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

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

Central Florida Future, Vol. 39 No. 145, December 3, 2007

Champs; Hitt\u27s pay high among colleges; Master\u27s programs approved to improve; Judge argues for softer drug laws.https://stars.library.ucf.edu/centralfloridafuture/3060/thumbnail.jp

Forensic Data Mining: Finding Intrusion Patterns in Evidentiary Data

In The extensive growth of computing networks and tools and tricks for intruding into and attacking networks has underscored the importance of intrusion detection in network security. Yet, contemporary intrusion detection systems (IDS) are limiting in that they typically employ a misuse detection strategy, with searches for patterns of program or user behavior that match known intrusion scenarios, or signatures. Accordingly, there is a need for more robust and adaptive methods for designing and updating intrusion detection systems. One promising approach is the use of data mining methods for discovering intrusion patterns. Discovered patterns and profiles can be translated into classifiers for detecting deviations from normal usage patterns. Among promising mining methods are association rules, link analysis, and rule-induction algorithms. Our particular contribution is a unique approach to combining association rules with link analysis and a rule-induction algorithm to augment intrusion detection systems

A comparison of forensic evidence recovery techniques for a windows mobile smart phone

<p>Acquisition, decoding and presentation of information from mobile devices is complex and challenging. Device memory is usually integrated into the device, making isolation prior to recovery difficult. In addition, manufacturers have adopted a variety of file systems and formats complicating decoding and presentation.</p> <p>A variety of tools and methods have been developed (both commercially and in the open source community) to assist mobile forensics investigators. However, it is unclear to what extent these tools can present a complete view of the information held on a mobile device, or the extent the results produced by different tools are consistent.</p> <p>This paper investigates what information held on a Windows Mobile smart phone can be recovered using several different approaches to acquisition and decoding. The paper demonstrates that no one technique recovers all information of potential forensic interest from a Windows Mobile device; and that in some cases the information recovered is conflicting.</p&gt

Writer Identification Using Inexpensive Signal Processing Techniques

We propose to use novel and classical audio and text signal-processing and otherwise techniques for "inexpensive" fast writer identification tasks of scanned hand-written documents "visually". The "inexpensive" refers to the efficiency of the identification process in terms of CPU cycles while preserving decent accuracy for preliminary identification. This is a comparative study of multiple algorithm combinations in a pattern recognition pipeline implemented in Java around an open-source Modular Audio Recognition Framework (MARF) that can do a lot more beyond audio. We present our preliminary experimental findings in such an identification task. We simulate "visual" identification by "looking" at the hand-written document as a whole rather than trying to extract fine-grained features out of it prior classification.Comment: 9 pages; 1 figure; presented at CISSE'09 at http://conference.cisse2009.org/proceedings.aspx ; includes the the application source code; based on MARF described in arXiv:0905.123

Air Force Institute of Technology Research Report 2009

This report summarizes the research activities of the Air Force Institute of Technology’s Graduate School of Engineering and Management. It describes research interests and faculty expertise; lists student theses/dissertations; identifies research sponsors and contributions; and outlines the procedures for contacting the school. Included in the report are: faculty publications, conference presentations, consultations, and funded research projects. Research was conducted in the areas of Aeronautical and Astronautical Engineering, Electrical Engineering and Electro-Optics, Computer Engineering and Computer Science, Systems and Engineering Management, Operational Sciences, Mathematics, Statistics and Engineering Physics

Downstream Competence Challenges and Legal/Ethical Risks in Digital Forensics

Forensic practice is an inherently human-mediated system, from processing and collection of evidence to presentation and judgment. This requires attention to human factors and risks which can lead to incorrect judgments and unjust punishments. For digital forensics, such challenges are magnified by the relative newness of the discipline and the use of electronic evidence in forensic proceedings. Traditional legal protections, rules of procedure and ethics rules mitigate these challenges. Application of those traditions better ensures forensic findings are reliable. This has significant consequences where findings may impact a person\u27s liberty or property, a person\u27s life or even the political direction of a nation. Conversely, a legal, procedural or ethical failure leads to a failure in the mission of the system of justice and of public security We examine this for digital forensics and outline a framework to mitigate the risk of a forensic and security failure

Make Research Data Public? -- Not Always so Simple: A Dialogue for Statisticians and Science Editors

Putting data into the public domain is not the same thing as making those data accessible for intelligent analysis. A distinguished group of editors and experts who were already engaged in one way or another with the issues inherent in making research data public came together with statisticians to initiate a dialogue about policies and practicalities of requiring published research to be accompanied by publication of the research data. This dialogue carried beyond the broad issues of the advisability, the intellectual integrity, the scientific exigencies to the relevance of these issues to statistics as a discipline and the relevance of statistics, from inference to modeling to data exploration, to science and social science policies on these issues.Comment: Published in at http://dx.doi.org/10.1214/10-STS320 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Air Force Institute of Technology Research Report 2010

This report summarizes the research activities of the Air Force Institute of Technology’s Graduate School of Engineering and Management. It describes research interests and faculty expertise; lists student theses/dissertations; identifies research sponsors and contributions; and outlines the procedures for contacting the school. Included in the report are: faculty publications, conference presentations, consultations, and funded research projects. Research was conducted in the areas of Aeronautical and Astronautical Engineering, Electrical Engineering and Electro-Optics, Computer Engineering and Computer Science, Systems and Engineering Management, Operational Sciences, Mathematics, Statistics and Engineering Physic