Computational intelligence-based steganalysis comparison for RCM-DWT and PVA-MOD methods

This research article proposes data hiding technique for improving the data hiding procedure and securing the data transmission with the help of contrast mapping technique along with advanced data encryption standard. High data hiding capacity, image quality and security are the measures of steganography. Of these three measures, number of bits that can be hidden in a single cover pixel, bits per pixel (bpp), is very important and many researchers are working to improve the bpp. We propose an improved high capacity data hiding method that maintains the acceptable image quality that is more than 30 dB and improves the embedding capacity higher than that of the methods proposed in recent years. The method proposed in this paper uses notational system and achieves higher embedding rate of 4 bpp and also maintain the good visual quality. To measure the efficiency of the proposed information hiding methodology, a simulation system was developed with some of impairments caused by a communication system. PSNR (Peak Signal to Noise ratio) is used to verify the robustness of the images. The proposed research work is verified in accordance to noise analysis. To evaluate the defencing performance during attack RS steganalysis is used

One-Time Pad Encryption Steganography System

In this paper we introduce and describe a novel approach to adaptive image steganography which is combined with One-Time Pad encryption, and demonstrate the software which implements this methodology. Testing using the state-of-the-art steganalysis software tool StegExpose concludes the image hiding is reliably secure and undetectable using reasonably-sized message payloads (≤25% message bits per image pixel; bpp). Payload image file format outputs from the software include PNG, BMP, JP2, JXR, J2K, TIFF, and WEBP. A variety of file output formats is empirically important as most steganalysis programs will only accept PNG, BMP, and possibly JPG, as the file inputs. Keywords: steganography, one-time pad, steganalysis, information hiding, digital forensic

Positive Identification of LSB Image Steganography Using Cover Image Comparisons

In this paper we introduce a new software concept specifically designed to allow the digital forensics professional to clearly identify and attribute instances of LSB image steganography by using the original cover image in side-by-side comparison with a suspected steganographic payload image. The “CounterSteg” software allows detailed analysis and comparison of both the original cover image and any modified image, using sophisticated bit- and color-channel visual depiction graphics. In certain cases, the steganographic software used for message transmission can be identified by the forensic analysis of LSB and other changes in the payload image. The paper demonstrates usage and typical forensic analysis with eight commonly available steganographic programs. Future work will attempt to automate the typical types of analysis and detection. This is important, as currently there is a steep rise in the use of image LSB steganographic techniques to hide the payload code used by malware and viruses, and for the purposes of data exfiltration. This results because of the fact that the hidden code and/or data can more easily bypass virus and malware signature detection in such a manner as being surreptitiously hidden in an otherwise innocuous image file

Identification of LSB image Steganography using Cover Image Comparisons

Steganography has long been used to counter forensic investigation. This use of steganography as an anti-forensics technique is becoming more widespread. This requires forensic examiners to have additional tools to more effectively detect steganography. In this paper we introduce a new software concept specifically designed to allow the digital forensics professional to clearly identify and attribute instances of LSB image steganography by using the original cover image in side-by-side comparison with a suspected steganographic payload image. This technique is embodied in a software implementation named CounterSteg. The CounterSteg software allows detailed analysis and comparison of both the original cover image and any modified image, using sophisticated bit- and color-channel visual depiction graphics. In certain cases, the steganographic software used for message transmission can be identified by the forensic analysis of LSB and other changes in the payload image. This paper demonstrates usage and typical forensic analysis with eight commonly available steganographic programs. Future work will attempt to automate the typical types of analysis and detection. This is important, as currently there is a steep rise in the use of image LSB steganographic techniques to hide the payload code used by malware and viruses, and for the purposes of data exfiltration. This results because of the fact that the hidden code and/or data can more easily bypass virus and malware signature detection in such a manner as being surreptitiously hidden in an otherwise innocuous image file