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 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.

scholarly journals A Dataset of Photos and Videos for Digital Forensics Analysis Using Machine Learning Processing

Data ◽  
2021 ◽  
Vol 6 (8) ◽  
pp. 87
Author(s):  
Sara Ferreira ◽  
Mário Antunes ◽  
Manuel E. Correia
Keyword(s):  
Machine Learning ◽  
Digital Forensics ◽  
State Of The Art ◽  
Forensic Analysis ◽  
Third Party ◽  
Support Vector ◽  
Multimedia Content ◽  
Digital Forensic ◽  
Video Frames ◽  
Forensic Tools

Deepfake and manipulated digital photos and videos are being increasingly used in a myriad of cybercrimes. Ransomware, the dissemination of fake news, and digital kidnapping-related crimes are the most recurrent, in which tampered multimedia content has been the primordial disseminating vehicle. Digital forensic analysis tools are being widely used by criminal investigations to automate the identification of digital evidence in seized electronic equipment. The number of files to be processed and the complexity of the crimes under analysis have highlighted the need to employ efficient digital forensics techniques grounded on state-of-the-art technologies. Machine Learning (ML) researchers have been challenged to apply techniques and methods to improve the automatic detection of manipulated multimedia content. However, the implementation of such methods have not yet been massively incorporated into digital forensic tools, mostly due to the lack of realistic and well-structured datasets of photos and videos. The diversity and richness of the datasets are crucial to benchmark the ML models and to evaluate their appropriateness to be applied in real-world digital forensics applications. An example is the development of third-party modules for the widely used Autopsy digital forensic application. This paper presents a dataset obtained by extracting a set of simple features from genuine and manipulated photos and videos, which are part of state-of-the-art existing datasets. The resulting dataset is balanced, and each entry comprises a label and a vector of numeric values corresponding to the features extracted through a Discrete Fourier Transform (DFT). The dataset is available in a GitHub repository, and the total amount of photos and video frames is 40,588 and 12,400, respectively. The dataset was validated and benchmarked with deep learning Convolutional Neural Networks (CNN) and Support Vector Machines (SVM) methods; however, a plethora of other existing ones can be applied. Generically, the results show a better F1-score for CNN when comparing with SVM, both for photos and videos processing. CNN achieved an F1-score of 0.9968 and 0.8415 for photos and videos, respectively. Regarding SVM, the results obtained with 5-fold cross-validation are 0.9953 and 0.7955, respectively, for photos and videos processing. A set of methods written in Python is available for the researchers, namely to preprocess and extract the features from the original photos and videos files and to build the training and testing sets. Additional methods are also available to convert the original PKL files into CSV and TXT, which gives more flexibility for the ML researchers to use the dataset on existing ML frameworks and tools.

LEGAL AND ORGANIZATIONAL PROBLEMS OF CONDUCTING COMPREHENSIVE COMMISSION INSPECTIONS OF PENAL FACILITIES ON THE SUBJECT OF ANTI-TERRORIST SECURITY STATE ASSESSMENT OF PENAL OBJECTS (TERRITORIES)

2021 ◽  
pp. 128-133
Author(s):  
Олег Игоревич Денисенко ◽  
Оганнес Давитович Мкртчян
Keyword(s):  
Law Enforcement ◽  
Russian Federation ◽  
State Assessment ◽  
The State ◽  
Organizational Level ◽  
Penal System ◽  
High Quality ◽  
The Subject ◽  
The Russian Federation ◽  
Qualitative Characteristics

В связи с увеличением числа преступлений террористической направленности разрешения требуют вопросы, связанные с обеспечением объектов (территорий) УИС инструментами антитеррористической защищенности, к которым можно отнести такие, как проведение организационно-практических мероприятий антитеррористической защиты объектов УИС, наличие соответствующей документации и ответственного должностного лица, выполнение режимных требований на объектах УИС в соответствии с законодательством РФ, а также обеспечение контроля за количественными и качественными характеристиками эксплуатируемых инженерно-технических средств охраны и надзора. Актуальность проводимого исследования обусловлена необходимостью качественной реализации в правоприменительной практике совокупности требований обеспечения мероприятий по обеспечению антитеррористической защищенности объектов (территорий) УИС с целью защиты прав и интересов всех субъектов уголовно-исполнительной системы от террористического посягательства. Авторами выявляются проблемы правового и организационного уровня при оценке состояния антитеррористической защищенности объектов УИС: формализм при проведении обследований, недостаточный уровень оснащенности объектов УИС инженерно-техническими средствами охраны и надзора, а также финансирования для удовлетворения нужд объектов УИС в части обеспечения антитеррористической защищенности. Помимо прочего упоминаются такие проблемы, как отсутствие унифицированных принципов организации деятельности комплексных комиссионных обследований, разработанных с учетом современных правоприменительных норм и запросов практики, а также обосновывается необходимость повышения компетентности сотрудников ФСИН России при проведении комплексных комиссионных обследований. In connection with the increase in the number of terrorist crimes, the resolution requires issues related to the provision of facilities (territories) of the penal system with anti-terrorist security tools, which include such as the implementation of organizational and practical measures for the anti-terrorist protection of the penal system, the availability of appropriate documentation and a responsible official, the implementation of regime requirements at the facilities of the penal system in accordance with the legislation of the Russian Federation, as well as ensuring control over the quantitative and qualitative characteristics of the operating engineering and technical means of protection and supervision. The relevance of the study is due to the fact that in law enforcement practice, a high-quality implementation of the set of requirements for ensuring the anti-terrorist protection of objects (territories) of the penal system is required so that the rights and interests of all subjects of the penal system in terms of protection from terrorist encroachment are observed. The authors identify the problems of the legal and organizational level when assessing the state of anti-terrorist security of penal facilities: formalism in conducting surveys, insufficient equipment of penal facilities with engineering and technical means of protection and supervision, as well as the level of funding to meet the needs of penal facilities in terms of ensuring anti-terrorist protection. Among other things, such problems as the lack of unified principles for organizing the activities of complex commission surveys, developed taking into account modern law enforcement norms and practice requests, are mentioned, as well as the need to improve the competence of employees of the Federal Penitentiary Service of Russia when conducting comprehensive commission surveys is substantiated.

