Identification of source mobile hand sets using audio latency feature

Goyal, Akshita; Shukla, Sudhir Kumar; Sarin, Rakesh K.

doi:10.1016/j.forsciint.2019.02.031

Cited by 9 publications

(6 citation statements)

References 2 publications

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“…However, for any alterations other than a modification of the beginning of an audio, it is impossible to detect the position of manipulation by existing methods. That is, the conventional method mentioned above in [3][4][5][6] can only determine whether the questioned audio recordings were manipulated and cannot identify the positions of any manipulations in the audio recordings.…”

Section: Most Researchers Have Been Interested In Authentication Tech...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…Figure 1 summarizes the research trends on forensic audio authentication. In the past, many studies have proposed methods for the analysis of the forensic integrity of digital audio evidence [3–6]. Most researchers have been interested in authentication techniques to detect the forgery of audio recordings against manipulation, and such authentication methods consist of file structure comparison, acoustic analysis, and audio latency features without device examination.…”

Section: Introductionmentioning

confidence: 99%

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

Park

Shim

Lee

et al. 2022

Journal of Forensic Sciences

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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

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Section: Most Researchers Have Been Interested In Authentication Tech...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Park

Shim

Lee

et al. 2022

Journal of Forensic Sciences

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“…Motorola make shows negligible input audio latency time in wav and 3gp format. (10) (Refer Tables 1 and 2) • The input audio latency time lies in the range of 0:00.130ms to 0:00.140ms in case of audio recordings recorded using Samsung mobile phones in 3gp format and in wav format input audio latency value lies below 0:00.200ms. (Refer Table 1)…”

Section: Methodsmentioning

confidence: 99%

A comparative study of audio latency feature of Motorola and Samsung mobile phones in forensic identification

Goyal¹,

Shukla²,

Sarin³

2021

IJST

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Background:In forensic science the process of proving authenticity of audio recording plays an important role. In recent times, Forensic experts mostly receives digital recording for authentication as compared to analog recording. A digitally altered audio signal, leaves no visual indications of being tampered, and it will be indistinguishable from an original audio signal. Objective: To highlight the significance of latency feature of mobile phone handsets in forensic science via comparing input audio latency feature of Samsung and Motorola mobile phone in two audio formats. Methods: In this work two wellestablished and most used brands of mobile phones were considered for comparison: SAMSUNG and MOTOROLA. In the present paper, the digital audio samples have been recorded using 20 mobile phones of various models from two different makes i.e. SAMSUNG and MOTOROLA, in two audio formats i.e. WAV and 3GP. Audio samples were then analysed using Adobe Audition 3.0 software for the input audio latency feature of mobile phones and compared. Findings: Input audio latency value of digital audio recordings can be helpful in forensic identification of make and model of source mobile phone. Novelty: A new technique in digital forensics, to classify the given audio samples on the basis of input audio latency feature and identifying the make of source mobile handsets.

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“…However, the manipulation by deletion was not considered in the blind detection method of copy-move forgery. In (12), the devices constrained to the Motorola mobile handsets could be identified by measuring the audio latency time using an audio tool. Recently, forensic authentication methods (5,13,14) for audio recordings from an iPhone were proposed, which involve combining device examination and techniques based on a comparison of file structure.…”

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confidence: 99%

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

Park

Lim

Byun

et al. 2022

Journal of Forensic Sciences

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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.

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Identification of source mobile hand sets using audio latency feature

Cited by 9 publications

References 2 publications

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

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

A comparative study of audio latency feature of Motorola and Samsung mobile phones in forensic identification

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

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