Faculty Publications
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Publications by NITK Faculty
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Item Map and Trie based Compression Algorithm for Data Transmission(Institute of Electrical and Electronics Engineers Inc., 2020) Ghuge, S.In-text compression algorithms, a set of symbols as alphabets are defined. These alphabets are the basic building blocks of the language. Traditionally 8-bit ASCII characters are chosen as alphabets. In this paper, an approach that chooses larger symbols as alphabets is proposed. For example, in the case of the English language, a set of words and special characters are chosen as alphabets. In the case of HTML documents, HTML tags are included along with alphabets from the English language described before. Better compression results can be achieved since words have larger byte size than individual ASCII characters but still get mapped to similar-sized encodings. Compressing the data to be transmitted across networks implies less usage of network bandwidth, faster transmission of data, sending several data files over a single transfer and faster reading and writing of data. Thus, the transmission of a compressed file is cost-effective and also saves time in communication. The results prove that the proposed approach gives better file size compression concerning the compression ratio when compared with state-of-the-art algorithms. © 2020 IEEE.Item Multilayer Technique to Secure Data Transfer in Private Cloud for SaaS Applications(Institute of Electrical and Electronics Engineers Inc., 2020) Ghuge, S.; Kumar, N.; Savitha, S.; Suraj, V.In recent times Cloud Computing[CC] has emanated as a substitute paradigm for hosting and providing services over the Internet. Software as a Service (Saas) is one among such services that deliver services to the end-users on pay-as-you-go manner. In spite of all its advantages, security always seems to be major drawback. For securing the users' data on the cloud, this paper proposes an application model for any SaaS application hosted on a private cloud environment. The application is divided into two micro-services, where the first one is Application Layer Firewall and second one is a secured application to login and send sensitive data. The application layer firewall checks for any malicious activity and prevents the intruder to access the features present in the application. Subsequently, a Hidden Markov Model layer is implemented which is a probability-based intrusion detection technique. The second micro-service uses Advanced Encryption Standard (AES) encryption algorithm to encrypt documents having sensitive data, which have to be transferred within the private cloud. Further security is provided by proposing a novel Video Steganography approach using the Least Significant Bit (LSB) technique. This paper gives a detailed structure of hiding the data using multiple levels of security. Thus, this paper provides a holistic approach to implement a high level of security in SaaS applications. © 2020 IEEE.Item Deep Neural Network Models for Detection of Arrhythmia based on Electrocardiogram Reports(Institute of Electrical and Electronics Engineers Inc., 2020) Ghuge, S.; Kumar, N.; Shenoy, T.; Kamath S․, S.Electrocardiogram (ECG) is an indicative technique using which the heartbeat time series of a patient is recorded on the moving strip of paper or line on the screen, for irregularity analysis by experts, which is a time-consuming manual process. In this paper, we proposed a deep neural network for the automatic, real-time analysis of patient ECGs for arrhythmia detection. The experiments were performed on the ECG data available in the standard dataset, MIT-BID Arrhythmia database. The ECG signals were processed by applying denoising, detecting the peaks, and applying segmentation techniques, after which extraction of temporal features was performed and fed into a deep neural network for training. Experimental evaluation on a standard dataset, using the evaluation metrics accuracy, sensitivity, and specificity revealed that the proposed approach outperformed two state-of-the-art models with an improvement of 2-7% in accuracy and 11-16% in sensitivity. © 2020 IEEE.Item Three-layer security for password protection using rdh, aes and ecc(Springer, 2021) Kumar, N.; Ghuge, S.; Jaidhar, C.D.In this work a three-layer password protection approach is proposed by utilizing Advanced Encryption Standard (AES), Elliptic Curve Cryptography (ECC) and Reversible Data Hiding (RDH). RDH is a sort of data concealing approach whereby the host image can be recuperated precisely. The proposed approach was implemented and evaluated by considering various images. Results have been presented by calculating Peak Signal to Noise Ratio (PSNR) and Rate. Obtained experimental results demonstrate the effectiveness of the proposed approach. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021.