Data Encryption using Morse Code
Publisher: CGC International Journal of Contemporary Technology and Research
DOI: 10.46860/cgcijctr.2022.07.31.319
Author: Aditya Pathak, Anmol Chahal, Sagar
Author: Cryptography is a method of hiding or protecting data from unauthorized access. With the rise of internet usage, data security is a major concern due to cyber-attacks and over-reliance on the internet. Cryptographic algorithms are used to ensure data is accessible only to the intended user. Morse code, a method of encryption, can be used to encrypt data but may pose a threat to user data. Python's Cryptography module, which uses symmetric encryption, is used to encrypt both the algorithm and data files. This paper demonstrates how Morse code, time, and Python's Cryptography module can be combined to provide maximum data safety. safety.
Privacy Enhancement in Internet of Things (IoT) via mRMR for prevention and avoidance of data leakage
Publisher: Computers and Electrical Engineering
DOI: 10.1016/j.compeleceng.2024.109151
Author: Aditya Pathak, Parveen Singla, Hitendra Garg, Gagandeep, Simar Preet Singh
Author: In today's world, data leakage on computer systems, Internet of Things (IoT) devices, or mobile devices carries a significant threat due to weaker encryption or communication techniques, resulting in the loss of data items. Identifying the leakage of sensitive data during data transmission requires an appropriate technique. In the IoT environment, default permissions granted to devices often lead to data leakage. This proposed method offers data leakage security based on data sensitivity. However, classifying sensitive data is challenging due to its large volume and data transformation. The proposed technique utilizes the minimum redundancy and maximum relevancy (mRMR) technique for feature selection. It accurately detects confidential data better than existing state-of-the-art methods and can identify rephrased confidential contents using filter-based features for sequential data leak deterrence. Specifically, data leakage measurement can be achieved using DBSCAN (Density-based Spatial Clustering of Applications with Noise) to average F-statistical values measured over individual time steps and to ensure continuity between leakage data points.