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Improving Image Recovery Rates in Big Data


Improving Image Recovery Rates in Big Data

The current problem with identifying objectionable images is that there are an enormous number of images on the internet that require analysing. forensic investigators are currently using two techniques for identification, namely; content based image retrieval (cbir) that uses visual aspects of an image for identification and concept based image indexing (cbii) that uses the metadata of the image for identification. the current challenge for investigators is to resolve the dilemma of one technique that is accurate, but very slow against the other that is inaccurate, but very fast for image retrieval. the utilization of both techniques to solve the problem is cost prohibitive in terms of time and resources in professional practice. our research was to investigate other methods of identifying images, which resulted with a ‘hashing’ based methodology that had the potential for providing an improvement in performance overall.




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Coming up in the Next issue of Digital Forensics Magazine

Coming up in Issue 34 on sale from February 2018:


Device Forensics in the Internet of Things

As more businesses and consumers adopt IoT devices, privacy violations and cyber-attacks by malicious actors will become commonplace due to the insecure IoT infrastructure. Read More »

Data Destruction In Current Hard Disks & Data Destruction Techniques

Data destruction is a process traditionally applied using physical techniques, aiming at the completely destruction of the hard disk, however, there is an increasing interest in the use of logical techniques for data destruction, that allow reusing the physical device. Read More »

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Faster Searching For Known Illegal Content

Cryptographic (“MD5”) hash searching for known illegal material is one of the most thorough methods of digital forensic investigation. However, the technique is hampered by the ever-increasing size of media being examined, and the size of the hash list being searched. Read More »

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