کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4969237 1449927 2017 27 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Combating highly imbalanced steganalysis with small training samples using feature selection,
ترجمه فارسی عنوان
مبارزه با استبانگالیس بسیار نامناسب با نمونه های آموزشی کوچک با استفاده از انتخاب ویژگی،
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
چکیده انگلیسی
We consider a particular paradigm of steganalysis, namely, highly imbalanced steganalysis with small training samples, in which the cover images always significantly outnumber the stego ones. Researchers have rigorously studied sampling and learning algorithms as well as feature selection approaches to the class imbalance problem, but the research in the steganalysis domain is rare. This study provides a systematic comparison of eight feature selection metrics and of three types of methods developed for the imbalanced data classification problem in the steganalysis domain. Each metric is compared across three different classifiers and four steganalytic features. The efficiency of the metrics is evaluated to determine which performs best with minimal features selected. The performance of the three types of methods and their combinations is examined. Moreover, we also investigate the effect of feature dimensionality, sample number and imbalance degree on the performance of feature selection inresolving imbalanced image steganalysis.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Visual Communication and Image Representation - Volume 49, November 2017, Pages 243-256
نویسندگان
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