MAPPING 2D TO 3D FORENSIC FACIAL RECOGNITION VIA BIO- INSPIRED ACTIVE APPEARANCE MODEL

2015 ◽  
Vol 78 (2-2) ◽  
Author(s):  
Siti Zaharah Abd. Rahman ◽  
Siti Norul Huda Sheikh Abdullah ◽  
Lim Eng Hao ◽  
Mohammed Hasan Abdulameer ◽  
Nazri Ahmad Zamani ◽  
...  
Keyword(s):  
Forensic Analysis ◽  
Support Vector ◽  
Appearance Model ◽  
Active Appearance Model ◽  
Video Footage ◽  
Digital Forensic ◽  
Facial Information ◽  
Active Appearance ◽  
2D Model ◽  
2D To 3D

This research done is to solve the problems faced by digital forensic analysts in identifying a suspect captured on their CCTV. Identifying the suspect through the CCTV video footage is a very challenging task for them as it involves tedious rounds of processes to match the facial information in the video footage to a set of suspect’s images. The biggest problem faced by digital forensic analysis is modeling 2D model extracted from CCTV video as the model does not provide enough information to carry out the identification process. Problems occur when a suspect in the video is not facing the camera, the image extracted is the side image of the suspect and it is difficult to make a matching with portrait image in the database. There are also many factors that contribute to the process of extracting facial information from a video to be difficult, such as low-quality video. Through 2D to 3D image model mapping, any partial face information that is incomplete can be matched more efficiently with 3D data by rotating it to matched position. The first methodology in this research is data collection; any data obtained through video recorder. Then, the video will be converted into an image. Images are used to develop the Active Appearance Model (the 2D face model is AAM) 2D and AAM 3D. AAM is used as an input for learning and testing process involving three classifiers, which are Random Forest, Support Vector Machine (SVM), and Neural Networks classifier. The experimental results show that the 3D model is more suitable for use in face recognition as the percentage of the recognition is higher compared with the 2D model.

scholarly journals Calm Before the Storm

2012 ◽  
Vol 4 (2) ◽  
pp. 28-48 ◽  
Author(s):  
George Grispos ◽  
Tim Storer ◽  
William Bradley Glisson
Keyword(s):  
Cloud Computing ◽  
Law Enforcement ◽  
Data Storage ◽  
It Infrastructure ◽  
Software Applications ◽  
Digital Forensic ◽  
Forensic Practice ◽  
New Research ◽  
Key Aspects ◽  
Control And Management

Cloud computing is a rapidly evolving information technology (IT) phenomenon. Rather than procure, deploy, and manage a physical IT infrastructure to host their software applications, organizations are increasingly deploying their infrastructure into remote, virtualized environments, often hosted and managed by third parties. This development has significant implications for digital forensic investigators, equipment vendors, law enforcement, as well as corporate compliance and audit departments, amongst other organizations. Much of digital forensic practice assumes careful control and management of IT assets (particularly data storage) during the conduct of an investigation. This paper summarises the key aspects of cloud computing and analyses how established digital forensic procedures will be invalidated in this new environment, as well as discussing and identifying several new research challenges addressing this changing context.

