Audio Forensics on Smartphone with Digital Forensics Research Workshop (DFRWS) Method

Audio is one of the digital items that can reveal a happened case. However, audio evidence can also be manipulated and changed to hide information. Forensics audio is a technique to identify the sound’s owner from the audio using pitch, formant, and spectrogram parameters. The conducted research examines the similarity of the original sound with the manipulated voice to determine the owner of the sound. It analyzes the level of similarity or identical sound using spectrogram analysis with the Digital Forensics Research Workshop (DFRWS) Method. The research objects are original and manipulated files. Both files are in mp3 format, which is encoded to WAV format. Then, the live forensics method is used by picking up the data on a smartphone. Several applications are also used. The results show that the research successfully gets digital evidence on a smartphone with the Oxygen Forensic application. It extracts digital evidence in the form of two audio files and two video files. Then, by the hashing process, the four obtained files are proven to be authentic. Around 90% of the data are identical to the original voice recording. Only 10% of the data are not identical.

Kinematic dataset of actors expressing emotions

Human body movements can convey a variety of emotions and even create advantages in some special life situations. However, how emotion is encoded in body movements has remained unclear. One reason is that there is a lack of public human body kinematic dataset regarding the expressing of various emotions. Therefore, we aimed to produce a comprehensive dataset to assist in recognizing cues from all parts of the body that indicate six basic emotions (happiness, sadness, anger, fear, disgust, surprise) and neutral expression. The present dataset was created using a portable wireless motion capture system. Twenty-two semi-professional actors (half male) completed performances according to the standardized guidance and preferred daily events. A total of 1402 recordings at 125 Hz were collected, consisting of the position and rotation data of 72 anatomical nodes. To our knowledge, this is now the largest emotional kinematic dataset of the human body. We hope this dataset will contribute to multiple fields of research and practice, including social neuroscience, psychiatry, computer vision, and biometric and information forensics.

Medical Information Forensics System Based on Convolutional Neural Network with Pattern Finding Prior

Hospital Information System HIS is an indispensable technical support environment and infrastructure for modern hospitals. It reflects the comprehensive management of a modern hospital. Many hospitals have established local networks and implemented some subsystems, such as inpatient toll collection systems and drug management systems, which have yielded some success. Medical information forensics is a comprehensive process of using scientific methods to collect network data, identify intrusion, analyze data, store data, determine the reason of intrusion tp enhance security equipment and trigger alarm procedures. In this paper, we study the concepts and techniques of medical information forensics, and discuss the definition, classification, sources and characteristics of medical information forensics. The deep learning model and the data analytic framework are combined to provide the comprehensive analysis of the research. The technique novelty is validated through the experiment. The simulation compared with the other state-of-the-art methodologies proves the efficiency of the method.