Unless live acquisition is performed, evidence is extracted from the seized digital devices at the forensic laboratory (i.e., static acquisition). At the forensics laboratory, digital evidence should be acquired in a manner that preserves the integrity of the evidence (i.e., ensuring that the data is unaltered); that is, in a forensically sound manner (see Cybercrime Module 4 on Introduction to Digital Forensics). To achieve this, the tools and techniques used to acquire digital evidence must prevent alterations to the data or when this is not possible, at the very least minimize them ( SWGDE Best Practices for Computer Forensic Acquisitions , 2018). The tools and techniques used should be valid and reliable (NIST, n.d.; SWGDE Recommended Guidelines for Validation Testing , 2014; US National Institute of Justice, 2007b). The limitations of these tools and techniques should be identified and considered before their use (SWGDE Best Practices for Computer Forensic Acquisitions, 2018). The US National Institute of Standards and Technology has a searchable digital forensics tools database with tools with various functionalities (e.g., cloud forensics tools, among others) (for more information on digital forensics tools, see Cybercrime Module 4 on Introduction to Digital Forensics).
In addition to the handling of digital evidence, the digital forensics process also involves the examination and interpretation of digital evidence ( analysis phase), and the communication of the findings of the analysis ( reporting phase). During the analysis phase, digital evidence is extracted from the device, data is analysed, and events are reconstructed. Before the analysis of the digital evidence, the digital forensics analyst in the laboratory must be informed of the objectives of the search, and provided with some background knowledge of the case and any other information that was obtained during the investigation that can assist the forensics analyst in this phase (e.g., IP address or MAC addresses). Various forms of analyses are performed depending on the type of digital evidence sought, such as network, file system, application, video, image, and media analysis (i.e., analysis of data on storage device) (Grance, Chevalier, Kent, and Dang, 2005; Carrier, 2005; European Network of Forensic Science Institute, 2015; SWGDE Best Practices for Image Authentication , 2018; SWGDE Best Practices for Image Content Analysis , 2017; SWGDE Guidelines for Forensic Image Analysis , 2017; SWGDE Best Practices for Data Acquisition from Digital Video Recorders , 2018; SWGDE Best Practices for Digital & Multimedia Evidence Video Acquisition from Cloud Storage , 2018). Files are analysed to determine their origin, and when and where the data was created, modified, accessed, downloaded, or uploaded, and the potential connection of these files on storage devices to, for example, remote storage, such as cloud-based storage (Carrier, 2005). The type of digital evidence (e.g., emails, text messages, geolocation, Word processing documents, images, videos, and chat logs) sought depends on the cybercrime case.
Laboratory Exercises For Electronic Devices Answer Key Zip
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Since 1979, he has been a professor with the Department of Electrical & Computer Engineering at Laval University, Quebec, Canada. He is working in the research laboratory LEEPCI. His research interests include the design & modeling of electrical machines and medium frequency magnetic components, AC drives and power electronics. He was Project Associate and consulting engineer at CERN, Geneva, Switzerland, in 2010 and 2018 respectively.
This paper presents the design and development of a wind turbine emulator (WTE), based on a separately excited DC motor, using an OPAL-RT digital simulator. The power-motor speed characteristics for different armature voltages in the motor are like the power-turbine speed characteristics for varying wind speeds in the turbine. WTE is a power electronic step-down chopper that is interfaced with a mathematical model of wind turbine present in the RT simulator. The wind turbine model generates a reference armature current that is compared with the actual armature current of the motor. The PI controller is used here to minimize the current error and provides a desired switching pulse to the MOSFET. The laboratory setup consists of a WTE that is coupled to a three-phase permanent magnet synchronous generator (PMSG) as a standalone system. The turbine model and PMSG model are presented in this paper. The effectiveness of this RT-LAB-based WTE is verified by simulation and experimental results under various wind speed and load change conditions.
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