scholarly journals Data Mining Technique to Data Collection and Analysis for Cyber Forensic

2020 ◽  
Vol 8 (5) ◽  
pp. 2786-2789
Keyword(s):  
Law Enforcement ◽  
Data Collection ◽  
Crime Scene ◽  
Forensic Analysis ◽  
Digital Data ◽  
Data Mining Technique ◽  
Faulty Node ◽  
Digital Forensic ◽  
Data Collection And Analysis ◽  
Data Investigation

In the world of Digital forensic the uncovered digital may contain vital information for digital data investigation for investigator. Digital data collected from the crime scene leads to find out the clue after performing analysis by the examiner. This process of data examination data collection and analysis plays important role in cyber world for the forensic investigator. The cybercrime is a part of computer forensics where the digital evidences are analyze by the investigator and to perform analysis special measurements and techniques are required in order to use this details that has to be accepted in court of law for law enforcement. The data collection of evidence is a key aspect for the investigator, such kind of digital data has to be collected from different sources at the crime scene and this process involves to collect each and every evidence of digital crime scene and later this gather data will be analyze by the experts to reach to the conclusion. In this paper the proposed method collected the data from the crime scene efficiently which includes log data, transactional data, physical drive data, and network data; later this collected data analyzed to find out the theft node in the network. In this paper FTK 4.0 digital forensic tool used to reduce plenty of time for data processing and later report will be produce that will be accepted tin the court of law. This paper also focuses the data collection method with in the network and reach to the faulty node and later this faulty node analyzed with all collected data for forensic analysis. For this standard algorithm used to analyze the performance of distinct features used for network attacks. Kmeans clustering methodology is used to create cluster of victim node and represent victim data in systematic manner for the ease of law enforcement.

Digital Data Collection and Analysis

2004 ◽  
Vol 35 (2) ◽  
pp. 112-121 ◽  
Author(s):  
Kelly Ingram ◽  
Ferenc Bunta ◽  
David Ingram
Keyword(s):  
Data Collection ◽  
Language Disorders ◽  
Speech Analysis ◽  
Digital Data ◽  
Digital Recording ◽  
Analog To Digital ◽  
Data Collection And Analysis ◽  
Audio Files ◽  
Speech And Language Disorders ◽  
Sound Files

Technology for digital speech recording and speech analysis is now readily available for all clinicians who use a computer. This article discusses some advantages of moving from analog to digital recordings and outlines basic recording procedures. The purpose of this article is to familiarize speech-language pathologists with computerized audio files and the benefits of working with those sound files as opposed to using analog recordings. This article addresses transcription issues and offers practical examples of various functions, such as playback, editing sound files, using waveform displays, and extracting utterances. An appendix is provided that describes step-by-step how digital recording can be done. It also provides some editing examples and a list of useful computer programs for audio editing and speech analyses. In addition, this article includes suggestions for clinical uses in both the assessment and the treatment of various speech and language disorders.

scholarly journals Drone Forensics

2021 ◽  
Vol 13 (1) ◽  
pp. 1-25
Author(s):  
Khalifa Al-Room ◽  
Farkhund Iqbal ◽  
Thar Baker ◽  
Babar Shah ◽  
Benjamin Yankson ◽  
...  
Keyword(s):  
Law Enforcement ◽  
Unmanned Aerial Vehicles ◽  
Methodological Approach ◽  
Forensic Analysis ◽  
High Quality ◽  
Significant Information ◽  
Daily Lives ◽  
Digital Forensic ◽  
Aerial View ◽  
Technological Paradigms

