Copyright © 2025 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{148446,
        author = {Rajeev B N},
        title = {Reconstruction of Texts by Keyboard Acoustic Emanations},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {6},
        number = {2},
        pages = {60-63},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=148446},
        abstract = {Any breach of privacy and security in a digital medium is a serious issue. Keyboard acoustic emanation one of many side channel attack. The sound from keystroke of physical keys input can be reconstructed to extract information without the awareness of the user from a system. In this paper such keyboard acoustic emanations achieved by the process of record sample, filter sample, peak detection and classification for basic keystroke recognition. Cluster keystrokes provide the initial guess of sequence, both language model and supervised classifier work repeatedly classify, spellcheck over the result then retrieve classifier with corrected labels. The improved method increases the accuracy of text recovery of supervised data. The acoustic data of keystrokes properties and recording limiting factors are explored.},
        keywords = {Keyboard Acoustic Emanations, Keystroke Extraction, Feature Extraction, Cluster Keystrokes, Supervised Classifier.
 
},
        month = {},
        }