Forensic Analysis of Telegram Desktop-based Applications using the National Institute of Justice (NIJ) Method

2020 ◽  
Vol 8 (4) ◽  
pp. 381
Author(s):  
I Gusti Ngurah Guna Wicaksana ◽  
I Ketut Gede Suhartana
Keyword(s):  
Instant Messaging ◽  
Personal Information ◽  
Forensic Analysis ◽  
Criminal Cases ◽  
Forensic Evidence ◽  
Digital Forensic ◽  
National Institute Of Justice ◽  
Evidence Analysis ◽  
The Media ◽  
Log File

Abstract The development of telecommunications has increased very rapidly since the internet-based instant messaging service has spread rapidly to Indonesia. Telegram application is one of the growing and well-known application services in Indonesia, Desktop or smartphone-based Telegram applications, it is very possible to use digital crimes by using services, user personal information, or by hacking the Telegram application. This study explains the stages of investigation of cybercrime cases that occurred in desktop-based telegram. The method used for this research refers to the stage of investigation that was carried out in previous studies, namely using the National Institute of Justice (NIJ) method with the stages of the preparation stage, the collection stage, the examination stage, the analysis stage, and the reporting stage. The media used in this study is a desktop-based Telegram application that is synchronized with an Android-based Telegram. In this process, the location of the log file, cache, and digital proof image file was obtained in the conversation of a desktop-based Telegram application. Digital forensic evidence obtained is expected to strengthen evidence of criminal cases in court in the form of digital evidence analysis results. Keywords: Telecommunications, Digital Forensic, Telegram, Investigation, Cybercrime

Digital Forensic Analysis of Cybercrimes

2017 ◽  
Vol 11 (2) ◽  
pp. 25-37 ◽  
Author(s):  
Regner Sabillon ◽  
Jordi Serra-Ruiz ◽  
Victor Cavaller ◽  
Jeimy J. Cano
Keyword(s):  
Best Practices ◽  
International Collaboration ◽  
Forensic Analysis ◽  
Lessons Learned ◽  
Digital Ecosystems ◽  
Cyber Forensics ◽  
Digital Forensic ◽  
Chain Of Custody ◽  
Technological Ecosystems ◽  
Forensic Tools

This paper reviews the existing methodologies and best practices for digital investigations phases like collecting, evaluating and preserving digital forensic evidence and chain of custody of cybercrimes. Cybercriminals are adopting new strategies to launch cyberattacks within modified and ever changing digital ecosystems, this article proposes that digital investigations must continually readapt to tackle cybercrimes and prosecute cybercriminals, working in international collaboration networks, sharing prevention knowledge and lessons learned. The authors also introduce a compact cyber forensics model for diverse technological ecosystems called Cyber Forensics Model in Digital Ecosystems (CFMDE). Transferring the knowledge, international collaboration, best practices and adopting new digital forensic tools, methodologies and techniques will be hereinafter paramount to obtain digital evidence, enforce organizational cybersecurity policies, mitigate security threats, fight anti-forensics practices and indict cybercriminals. The global Digital Forensics community ought to constantly update current practices to deal with cybercriminality and foreseeing how to prepare to new technological environments where change is always constant.

Systematic Memory Forensic Analysis of Ransomware using Digital Forensic Tools

2020 ◽  
Vol 9 (2) ◽  
pp. 61-81
Author(s):  
Paul Joseph ◽  
Jasmine Norman
Keyword(s):  
Forensic Analysis ◽  
Vital Role ◽  
Financial Loss ◽  
Cyber Forensics ◽  
Digital Forensic ◽  
Memory Forensics ◽  
Forensic Tools

Cybercrimes catastrophically caused great financial loss in the year 2018 as powerful obfuscated malware known as ransomware continued to be a continual threat to governments and organizations. Advanced malwares capable of system encryption with sophisticated obscure keys left organizations paying the ransom that hackers demand. Since every individual is vulnerable to this assault, cyber forensics play a vital role either in educating society or combating the attacks. As cyber forensics is classified into many subdomains, memory forensics is the domain that leads in curbing these types of attacks. This article gives insight on importance of memory forensics and provides widespread analysis on working of ransomware, recognizes the workflow, provides the ways to overcome this attack. Furthermore, this article implements user defined rules by integrating into powerful search tools known as YARA to detect and prevent the ransomware attacks.

Development of Human-Symbiotic Robot “EMIEW” – Design Concept and System Construction –

2006 ◽  
Vol 18 (2) ◽  
pp. 195-202 ◽  
Author(s):  
Yuji Hosoda ◽  
◽  
Saku Egawa ◽  
Junichi Tamamoto ◽  
Kenjiro Yamamoto ◽  
...  
Keyword(s):  
Speech Synthesis ◽  
Autonomous Mobile Robot ◽  
System Construction ◽  
Complex Environments ◽  
High Quality ◽  
Daily Lives ◽  
Mobility System ◽  
User Friendly ◽  
Wheeled Mobility ◽  
World Exposition

We are developing a robot that will support people in their daily lives, i.e., a human-symbiotic robot. This kind of robot is required to coexist with users, be user friendly, and be capable of supporting them. As a first step to achieving the last goal, we have developed an autonomous mobile robot that makes use of a self-balancing two-wheeled mobility system and a body swing mechanism to shift its center of gravity. This allows it to move nimbly at up to six kilometers per hour. It also has capabilities that enable it to avoid collisions with obstacles and move safely through complex environments. It is able to interact with people naturally without special tools by means of distant-speech recognition and high-quality speech-synthesis technologies. These capabilities were demonstrated at the 2005 World Exposition Aichi Japan.

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