approach with CNN–RNN networks
R. Geetha, T. Thilagam, and T. Padmavathy
Springer Science and Business Media LLC



A Review on the Effectiveness of Machine Learning and Deep Learning Algorithms for Cyber Security
R. Geetha and T. Thilagam
Springer Science and Business Media LLC



Tamilian Cryptography: An Efficient Hybrid Symmetric Key Encryption Algorithm
R. Geetha, T. Padmavathy, T. Thilagam, and A. Lallithasree
Springer Science and Business Media LLC



A survey on security and privacy issues in cloud computing

RECENT SCHOLAR PUBLICATIONS

Intrusion detection for network based cloud computing by custom RC-NN and optimization
T Thilagam, R Aruna
ICT Express 7 (4), 512-520 2021



Effective offline handwritten text recognition model based on a sequence-to-sequence approach with CNN–RNN networks
R Geetha, T Thilagam, T Padmavathy
Neural Computing and Applications 33 (17), 10923-10934 2021



A review on the effectiveness of machine learning and deep learning algorithms for cyber security
R Geetha, T Thilagam
Archives of Computational Methods in Engineering 28 (4), 2861-2879 2021



Trash Monitoring and Alerting System Using Internet of Things
T Thilagam, SN Ananthi, T Padmavathy, A Lallithashri
Journal of Computational and Theoretical Nanoscience 17 (5), 2363-2368 2020



Tamilian cryptography: an efficient hybrid symmetric key encryption algorithm
R Geetha, T Padmavathy, T Thilagam, A Lallithasree
Wireless Personal Communications 112, 21-36 2020



SURVEY ON SENSING AND ALERTING OVERFLOW OF TRASH-USING IOT
T Thilagam
International Journal of Advanced Research in Management, Architecture 2018



A Survey on Security and Privacy Issues in Cloud Computing
CA T. Thilagam1* , K. Arthi2
International Journal of Engineering & Technology 7 (2.4) 2018



PRIVACY PRESERVING NATURAL LANGUAGE PROCESSING IN THE CLOUD SUPPORTING SIMILARITY BASED TEXT RETRIEVAL THROUGH BLIND STORAGE.
T Thilagam.
INTERNATIONAL JOURNAL OF ADVANCED RESEARCH 4 (`11), 2256-2260 2016



RRW - A RESILIENT REVERSIBLE WATERMARKING TECHNIQUE FOR THE PRECLUSION OF INFORMATION FROM CYBER PUNKERS
T.THILAGAM
International Journal of Engineering Research-Online A Peer Reviewed 2016



Service Oriented Multi-Agent System
MKDS T.Thilagam,S.Rekha
International Journal of Emerging Technology And Advanced Engineering 5 (3 2015



Invulnerable & Increase rate multicast routing in Wireless Networks
RA R.Kannan, T.Thilagam
International Journal of P2P Networks Trends and Technology 17 (3), 10-13 2015



Lm-Ga: A Novel Ids with Aes and Machine Learning Architecture for Enhanced Cloud Storage Security
T Aruna




RESEARCH ARTICLE ISSN: 2321-7758
T THILAGAM, R VINOTH

MOST CITED SCHOLAR PUBLICATIONS

A review on the effectiveness of machine learning and deep learning algorithms for cyber security
R Geetha, T Thilagam
Archives of Computational Methods in Engineering 28 (4), 2861-2879 2021
Citations: 88



Intrusion detection for network based cloud computing by custom RC-NN and optimization
T Thilagam, R Aruna
ICT Express 7 (4), 512-520 2021
Citations: 54



Effective offline handwritten text recognition model based on a sequence-to-sequence approach with CNN–RNN networks
R Geetha, T Thilagam, T Padmavathy
Neural Computing and Applications 33 (17), 10923-10934 2021
Citations: 35



Tamilian cryptography: an efficient hybrid symmetric key encryption algorithm
R Geetha, T Padmavathy, T Thilagam, A Lallithasree
Wireless Personal Communications 112, 21-36 2020
Citations: 23



A Survey on Security and Privacy Issues in Cloud Computing
CA T. Thilagam1* , K. Arthi2
International Journal of Engineering & Technology 7 (2.4) 2018
Citations: 4



RRW - A RESILIENT REVERSIBLE WATERMARKING TECHNIQUE FOR THE PRECLUSION OF INFORMATION FROM CYBER PUNKERS
T.THILAGAM
International Journal of Engineering Research-Online A Peer Reviewed 2016
Citations: 1