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Audio Data Security and Feature Extraction over Cloud

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Sayyada Fahmeeda, Amreen Tabassum

Sayyada Fahmeeda and Amreen Tabassum. Audio Data Security and Feature Extraction over Cloud. International Journal of Computer Applications 168(10):33-37, June 2017. BibTeX

	author = {Sayyada Fahmeeda and Amreen Tabassum},
	title = {Audio Data Security and Feature Extraction over Cloud},
	journal = {International Journal of Computer Applications},
	issue_date = {June 2017},
	volume = {168},
	number = {10},
	month = {Jun},
	year = {2017},
	issn = {0975-8887},
	pages = {33-37},
	numpages = {5},
	url = {},
	doi = {10.5120/ijca2017914518},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


The demand for on-demand services of multimedia; most individuals, companies, and governments use cloud services to maintain confidentiality from intruder from being hacked as every day huge data was embedded in a digital media or distributed over the internet. For this reason, the user require to secure their data and encryption method is the one that provides security to your information and most security system uses this technique which is widely used in the database areas such as internet banking, audio communication channel, phone recordings, music companies, military conversations etc. A Cryptographic encryption method is certainly the best option for maintaining the security to our audio files. As the audio is encrypted it does not make sense to recognize the audio for that reason audio feature extraction method is used for classification purpose. Audio classification involves extracting representative features and feeding them into the classifier. The proposed method provides security to audio files using spread spectrum technique and LSB steganography for easy search of these files by extracting audio features using K-NN classifier.


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Cryptography, Steganography, Feature Extraction, Audio Classification, Cloud Security.