6,749 research outputs found

    Admissions Magazine Spring 2021

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    We Will Rock It: Eagles Around the Globe Aim for Asteroid Belt. Who We Are Eagles Around the Globe Aim for Asteroid Belt Hands-On Experiences Finding a Future in Forensics Leading the Way Forward Golden Eagles Soaring High On the Open Road Hole-in-one Fellowship Storytelling that Serves Now Trending: What’s life like when you join the Embry-Riddle family? It’s rewarding, challenging — and fun. Have a look for yourself. Worldwide / Online Switching Gears Connecting in a Digital World Hitting the Ground Running Florida Campus Astronomical Selfie Surf\u27s Up! Beach Break Driving Drone Research Arizona Campus Advancing the Safety of Air Travel A degree Worth Investigating For These Students, it is Rocket Science Leading with Compassion Next Stepshttps://commons.erau.edu/admissions-magazine/1003/thumbnail.jp

    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

    Dark clouds on the horizon:the challenge of cloud forensics

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    We introduce the challenges to digital forensics introduced by the advent and adoption of technologies, such as encryption, secure networking, secure processors and anonymous routing. All potentially render current approaches to digital forensic investigation unusable. We explain how the Cloud, due to its global distribution and multi-jurisdictional nature, exacerbates these challenges. The latest developments in the computing milieu threaten a complete “evidence blackout” with severe implications for the detection, investigation and prosecution of cybercrime. In this paper, we review the current landscape of cloud-based forensics investigations. We posit a number of potential solutions. Cloud forensic difficulties can only be addressed if we acknowledge its socio-technological nature, and design solutions that address both human and technological dimensions. No firm conclusion is drawn; rather the objective is to present a position paper, which will stimulate debate in the area and move the discipline of digital cloud forensics forward. Thus, the paper concludes with an invitation to further informed debate on this issue

    Digital Forensic Evidence in the Courtroom: Understanding Content and Quality

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    With the widespread permeation of continually advancing technologies into our daily lives, it is inevitable that the product of those technologies, i.e. digital information, makes its way into the courtroom. This has largely occurred in the form of electronic discovery, or “e-discovery,” where each party involved in an action provides the relevant information they possess electronically. However, in cases where information is hidden, erased, or otherwise altered, digital forensic analysis is necessary to draw further conclusions about the available evidence. Digital forensic analysis is analogous to more traditional forensic analysis. For example, in criminal cases where a firearm was used in the commission of the crime, but the gun is not readily admissible, forensic science is necessary to trace the origin of the weapon, perform fingerprint analysis on it, and compare fired bullet casings to ensure the weapon used and the weapon analyzed are one and the same. In sum, digital forensics is the preservation and analysis of electronic data. These data include the primary substantive data (the gun) and the secondary data attached to the primary data, such as data trails and time/date stamps (the fingerprints). These data trails and other metadata markers are often the key to establishing a timeline and correlating important events

    Digital Forensic Evidence in the Courtroom: Understanding Content and Quality

    Get PDF
    With the widespread permeation of continually advancing technologies into our daily lives, it is inevitable that the product of those technologies, i.e. digital information, makes its way into the courtroom. This has largely occurred in the form of electronic discovery, or “e-discovery,” where each party involved in an action provides the relevant information they possess electronically. However, in cases where information is hidden, erased, or otherwise altered, digital forensic analysis is necessary to draw further conclusions about the available evidence. Digital forensic analysis is analogous to more traditional forensic analysis. For example, in criminal cases where a firearm was used in the commission of the crime, but the gun is not readily admissible, forensic science is necessary to trace the origin of the weapon, perform fingerprint analysis on it, and compare fired bullet casings to ensure the weapon used and the weapon analyzed are one and the same. In sum, digital forensics is the preservation and analysis of electronic data. These data include the primary substantive data (the gun) and the secondary data attached to the primary data, such as data trails and time/date stamps (the fingerprints). These data trails and other metadata markers are often the key to establishing a timeline and correlating important events

    Assessing database and network threats in traditional and cloud computing

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    Cloud Computing is currently one of the most widely-spoken terms in IT. While it offers a range of technological and financial benefits, its wide acceptance by organizations is not yet wide spread. Security concerns are a main reason for this and this paper studies the data and network threats posed in both traditional and cloud paradigms in an effort to assert in which areas cloud computing addresses security issues and where it does introduce new ones. This evaluation is based on Microsoft’s STRIDE threat model and discusses the stakeholders, the impact and recommendations for tackling each threat

    An Analysis of Optical Contributions to a Photo-Sensor's Ballistic Fingerprints

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    Lens aberrations have previously been used to determine the provenance of an image. However, this is not necessarily unique to an image sensor, as lens systems are often interchanged. Photo-response non-uniformity noise was proposed in 2005 by Luk\'a\v{s}, Goljan and Fridrich as a stochastic signal which describes a sensor uniquely, akin to a "ballistic" fingerprint. This method, however, did not account for additional sources of bias such as lens artefacts and temperature. In this paper, we propose a new additive signal model to account for artefacts previously thought to have been isolated from the ballistic fingerprint. Our proposed model separates sensor level artefacts from the lens optical system and thus accounts for lens aberrations previously thought to be filtered out. Specifically, we apply standard image processing theory, an understanding of frequency properties relating to the physics of light and temperature response of sensor dark current to classify artefacts. This model enables us to isolate and account for bias from the lens optical system and temperature within the current model.Comment: 16 pages, 9 figures, preprint for journal submission, paper is based on a thesis chapte
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