Forensic integrity verification of video recordings based on MTS files.

Digital video is used in criminal trials as evidence with legal responsibility because video content vividly depicts events occurring at a crime scene. However, using sophisticated video editing software, assailants can easily manipulate visible clues for their own benefit. Therefore, the integrity of digital video files acquired or submitted as evidence must be ensured. Forensic analysis of digital video is key to ensuring the integrity of links with individual cameras. In this study, we analyzed whether it is possible to ensure the integrity of MTS video files. Herein, we propose a method to verify the integrity of MTS files encoded by advanced video coding high definition (AVCHD), which is frequently used for video recording. To verify MTS file integrity, we propose five features. Codec information, picture timing, and camera manufacture/model are modified AVI and MP4-like format video verification features. Group of pictures and Universally Unique Identifier patterns were specifically developed for MTS streams. We analyzed the features of 44 standard files recorded using all recording options of seven cameras. We checked whether integrity can be validated on unmanipulated videos recorded in various environments. In addition, we considered whether manipulated MTS files edited in video editing software could be validated. Experimental results show that all unmanipulated and manipulated MTS files with known recording devices were discriminated only when all five features were checked. These results show that the proposed method verifies the integrity of MTS files, strengthening the validity of MTS file-based evidence in trials.

Forensic authentication method for audio recordings generated by Voice Recorder application on Samsung Galaxy Watch4 series.

The number of smartwatch users has been rapidly increasing in recent years. A smartwatch is a wearable device that collects various types of data using sensors and provides basic functions, such as healthcare-related measurements and audio recording. In this study, we proposed the forensic authentication method for audio recordings from the Voice Recording application in the Samsung Galaxy Watch4 series. First, a total of 240 audio recordings from each of the four different models, paired with four different smartphones for synchronization via Bluetooth, were collected and verified. To analyze the characteristics of smartwatch audio recordings, we examined the transition of the audio latency, writable audio bandwidth, timestamps, and file structure between those generated in the smartwatches and those edited using the Voice Recording application of the paired smartphones. In addition, the devices with the audio recordings were examined via the Android Debug Bridge (ADB) tool and compared with the timestamps stored in the file system. The experimental results showed that the audio latency, writable audio bandwidth, and file structure of audio recordings generated by smartwatches differed from those generated by smartphones. Additionally, by analyzing the file structure, audio recordings can be classified as unmanipulated, manipulation has been attempted, or manipulated. Finally, we can forensically authenticate the audio recordings generated by the Voice Recorder application in the Samsung Galaxy Watch4 series by accessing the smartwatches and analyzing the timestamps related to the audio recordings in the file system.

Advanced forensic procedure for the authentication of audio recordings generated by Voice Memos application of iOS14.

In this study, we propose an advanced forensic examination procedure for audio recordings generated by the Voice Memos application with iPhone Operation System (iOS)14, to verify that these are the original recordings and have not been manipulated. The proposed examination procedure consists of an analysis of the characteristics of audio recordings and of the file system of the device storing the audio recordings. To analyze the characteristics of audio recordings, we compare the encoding parameters (bitrate, sampling rate, timestamps, etc.) and the file structure to determine whether audio recordings were manipulated. Next, in the device examination step, we analyze the media-log history and temporary files of the file system obtained by mobile forensic tools. For comparative analysis, a total of 100 audio recording samples were obtained through the Voice Memos application from five iPhone mobile handsets of different models with iOS14 installed using Advanced audio coding (AAC) or Apple lossless audio codec (ALAC). As a result of analyzing the encoding parameters between the original and manipulated audio recordings, as well as the temporary files contained in the device file system, the difference in the encoding parameters and the very unique trace of the original audio recordings in the temporary files were confirmed when manipulating the audio recordings. In particular, the primary advantage of our proposed method is its potential ability to recover original audio recordings that were subsequently manipulated via the temporary files examined in the device file system analysis.

A method of forensic authentication of audio recordings generated using the Voice Memos application in the iPhone.

Considering the widespread use of mobile phones, audio recordings of crime scenes are widely used as digital evidence; however, it is important to authenticate the audio recordings before consideration as legal evidence. This study aimed to develop a method to authenticate audio recordings generated using the iPhone through three steps: 1) bitrate/audio latency time analysis of audio recordings, 2) comparison of the file structure/timestamp on audio recordings, and 3) device-based log history examinations for the provenance of audio recordings. Herein, we analyzed audio recording samples from ten different models of mobile handsets of the iPhone with Advanced Audio Coding (AAC) or Apple Lossless Audio Codec (ALAC), through the Voice Memos application depending on the iPhone Operating System (iOS). To analyze the characteristics of these audio recordings, we compared features including audio latency, file format/structure, and timestamps between the audio recordings generated in the iPhone and those edited through the built-in audio editing function. Furthermore, we investigated the log history registered in devices during the generation of the audio recordings. Differences in the audio latency, file size, timestamps, bitrate, and log history were confirmed on the iPhone when manipulating the audio recordings. The present results show that it is possible to verify the authentication of audio recordings generated using the Voice Memos application on iPhone.

Monitoring of the Binding Between EGFR Protein and EGFR Aptamer Using In-Situ Total Internal Reflection Ellipsometry.

The epidermal growth factor receptor (EGFR) protein has received significant attention in medical biotechnology because it is an important component in cell growth and division. We report the results of a study on the binding between the EGFR protein and the associated aptamer, measured in real time. Aptamers can be used for clinical purposes including macromolecular medicine and basic research. In particular, EGFR aptamers are promising molecular agents for targeting cancer. The data were obtained in-situ with total internal reflection ellipsometry (TIRE), which combines the analytic capability of spectroscopic ellipsometry with the high surface sensitivity of surface plasmon resonance measurements. Our results show that TIRE can be used to determine adsorption of nanoscale biomolecules. Our results are supported by additional data obtained by liquid atomic-force-microscopy.