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Mina Zolfy Lighvan

Publications and source records attributed to Mina Zolfy Lighvan.

2 recordsLinked to original sources

FPGA Implementation of a Novel Image Steganography for Hiding Images

As the complexity of current data flow systems and according infrastructure networks increases, the security of data transition through such platforms becomes more important. Thus, different areas of steganography turn to one of the most challengeable topics of current researches. In this paper a novel method is presented to hide an image into the host image and Hardware/Software design is proposed to implement our stagenography system on FPGA- DE2 70 Altera board. The size of the secret image is quadrant of the host image. Host image works as a cipher key to completely distort and encrypt the secret image using XOR operand. Each pixel of the secret image is composed of 8 bits (4 bit-pair) in which each bit-pair is distorted by XORing it with two LSB bits of the host image and putting the results in the location of two LSB bits of host image. The experimental results show the effectiveness of the proposed method compared to the most recently proposed algorithms by considering that the obtained information entropy for encrypt image is approximately equal to 8.

cs.AR↗

HPS: a hierarchical Persian stemming method

In this paper, a novel hierarchical Persian stemming approach based on the Part-Of-Speech of the word in a sentence is presented. The implemented stemmer includes hash tables and several deterministic finite automata in its different levels of hierarchy for removing the prefixes and suffixes of the words. We had two intentions in using hash tables in our method. The first one is that the DFA don't support some special words, so hash table can partly solve the addressed problem. the second goal is to speed up the implemented stemmer with omitting the time that deterministic finite automata need. Because of the hierarchical organization, this method is fast and flexible enough. Our experiments on test sets from Hamshahri collection and security news (istna.ir) show that our method has the average accuracy of 95.37% which is even improved in using the method on a test set with common topics.

cs.CL↗