Drones (a.k.a. unmanned aerial vehicles – UAV) have become a societal norm in our daily lives. The ability of drones capture high-quality photos from an aerial view and store and transmit such data presents a multi-facet problem. These actions possess privacy challenges to innocent users who can be spied on or drone owner's data which may be intercepted by a hacker. With all technological paradigms, utilities can be misused, and this is an increasing occurrence with drones. As a result, it is imperative to develop a novel methodological approach for the digital forensic analysis of a seized drone. This paper investigates six brands of drones commonly used in criminal activities and extracts forensically relevant data such as location information, captured images and videos, drones' flight paths, and data related to the ownership of the confiscated drone. The experimental results indicate that drone forensics would facilitate law enforcement in collecting significant information necessary for criminal investigations.

scholarly journals Collective Imagining: The Early Genesis and Development of a sense of Collectiveness during Infancy

2021 ◽  
Vol 17 (3) ◽  
pp. 84-93
Author(s):  
G. Fragkiadaki ◽  
M. Fleer ◽  
P. Rai
Keyword(s):  
Data Collection ◽  
Formal Education ◽  
Digital Data ◽  
Visual Methods ◽  
Abstract Space ◽  
Important Concept ◽  
Collective Orientation ◽  
Data Collection And Analysis ◽  
Model Of Practice ◽  
Opening Up

On entering formal education, infants face the demand of participating in collective educational rou¬tines and learning experiences. However, in this age period, the sense of collectiveness is still in an embry¬onic form. This study explored how infants enter into and experience the need for collectiveness and how teachers create the conditions for the development of a sense of collectiveness during infancy. Our educa¬tional experiment drew on a Conceptual PlayWorld, as a collective model of practice for the development of play and imagination. Thirteen infants (0,5—2 years old) participated in the study. Visual methods were used for digital data collection and analysis. It was found that, being in the imaginary situation as play part¬ners, teachers introduced to the infants’ environment the demand to align with the collective, consistently facilitated and sustained infants’ motive orientation to the collective. The use of props, the embodiment of the experience and the shift from physical objects and concrete spaces to a shared intellectual and abstract space appeared to be critical. The findings inform everyday practice and policy opening up a new area of understanding about the concept of collective imagining, as an important concept for the development of a collective orientation for infants.

Development of a DNP measurement grid to increase the rigor of doctor of nursing practice students' data collection and analysis methods

2020 ◽  
Vol 36 (6) ◽  
pp. 666-672
Author(s):  
Linda L. Costa ◽  
Debra Bingham ◽  
Carla L. Storr ◽  
Margaret Hammersla ◽  
Jeffrey Martin ◽  
...  
Keyword(s):  
Data Collection ◽  
Nursing Practice ◽  
Doctor Of Nursing Practice ◽  
Analysis Methods ◽  
Data Collection And Analysis

scholarly journals Forensic analysis of beverage stains using hyperspectral imaging

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Binu Melit Devassy ◽  
Sony George
Keyword(s):  
Hyperspectral Imaging ◽  
Crime Scene ◽  
Forensic Analysis ◽  
Classification Model ◽  
Support Vector ◽  
Additional Information ◽  
Non Invasive ◽  
Spectral Bands ◽  
Data Dimensionality Reduction ◽  
Gradient Based

AbstractDocumentation and analysis of crime scene evidences are of great importance in any forensic investigation. In this paper, we present the potential of hyperspectral imaging (HSI) to detect and analyze the beverage stains on a paper towel. To detect the presence and predict the age of the commonly used drinks in a crime scene, we leveraged the additional information present in the HSI data. We used 12 different beverages and four types of paper hand towel to create the sample stains in the current study. A support vector machine (SVM) is used to achieve the classification, and a convolutional auto-encoder is used to achieve HSI data dimensionality reduction, which helps in easy perception, process, and visualization of the data. The SVM classification model was re-established for a lighter and quicker classification model on the basis of the reduced dimension. We employed volume-gradient-based band selection for the identification of relevant spectral bands in the HSI data. Spectral data recorded at different time intervals up to 72 h is analyzed to trace the spectral changes. The results show the efficacy of the HSI techniques for rapid, non-contact, and non-invasive analysis of beverage stains.

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