Location
Grand Wailea, Hawaii
Event Website
https://hicss.hawaii.edu/
Start Date
7-1-2020 12:00 AM
End Date
10-1-2020 12:00 AM
Description
Wearable devices and Internet of Things (IoT) devices have marked the beginning of a new era in forensic science. Data from smart home gadgets and wearable devices can serve as an important "witness" in civil as well as criminal cases. Thus data extracted from these devices has started to impact and transform litigation. Data collected from wearable devices can help determine truths in witness testimony since these devices document several types of activities of an individual at all times. Increased use of smart home devices also opens a new window for investigators. The collective data extracted from wearables and smart home devices can help investigators view the detailed events that have happened in an environment in a larger context, and give them better perspectives in the case under investigation. Our work aims to provide a solution to the challenges faced by the investigators in both extracting and analyzing the sheer volume of extracted data, and illustrates techniques to automatically highlight anomalies and correlations in the time series data collected from these devices.
Data Extraction and Forensic Analysis for Smartphone Paired Wearables and IoT Devices
Grand Wailea, Hawaii
Wearable devices and Internet of Things (IoT) devices have marked the beginning of a new era in forensic science. Data from smart home gadgets and wearable devices can serve as an important "witness" in civil as well as criminal cases. Thus data extracted from these devices has started to impact and transform litigation. Data collected from wearable devices can help determine truths in witness testimony since these devices document several types of activities of an individual at all times. Increased use of smart home devices also opens a new window for investigators. The collective data extracted from wearables and smart home devices can help investigators view the detailed events that have happened in an environment in a larger context, and give them better perspectives in the case under investigation. Our work aims to provide a solution to the challenges faced by the investigators in both extracting and analyzing the sheer volume of extracted data, and illustrates techniques to automatically highlight anomalies and correlations in the time series data collected from these devices.
https://aisel.aisnet.org/hicss-53/da/iot/4