Digital audio steganography: Systematic review, classification, and analysis of the current state of the art

Audio signal processing is the most challenging field in the current era for an analysis of an audio signal. Audio signal classification (ASC) comprises of generating appropriate features from a sound and utilizing these features to distinguish the class the sound is most likely to fit. Based on the application’s classification domain, the characteristics extraction and classification/clustering algorithms used may be quite diverse. The paper provides the survey of the state-of art for understanding ASC’s general research scope, including different types of audio; representation of audio like acoustic, spectrogram; audio feature extraction techniques like physical, perceptual, static, dynamic; audio pattern matching approaches like pattern matching, acoustic phonetic, artificial intelligence; classification, and clustering techniques. The aim of this state-of-art paper is to produce a summary and guidelines for using the broadly used methods, to identify the challenges as well as future research directions of acoustic signal processing.

Pattern analysis based acoustic signal processing: a survey of the state-of-art

Recently, a remote-sensing platform based on wireless interconnection of tiny ECG sensors called telecardiology sensor networks (TSN) provided a promising approach to perform low-cost real-time cardiac patient monitoring at any time in community areas (such as elder nursing homes or hospitals). The contribution of this research is the design of a practical TSN hardware/software platform for a typical U.S. healthcare community scenario (such as large nursing homes with many elder patients) to perform real-time healthcare data collections. On the other hand, due to the radio broadcasting nature of MANET, a TSN has the risk of losing the privacy of patients' data. Medical privacy has been highly emphasized by U.S. Department of Health and Human Services. This research also designs a medical security scheme with low communication overhead to achieve confidential electrocardiogram data transmission in wireless medium.

Privacy preserving telecardiology sensor networks: towards a low-cost portable wireless hardware/software co-design

The following paper represents a survey of steganography techniques suitable for usage in ECG. A few steganographic methods have been discussed below, it has been believed that these methods can be exploited to bring out more techniques suitable for ECG. The objective of this paper is to provide a comprehensive survey of existing steganographic techniques for ECG.

A Brief Survey of Steganographic Methods for ECG Signal

Point of care testing (POCT) in patients with ischemic heart disease is impelled by the time critical need for quick, specific and accurate results for initiation of therapy instantly. The driving force behind POCT using ECG signals is to provide test immediately and conveniently to cardiac patients. This will intensify the probability of patient, physician and care team receiving the results faster, which facilitate immediate clinical management decisions to be taken. In wireless communication the biomedical data may be susceptible to potential attacks leading to following security challenges. ● To safeguard the privacy and integrity of biomedical data. ● To make sure that only authorized people can have the access to secret information. This paper proposes a five level wavelet decomposition based steganography technique applied to ECG signals along with RSA encryption and scrambling matrix based encoding technique to protect confidential information related to patient hidden inside ECG signals. To assess the efficiency of the proposed algorithm on the patient ECG signal, the two distortion measurement metrics like percentage RMSE difference (PRD) and PSNR(peak signal to noise ratio) have been compared with existing algorithm results and energy of watermarked ECG signal is compared with original ECG for Coiflet, Bioorthogonal and symlet wavelets. It is found that the proposed algorithm provides very high security protection for information related to patient and as well as with very less distortion of ECG signal, so that it remains diagnosable even after retrieval of patient related secret information.

Novel Audio Steganography Technique for ECG Signals in Point of Care Systems (NASTPOCS)

: In the course of our daily lives, we are witness to a significant amount of dishonesty and theft that goes unreported. The automated teller machine is the scene of most major crimes. The purpose of this research is to present a new supervised method that can detect odd occurrences in restricted spaces such as ATM rooms, server rooms, and other such places. One of the technologies that are used to make up the technical base is abnormal behaviour detection using image processing. The purpose of the work that is being proposed is to establish a technical base that will support a social infrastructure that is both more secure and more convenient for its users. The robbery will be prevented as a result of this, and the perpetrator of the robbery will be easier to find. The use of this method will result in an end to robberies as well as a significant decrease in the number of complaints received. Because of this, the results of the suggested framework indicate that the framework is capable of delivering a high level of security to the ATM System's.

Anitha Devi

Papers

Novel Audio Steganography Technique for ECG Signals in Point of Care Systems (NASTPOCS)

Identification And Detection of Abnormal Activity in Atms Using Deep Learning