Attribute Reduction for Steganalysis Redundant Indicators
Chen Huan Hong · Telecommunication Engineering · 2011
For the existence of knowledge redundancy in steganalysis evaluation indicators,an attribute reduction for steganalysis indicators is proposed.Based on analysing the indicators knowledge redundant,the algorithm uses BCC algorithm to get initial interzone and its reduction of each index, with which data of experiment result are despersed.The discrete matrix is used as the input of Heuristics Optimal Finding Reduct Algorithm based on Frequencies Attributes(HORAFA) algorithm,and then the final reduction result of steganalysis evaluation indicators is obtained.The experiments results show that the algorithm is effective in steganalysis evaluation indicators reduction.It is proved that the attribute reduction algorithm can increase the reliability of evaluation results by analysing the compatibility of given evaluation algorithm before and after attribute reduction.