2,171 research outputs found

    Cloud Digital Forensics Evaluation and Crimes Detection

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    © 2018, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. Cloud computing is one of the significant topics of today’s era; due to the enhancement it brings to the Information Technology world. This transformation lead to its rapid adoption by different sectors, ranging from enterprise to personal usage. Organizations are constantly looking for ways to increase productivity with optimum cost; which derived the need for Cloud environments and its underlying virtualized infrastructure. With the increase usage of Cloud based infrastructure, criminals utilized its anonymity factor to hide their criminal activities; escaping from legal actions. This paper highlights the obstacles experienced during Cloud virtual layer forensics acquisition and analysis, due to lack of specialized forensics tools. We have developed a framework to aid in assessing the virtual environment readiness for forensics investigation and examine the applicability of existing state-of-the-art forensics tools to Cloud environment. The paper reveals the need for having specialized forensics tools for Cloud infrastructure forensics

    Calm before the storm: the challenges of cloud computing in digital forensics

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    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 (among others). 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. Several new research challenges addressing this changing context are also identified and discussed

    Cyber security investigation for Raspberry Pi devices

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    Big Data on Cloud application is growing rapidly. When the cloud is attacked, the investigation relies on digital forensics evidence. This paper proposed the data collection via Raspberry Pi devices, in a healthcare situation. The significance of this work is that could be expanded into a digital device array that takes big data security issues into account. There are many potential impacts in health area. The field of Digital Forensics Science has been tagged as a reactive science by some who believe research and study in the field often arise as a result of the need to respond to event which brought about the needs for investigation; this work was carried as a proactive research that will add knowledge to the field of Digital Forensic Science. The Raspberry Pi is a cost-effective, pocket sized computer that has gained global recognition since its development in 2008; with the wide spread usage of the device for different computing purposes. Raspberry Pi can potentially be a cyber security device, which can relate with forensics investigation in the near future. This work has used a systematic approach to study the structure and operation of the device and has established security issues that the widespread usage of the device can pose, such as health or smart city. Furthermore, its evidential information applied in security will be useful in the event that the device becomes a subject of digital forensic investigation in the foreseeable future. In healthcare system, PII (personal identifiable information) is a very important issue. When Raspberry Pi plays a processor role, its security is vital; consequently, digital forensics investigation on the Raspberry Pies becomes necessary

    Computer Forensics: Dark Net Forensic Framework and Tools Used for Digital Evidence Detection

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    As the development of technology increases and its use becomes increasingly more widespread, computer crimes grow. Hence, computer forensics research is becoming more crucial in developing good forensic frameworks and digital evidence detection tools to deter more cyber-attacks. In this paper, we explore the science of computer forensics, a dark web forensic framework, and digital evidence detection tools

    Development of conceptual framework for cyber fraud investigation

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    The increase in the number of internet users in Indonesia as much as 175.4 million as recorded in the Datareportal.com report and 4.83 billion globally, impact the increase in the number of cyber fraud cases. Data states that 96% of fraud cases are not resolved due to fraud methods carried out online and make it difficult for legal officers to obtain evidence. Previous fraud investigation research mainly focused on fraud detection, so this research focuses on submitting a framework for investigating cyber fraud cases. The cyber fraud case requires a new framework for investigation because in this fraud case, there is digital evidence that is very prone to be damaged, lost, or modified, which makes this case unsolved. This research aims to develop a framework that is expected to help auditors to uncover cases of cyber fraud so that resolved cyber fraud cases can increase. The method used in making this framework uses Jabareen's conceptual framework development method, which consists of 6 stages, namely, Mapping the selected data source, extensive reading and categorizing of the chosen data, Identifying and naming objects, Deconstructing and categorizing the concept, Integrating concept, Synthesis, resynthesis. And make it all sense. The framework for cyber fraud investigation uses 22 digital forensic frameworks and eight frameworks for fraud audit investigations. The results of developing a framework using the Jabareen method resulted in 8 stages, integrating various concepts selected from digital forensics and fraud audits. Evaluation of framework development was carried out by giving limited questionnaires to practitioners and academics, which produced 89% for the feasibility value and needs of the framework and 67% there is no need for changes to the framework being developed

    EviPlant: An efficient digital forensic challenge creation, manipulation and distribution solution

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    Education and training in digital forensics requires a variety of suitable challenge corpora containing realistic features including regular wear-and-tear, background noise, and the actual digital traces to be discovered during investigation. Typically, the creation of these challenges requires overly arduous effort on the part of the educator to ensure their viability. Once created, the challenge image needs to be stored and distributed to a class for practical training. This storage and distribution step requires significant time and resources and may not even be possible in an online/distance learning scenario due to the data sizes involved. As part of this paper, we introduce a more capable methodology and system as an alternative to current approaches. EviPlant is a system designed for the efficient creation, manipulation, storage and distribution of challenges for digital forensics education and training. The system relies on the initial distribution of base disk images, i.e., images containing solely base operating systems. In order to create challenges for students, educators can boot the base system, emulate the desired activity and perform a "diffing" of resultant image and the base image. This diffing process extracts the modified artefacts and associated metadata and stores them in an "evidence package". Evidence packages can be created for different personae, different wear-and-tear, different emulated crimes, etc., and multiple evidence packages can be distributed to students and integrated into the base images. A number of additional applications in digital forensic challenge creation for tool testing and validation, proficiency testing, and malware analysis are also discussed as a result of using EviPlant.Comment: Digital Forensic Research Workshop Europe 201
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