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Detection of Stego-Images in Communication among the Terrorist Boko-Haram Sect in Nigeria
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作者 owoeye kolade Ajayi Adedoyin Olayinka +2 位作者 Fadugba Sunday Obayomi Adesoji Isinkaye Folasade Olubusola 《Journal of Data Analysis and Information Processing》 2015年第4期168-174,共7页
Nigeria was listed as a part of terrorist states by United States of America as a result of Islamic group (Boko Haram Sect) attacks and other activities in the nation. It has also been discovered that the group emplo... Nigeria was listed as a part of terrorist states by United States of America as a result of Islamic group (Boko Haram Sect) attacks and other activities in the nation. It has also been discovered that the group employs “steganographic” schemes as a secure means for transmitting their hidden information to each other via Internet and social networks. The group has killed thousands of people since their increased insurgency in July, 2009. These challenges have affected the nation’s foreign policies, political and social economic developments. This research addresses the challenges by employing forensic technique using blind steganalysis approach to detect the presence of the hidden messages in images. Image Quality Metric is employed for extracting the features, and logistic regression is trained as the classifier to predict the stego-images. We show the effectiveness of the method by conducting test and analysis with 319 images varying in size and style. The result shows that the performance of the method is better than other steganalysis methods. 展开更多
关键词 Stego Staganalysis LOGISTIC Regression Boko-Haram SECT
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Fingerprint Database Optimization Using Watershed Transformation Algorithm
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作者 owoeye kolade Ajayi Adedoyin Olayinka Ukorigho Ovie 《Open Journal of Optimization》 2014年第4期59-67,共9页
Fingerprints are a unique feature for identification and verification of humans. The need to optimise several databases for storing the images of fingerprints is a major concerning issue. Several segmentation algorith... Fingerprints are a unique feature for identification and verification of humans. The need to optimise several databases for storing the images of fingerprints is a major concerning issue. Several segmentation algorithms have been used in the time past but there are still several challenges facing some current segmentation algorithms like computational efficiency. Another challenge is that segmentation procedure can be impractically slow, or requires extremely large amounts of memory. This paper addresses the challenges by employing watershed flooding algorithm on the fingerprint images so as to optimize the sizes of the databases. A pre-processing plug-in that implements this segmentation process is developed using Java. We showed its effectiveness by testing it on fingerprint image dataset and the entropy showed that the segmented images sizes were reduced. 展开更多
关键词 WATERSHED TRANSFORMATION FINGERPRINT SEGMENTATION Entrophy
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