@ARTICLE{ iet:/content/journals/10.1049/iet-ifs.2018.5295, author = {J. Anitha Ruth}, author = {H. Sirmathi}, author = {A. Meenakshi}, keywords = {user text data;intrusion detection system;dual encryption algorithms;steganography techniques;Internet;input text document;data communication;secure data storage;network security;MANN;storage security;modified artificial neural network;RSA;IDS;particle swarm optimisation;cloud simulator;computer security;AES;Java;}, ISSN = {1751-8709}, language = {English}, abstract = {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.}, title = {Secure data storage and intrusion detection in the cloud using MANN and dual encryption through various attacks}, journal = {IET Information Security}, issue = {4}, volume = {13}, year = {2019}, month = {July}, pages = {321-329(8)}, publisher ={Institution of Engineering and Technology}, copyright = {© The Institution of Engineering and Technology}, url = {https://digital-library.theiet.org/;jsessionid=45o3sigfh5tfk.x-iet-live-01content/journals/10.1049/iet-ifs.2018.5295} }