Download Digital Forensics and Cyber Crime: 7th International by Joshua I. James, Frank Breitinger PDF

By Joshua I. James, Frank Breitinger

This publication constitutes the refereed lawsuits of the seventh overseas convention on electronic Forensics and Cyber Crime, ICDF2C 2015, held in Seoul, South Korea, in October 2015. The 14 papers and three abstracts have been chosen from forty submissions and canopy assorted themes starting from strategies of cyber crime investigations to electronic forensic schooling, community forensics, and foreign cooperation in electronic investigations.

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Additional resources for Digital Forensics and Cyber Crime: 7th International Conference, ICDF2C 2015, Seoul, South Korea, October 6–8, 2015, Revised Selected Papers

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Singh et al. Proposed Methodology The Frame duplication is one of the major attacks performed on videos because it is easy to perform in comparison with other types of attack. Hence a need of efficient, fast and reliable algorithm arises to detect frame duplication. In this type of attack some sequence of frames are replaced with some other sequence of frames from the same video sequence. A novel method is presented through this paper to detect frame duplication. After performing a number of experiments on any raw video (even with static scene), it is concluded that there is very less probability to have two or more frames exactly same on the basis of intensity values.

On the database lookup problem of approximate matching. Digital Invest. 11, S1–S9 (2014) 52 V. Gupta and F. Breitinger 7. : Approximate matching: Definition and terminology. Special publication 800–168. National Institute of Standards and Technologies, May 2014 8. : Frash: a framework to test algorithms of similarity hashing. Digit. Investig. 10, S50–S58 (2013) 9. : Network applications of bloom filters: a survey. Internet Math. 1(4), 485–509 (2004) 10. : Cuckoo filter: practically better than bloom.

It should be ensured that each feature vector (vi) contains its actual position even after sorting. 3 Calculation of RMSE and Suspected Frame Detection RMSE (Root Mean Square Error) is calculated between the feature vectors of adjacent frames after sorting. If RMSE is found more than threshold then discards such frames and rest of the frames are marked as suspected frames. We set the threshold value little bigger in order to detect suspected frames in compressed videos. 4 Detection of Duplicated Frames Finally, we get a list of frames that are suspected frames according to their RMSE.

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