RT Journal Article
A1 J. Anitha Ruth
A1 H. Sirmathi
A1 A. Meenakshi

PB iet
T1 Secure data storage and intrusion detection in the cloud using MANN and dual encryption through various attacks
JN IET Information Security
VO 13
IS 4
SP 321
OP 329
AB Nowadays, it is very important to maintain a high level security to ensure safe and trusted communication of information between various organisations. But secured data communication over the Internet and any other network is always under threat of intrusions and misuses. So intrusion detection system (IDS) has become a needful component in terms of computer and network security. In this research, the authors have intended to propose an effective method for text data based IDS and secure data storage. In the proposed preprocessing steps, the input text document is preprocessed and then change to the desired format. Next the resultant output is fed to the IDS. Here user text data is checked; whether the given data is normal or intrusive based on a modified artificial neural network (MANN). Here traditional neural network is modified by means of modified particle swarm optimisation. The final process of the authors’ proposed method is to encrypt the file using dual encryption algorithms (RSA and AES). To improve the storage security of the proposed method, steganography techniques are utilised after the dual encryption. Their proposed system is implemented with the help of Cloud simulator in the working platform Java.
K1 user text data
K1 intrusion detection system
K1 dual encryption algorithms
K1 steganography techniques
K1 Internet
K1 input text document
K1 data communication
K1 secure data storage
K1 network security
K1 MANN
K1 storage security
K1 modified artificial neural network
K1 RSA
K1 IDS
K1 particle swarm optimisation
K1 cloud simulator
K1 computer security
K1 AES
K1 Java
DO https://doi.org/10.1049/iet-ifs.2018.5295
UL https://digital-library.theiet.org/;jsessionid=2cvcgk7qkgdrr.x-iet-live-01content/journals/10.1049/iet-ifs.2018.5295
LA English
SN 1751-8709
YR 2019
OL EN