6,100 research outputs found

    Physical Multi-Layer Phantoms for Intra-Body Communications

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    This paper presents approaches to creating tissue mimicking materials that can be used as phantoms for evaluating the performance of Body Area Networks (BAN). The main goal of the paper is to describe a methodology to create a repeatable experimental BAN platform that can be customized depending on the BAN scenario under test. Comparisons between different material compositions and percentages are shown, along with the resulting electrical properties of each mixture over the frequency range of interest for intra-body communications; 100 KHz to 100 MHz. Test results on a composite multi-layer sample are presented confirming the efficacy of the proposed methodology. To date, this is the first paper that provides guidance on how to decide on concentration levels of ingredients, depending on the exact frequency range of operation, and the desired matched electrical characteristics (conductivity vs. permittivity), to create multi-layer phantoms for intra-body communication applications

    A Periodic Transmission Line Model for Body Channel Communication

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    Body channel communication (BCC) is a technique for data transmission exploiting the human body as communication channel. Even though it was pioneered about 25 years ago, the identification of a good electrical model behind its functioning is still an open research question. The proposed distributed model can then serve as a supporting tool for the design, allowing to enhance the performances of any BCC system. A novel finite periodic transmission line model was developed to describe the human body as transmission medium. According to this model, for the first time, the parasitic capacitance between the transmitter and the receiver is assumed to depend on their distance. The parameters related to the body and electrodes are acquired experimentally by fitting the bio-impedentiometric measurements, in the range of frequencies from 1 kHz to 1 MHz, obtaining a mean absolute error lower than 4° and 30Ω for the phase angle and impedance modulus, respectively. The proposed mathematical framework has been successfully validated by describing a ground-referred and low-complexity system called Live Wire, suitable as supporting tool for visually impaired people, and finding good agreement between the measured and the calculated data, marking a ±3% error for communication distances ranging from 20 to 150 cm. In this work we introduced a new circuital approach, for capacitive-coupling systems, based on finite periodic transmission line, capable to describe and model BCC systems allowing to optimize the performances of similar systems

    A Periodic Transmission Line Model for Body Channel Communication

    Get PDF
    Body channel communication (BCC) is a technique for data transmission exploiting the human body as communication channel. Even though it was pioneered about 25 years ago, the identification of a good electrical model behind its functioning is still an open research question. The proposed distributed model can then serve as a supporting tool for the design, allowing to enhance the performances of any BCC system. A novel finite periodic transmission line model was developed to describe the human body as transmission medium. According to this model, for the first time, the parasitic capacitance between the transmitter and the receiver is assumed to depend on their distance. The parameters related to the body and electrodes are acquired experimentally by fitting the bio-impedentiometric measurements, in the range of frequencies from 1 kHz to 1 MHz, obtaining a mean absolute error lower than 4° and 30 OmegaOmega for the phase angle and impedance modulus, respectively. The proposed mathematical framework has been successfully validated by describing a ground-referred and low-complexity system called Live Wire, suitable as supporting tool for visually impaired people, and finding good agreement between the measured and the calculated data, marking a ±3% error for communication distances ranging from 20 to 150 cm. In this work we introduced a new circuital approach, for capacitive-coupling systems, based on finite periodic transmission line, capable to describe and model BCC systems allowing to optimize the performances of similar systems

    Mobile forensic triage for damaged phones using M_Triage

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    Mobile forensics triage is a useful technique in a digital forensics investigation for recovering lost or purposely deleted and hidden files from digital storage. It is particularly useful, especially when solving a very sensitive crime, for example, kidnapping, in a timely manner. However, the existing mobile forensics triage tools do not consider performing a triage examination on damaged mobile phones. This research addressed the issues of performing triage examination on damaged Android mobile phones and reduction of false positive result generated by the current mobile forensics triage tools. Furthermore, the research addressed the issues of ignoring possible evidence residing in a bad block memory location. In this research a new forensics triage tool called M_Triage was introduced by extending Decode’s framework to handle data retrieval challenges on damaged Android mobile phones. The tool was designed to obtain evidence quickly and accurately (i.e. valid address book, call logs, SMS, images, and, videos, etc.) on Android damaged mobile phones. The tool was developed using C#, while back end engines was done using C programming and tested using five data sets. Based on the computational time processing comparison with Dec0de, Lifter, XRY and Xaver, the result showed that there was 75% improvement over Dec0de, 36% over Lifter, 28% over XRY and finally 71% over Xaver. Again, based on the experiment done on five data sets, M_Triage was capable of carving valid address book, call logs, SMS, images and videos as compared to Dec0de, Lifter, XRY and Xaver. With the average improvement of 90% over DEC0DE, 30% over Lifter, 40% over XRY and lastly 61% over Xaver. This shows that M_Triage is a better tool to be used because it saves time, carve more relevant files and less false positive result are achieved with the tool

    Mobile forensic triage for damaged phones using M_Triage

    Get PDF
    Mobile forensics triage is a useful technique in a digital forensics investigation for recovering lost or purposely deleted and hidden files from digital storage. It is particularly useful, especially when solving a very sensitive crime, for example, kidnapping, in a timely manner. However, the existing mobile forensics triage tools do not consider performing a triage examination on damaged mobile phones. This research addressed the issues of performing triage examination on damaged Android mobile phones and reduction of false positive result generated by the current mobile forensics triage tools. Furthermore, the research addressed the issues of ignoring possible evidence residing in a bad block memory location. In this research a new forensics triage tool called M_Triage was introduced by extending Decode’s framework to handle data retrieval challenges on damaged Android mobile phones. The tool was designed to obtain evidence quickly and accurately (i.e. valid address book, call logs, SMS, images, and, videos, etc.) on Android damaged mobile phones. The tool was developed using C#, while back end engines was done using C programming and tested using five data sets. Based on the computational time processing comparison with Dec0de, Lifter, XRY and Xaver, the result showed that there was 75% improvement over Dec0de, 36% over Lifter, 28% over XRY and finally 71% over Xaver. Again, based on the experiment done on five data sets, M_Triage was capable of carving valid address book, call logs, SMS, images and videos as compared to Dec0de, Lifter, XRY and Xaver. With the average improvement of 90% over DEC0DE, 30% over Lifter, 40% over XRY and lastly 61% over Xaver. This shows that M_Triage is a better tool to be used because it saves time, carve more relevant files and less false positive result are achieved with the tool
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