Due to the exponential increase in cyber/online crimes involving the use of steganography in streaming media, it is crucial to focus on studying steganalysis technology for the detection of covert communications. Several existing steganalysis methods rely on classifiers such as Support Vector Machines (SVM) and conventional statistical analysis. However, these methods suffer from high computational intensity and time consumption, making them unsuitable for real-time detection of steganography in streaming media. Additionally, some steganalysis techniques are specifically designed for certain codecs or depend on particular steganographic algorithms, limiting their practicality and universality. To address these challenges, this study devises five steganalysis algorithms tailored for Voice over Internet Protocol (VoIP) to detect covert channels in streaming media communications. The algorithms are as follows: ANOVA, derivative-based Mel Frequency Cepstrum Coefficient (DMFCC), improved Regular and Singular (RS) test, Mann–Whitney–Wilcoxon (M-W-W) test, and FFT-based Steganalysis. Experimental evaluations were performed on two sets of media streams — one without steganography and the other with steganography. The results obtained from these experiments reveal that the proposed VoIP steganalysis algorithms exhibit variations in terms of detection sensitivity, whether blind or targeted, online or offline, as well as the requirement for original samples.

This paper introduces MouthIO, the first customizable intraoral user interface that can be equipped with various sensors and output components. MouthIO consists of an SLA-printed brace that houses a flexible PCB within a bite-proof enclosure positioned between the molar teeth and inner cheeks. Our MouthIO design and fabrication technique enables makers to customize the oral user interfaces in both form and function at low cost. All parts in contact with the oral cavity are made of bio-compatible materials to ensure safety, while the design takes into account both comfort and portability. We demonstrate MouthIO through three application examples ranging from beverage consumption monitoring, health monitoring, to assistive technology. Results from our full-day user study indicate high wearability and social acceptance levels, while our technical evaluation demonstrates the device’s ability to withstand adult bite forces.

Recent studies have shown that adding sonification to stroke rehabilitation training is effective. It helps patients achieve better training results by positively affecting motor control, the somatosensory system, and patient engagement. This paper explores the concept of audio-based games in stroke rehabilitation, hypothesizing that the removal of a visual dimension might increase patient focus on the body part being trained. In an expert study with nine therapists we evaluated Serenity, an audio-based rehabilitation game, as a design probe to explore the potential of audio-based games in rehabilitation training. Results show promise for further exploring the concept of audio-based gaming in stroke rehabilitation.

Voice over IP (VoIP) is finding its way into several applications, but its security concerns still remain. This paper shows how a new self-adaptive steganographic method can ensure the security of covert VoIP communications over the Internet. In this study an Active Voice Period Detection algorithm is devised for PCM codec to detect whether a VoIP packet carries active or inactive voice data, and the data embedding location in a VoIP stream is chosen randomly according to random sequences generated from a logistic chaotic map. The initial parameters of the chaotic map and the selection of where to embed the message are negotiated between the communicating parties. Steganography experiments on active and inactive voice periods were carried out using a VoIP communications system. Performance evaluation and security analysis indicates that the proposed VoIP steganographic scheme can withstand statistical detection, and achieve secure real-time covert communications with high speech quality and negligible signal distortion.

The last few years have witnessed an explosive growth in the research of information hiding in multimedia objects, but few studies have taken into account packet loss in multimedia networks. As one of the most popular real-time services in the Internet, Voice over Internet Protocol (VoIP) contributes to a large part of network traffic for its advantages of real time, high flow, and low cost. So packet loss is inevitable in multimedia networks and affects the performance of VoIP communications. In this study, a fractal-based VoIP steganographic approach was proposed to realize covert VoIP communications in the presence of packet loss. In the proposed scheme, secret data to be hidden were divided into blocks after being encrypted with the block cipher, and each block of the secret data was then embedded into VoIP streaming packets. The VoIP packets went through a packet-loss system based on Gilbert model which simulates a real network situation. And a prediction model based on fractal interpolation was built to decide whether a VoIP packet was suitable for data hiding. The experimental results indicated that the speech quality degradation increased with the escalating packet-loss level. The average variance of speech quality metrics (PESQ score) between the “no-embedding” speech samples and the “with-embedding” stego-speech samples was about 0.717, and the variances narrowed with the increasing packet-loss level. Both the average PESQ scores and the SNR values of stego-speech samples and the data-retrieving rates had almost the same varying trends when the packet-loss level increased, indicating that the success rate of the fractal prediction model played an important role in the performance of covert VoIP communications.