بهبود امنیت روش پنهان‌نگاری LSBM با استفاده از الگوریتم ژنتیک، چندکلیدی و بلاک‌بندی
محورهای موضوعی : مهندسی برق و کامپیوتروجیهه ثابتی 1 * , سپیده فیاضی 2 , حدیثه شیرین خواه 3
1 - دانشگاه الزهرا
2 - دانشگاه الزهرا
3 - دانشگاه الزهرا
کلید واژه: الگوریتم ژنتیکپنهان‌شکنیپنهان‌نگاریروش LSBM,
چکیده مقاله :
با افزایش دقت حملات پنهان‌شکنی در کشف روش‌های پنهان‌نگاری، نیاز به بهبود امنیت روش‌های پنهان‌نگاری بیشتر از گذشته احساس می‌شود. LSBM یکی از روش‌های ساده پنهان‌نگاری است که حملات نسبتاً موفقی برای کشف آن تا به حال ارائه شده است. هدف اصلی در این مقاله ارائه روشی برای بهبود LSBM است. انتخاب دنباله پیکسل‌ها برای جاسازی و چگونگی تغییر مقدار آنها در روش‌های مبتنی بر LSBM متفاوت هستند. در اغلب روش‌های موجود بعضی از این تصمیمات به صورت تصادفی گرفته می‌شود. در روش پیشنهادی در این مقاله، در مرحله اول از ایده چندکلیدی و در مرحله دوم از الگوریتم ژنتیک استفاده شده است تا تصمیمات بهتری اتخاذ شود. در روش پیشنهادی با عنوان MKGM، تصویر پوشش بلاک‌بندی شده و برای هر بلاک با چند کلید مختلف روش GLSBM اجرا می‌شود و در انتها بلاکی که کمترین تغییر هیستوگرام را نسبت به بلاک اولیه داشته باشد، در تصویر استگو قرار می‌گیرد. روش GLSBM، همان روش LSBM است با این تفاوت که برای تصمیم‌گیری در مورد افزایش یا کاهش پیکسل‌های غیر مطابق، از الگوریتم ژنتیک استفاده می‌شود. مقایسه معیارهای کیفیت تصویر و دقت حملات در کشف روش پیشنهادی، نشان‌دهنده بهبود این معیارها در مقایسه با روش LSBM اصلی است.
By increasing the precision of steganalysis attacks in discovering methods of steganography, the need to improve the security of steganographic methods is felt more than ever. The LSBM is one of the simplest methods of steganography, which have been proposed relatively successful attacks for its discovery. The main purpose of this paper is to provide a method for improving security of LSBM. The choice of the sequence of pixels to embed and how to modify them varies in LSBM-based methods. In most existing methods some of these decisions are made at random. In the proposed method in this paper, a multi-key idea in the first step and a genetic algorithm in the second step are used to make better decisions. In the proposed method, as MKGM, the image is blocked and GLSBM is executed for each block with different keys and finally the block with the least histogram change compared to the original block is included in the stego image. The GLSBM method is the same as the LSBM method except that the genetic algorithm is used to decide whether to increase or decrease non-matching pixels. Comparison of the image quality criteria and the accuracy of the attacks in the detection of the proposed method show that these criteria are improved compared to the original LSBM method.
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