Vajiheh Sabeti; Mahsa Amerehei
Abstract
A steganography system must embed the message in an unseen and unrecognizable manner in the cover signal. Embedding information in transform coefficients, especially Discrete Wavelet Transform (DWT), is one of the most successful approaches in this field. The proposed method in this paper has two main ...
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A steganography system must embed the message in an unseen and unrecognizable manner in the cover signal. Embedding information in transform coefficients, especially Discrete Wavelet Transform (DWT), is one of the most successful approaches in this field. The proposed method in this paper has two main steps. In the first step, the XOR logical function was used to embed two bits of data in the adjacent DWT coefficient pair. No change in the coefficients will occur if the XOR result of the two bits of low-value data of the two adjacent coefficients is identical to the two bits of secret data. Otherwise, one or both of the coefficient(s) will need a one-unit increase or decrease. In the second step, the genetic algorithm was used to select, between the two possible solutions, a new value for the adjacent coefficient pair that needs to be changed. Using the genetic algorithm, the selections were made such that the generated stego image experienced the least change relative to the cover image. The results of comparing this method with the existing methods in low- and high-level embedding showed that the proposed method was successful in producing stego images with high-quality criteria. In addition, the SPAM steganalysis method did not show high accuracy in its detection. One of the benefits of the proposed method is the need for a short key to embed and extract the secret message. This issue increases the security and feasibility of the proposed method.
Vajiheh Sabeti; Minoo Shoaei
Abstract
In network steganography methods based on packet length, the length of the packets is used as a carrier for exchanging secret messages. Existing methods in this area are vulnerable against detections due to abnormal network traffic behaviors. The main goal of this paper is to propose a method which has ...
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In network steganography methods based on packet length, the length of the packets is used as a carrier for exchanging secret messages. Existing methods in this area are vulnerable against detections due to abnormal network traffic behaviors. The main goal of this paper is to propose a method which has great resistance to network traffic detections. In the first proposed method, the sender embeds a bit of data in each pair that includes two non-identical packet lengths. In the current situation, if the first packet length of the pair is larger than the second one, it shows a ‘1’ bit and otherwise, it shows a ‘0’ bit. If the intended bit of the sender is in conflict with the current status, he/she will create the desired status by swapping the packet lengths. In this method, the paired packets can be selected freely, but in the second proposed method, the packets are divided into buckets and only packets within a single bucket can be paired together. In this case, the embedding method is similar to the previous one. The results show that the second method, despite having low embedding capacity, will be more secure in real traffic compared to the other methods. Since the packet lengths of UDP protocol are more random in comparison to TCP, the proposed methods have higher embedding capacity and they are more secure for UDP-based packets. However, these methods are only applicable to the protocols in which the packet length has not a constant value.
V. Sabeti; Sh. Samavi; M. Mahdavi; Sh. Shirani
Abstract
In this paper a steganalysis method is proposed for pixel value differencing method. This steganographic method, which has been immune against conventional attacks, performs the embedding in the difference of the values of pixel pairs. Therefore, the histogram of the differences of an embedded image ...
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In this paper a steganalysis method is proposed for pixel value differencing method. This steganographic method, which has been immune against conventional attacks, performs the embedding in the difference of the values of pixel pairs. Therefore, the histogram of the differences of an embedded image is di_erent as compared with a cover image. A number of characteristics are identified in the difference histogram that show meaningful alterations when an image is embedded. Five distinct multilayer perceptrons neural networks are trained to detect different levels of embedding. Every image is fed in to all networks and a voting system categorizes the image as stego or cover. The implementation results indicate an 88.6% success in correct categorization of the test images.