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Digital Investigation, Volume 10
Volume 10, Number 1, June 2013
- Eoghan Casey:
Smartphone incident response. 1-2
- Darren Quick, Kim-Kwang Raymond Choo:
Dropbox analysis: Data remnants on user machines. 3-18 - Martin Kerrigan:
A capability maturity model for digital investigations. 19-33 - Keyun Ruan, Joe Carthy, M. Tahar Kechadi, Ibrahim M. Baggili:
Cloud forensics definitions and critical criteria for cloud forensic capability: An overview of survey results. 34-43 - William Bradley Glisson, Tim Storer, Joe Buchanan-Wollaston:
An empirical comparison of data recovered from mobile forensic toolkits. 44-55 - Floris Gisolf, Zeno J. M. H. Geradts, Dennie Verhoeven, Coert Klaver:
The effects of switching the camera module from BlackBerry Curve 9360 devices. 56-61 - Ming Xu, Xue Yang, Beibei Wu, Jun Yao, Haiping Zhang, Jian Xu, Ning Zheng:
A metadata-based method for recovering files and file traces from YAFFS2. 62-72 - Mohammad Akbarpour Sekeh, Mohd Aizaini Maarof, Mohd. Foad Rohani, Babak Mahdian:
Efficient image duplicated region detection model using sequential block clustering. 73-84
Volume 10, Number Supplement, August 2013
- Namheun Son, Yunho Lee, Dohyun Kim, Joshua I. James, Sangjin Lee, Kyungho Lee:
A study of user data integrity during acquisition of Android devices. S3-S11 - Justin Grover:
Android forensics: Automated data collection and reporting from a mobile device. S12-S20 - Ralf D. Brown:
Improved recovery and reconstruction of DEFLATEd files. S21-S29 - Stefan Vömel, Johannes Stüttgen:
An evaluation platform for forensic memory acquisition software. S30-S40 - Mario Piccinelli, Paolo Gubian:
Modern ships Voyage Data Recorders: A forensics perspective on the Costa Concordia shipwreck. S41-S49 - Frank Breitinger, Georgios Stivaktakis, Harald Baier:
FRASH: A framework to test algorithms of similarity hashing. S50-S58 - Andrew White, Bradley L. Schatz, Ernest Foo:
Integrity verification of user space code. S59-S68 - Vassil Roussev, Candice Quates:
File fragment encoding classification - An empirical approach. S69-S77 - Neil C. Rowe, Riqui Schwamm, Simson L. Garfinkel:
Language translation for file paths. S78-S86 - Josiah Dykstra, Alan T. Sherman:
Design and implementation of FROST: Digital forensic tools for the OpenStack cloud computing platform. S87-S95 - Mark D. Guido, Jared Ondricek, Justin Grover, David Wilburn, Thanh Nguyen, Andrew Hunt:
Automated identification of installed malicious Android applications. S96-S104 - Johannes Stüttgen, Michael Cohen:
Anti-forensic resilient memory acquisition. S105-S115 - Jon Stewart, Joel Uckelman:
Unicode search of dirty data, or: How I learned to stop worrying and love Unicode Technical Standard #18. S116-S125
Volume 10, Number 2, September 2013
- Eoghan Casey:
Triage in digital forensics. 85-86
- Mark Pollitt:
Triage: A practical solution or admission of failure. 87-88 - Andreas Moser, Michael I. Cohen:
Hunting in the enterprise: Forensic triage and incident response. 89-98 - Stavros N. Shiaeles, Anargyros Chryssanthou, Vasilios Katos:
On-scene triage open source forensic tool chests: Are they effective? 99-115 - Adrian Shaw, Alan Browne:
A practical and robust approach to coping with large volumes of data submitted for digital forensic examination. 116-128 - Martin B. Koopmans, Joshua I. James:
Automated network triage. 129-137 - Eoghan Casey, Gary Katz, Joe Lewthwaite:
Honing digital forensic processes. 138-147 - Joshua I. James, Pavel Gladyshev:
A survey of digital forensic investigator decision processes and measurement of decisions based on enhanced preview. 148-157 - Vassil Roussev, Candice Quates, Robert Martell:
Real-time digital forensics and triage. 158-167 - Richard E. Overill, Jantje A. M. Silomon, Keith A. Roscoe:
Triage template pipelines in digital forensic investigations. 168-174 - Ilyoung Hong, Hyeon Yu, Sangjin Lee, Kyungho Lee:
A new triage model conforming to the needs of selective search and seizure of electronic evidence. 175-192 - Fabio Marturana, Simone Tacconi:
A Machine Learning-based Triage methodology for automated categorization of digital media. 193-204
Volume 10, Number 3, October 2013
- Eoghan Casey:
New developments in digital & multimedia forensics. 205-206
- Floris Gisolf, Anwar Malgoezar, Teun Baar, Zeno J. M. H. Geradts:
Improving source camera identification using a simplified total variation based noise removal algorithm. 207-214 - Lit-Hung Chan, Ngai-Fong Law, Wan-Chi Siu:
A confidence map and pixel-based weighted correlation for PRNU-based camera identification. 215-225 - Gajanan K. Birajdar, Vijay H. Mankar:
Digital image forgery detection using passive techniques: A survey. 226-245 - Rimba Whidiana Ciptasari, Kyung Hyune Rhee, Kouichi Sakurai:
Exploiting reference images for image splicing verification. 246-258 - Jason S. Hale:
Amazon Cloud Drive forensic analysis. 259-265 - Darren Quick, Kim-Kwang Raymond Choo:
Forensic collection of cloud storage data: Does the act of collection result in changes to the data or its metadata? 266-277
Volume 10, Number 4, December 2013
- Eoghan Casey:
Enhancing forensic science through basic and applied research. 279-280
- Huw Read, Konstantinos Xynos, Iain Sutherland, Gareth Davies, Tom Houiellebecq, Frode Roarson, Andrew Blyth:
Manipulation of hard drive firmware to conceal entire partitions. 281-286 - Ben Martini, Kim-Kwang Raymond Choo:
Cloud storage forensics: ownCloud as a case study. 287-299 - Christopher Lees:
Determining removal of forensic artefacts using the USN change journal. 300-310 - Athina Provataki, Vasilios Katos:
Differential malware forensics. 311-322 - Konstantia Barmpatsalou, Dimitrios Damopoulos, Georgios Kambourakis, Vasilios Katos:
A critical review of 7 years of Mobile Device Forensics. 323-349 - Tamer Shanableh:
Detection of frame deletion for digital video forensics. 350-360 - Christian Winter, Markus Schneider, York Yannikos:
F2S2: Fast forensic similarity search through indexing piecewise hash signatures. 361-371 - Philip Penrose, Richard Macfarlane, William J. Buchanan:
Approaches to the classification of high entropy file fragments. 372-384 - Pratik C. Patel, Upasna Singh:
A novel classification model for data theft detection using advanced pattern mining. 385-397
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