Hassan Dana-Mazraeh

With the popularity of smartphones and widespread use of high-speed Internet, social media has become a vital part of people's daily life. Currently, text messages are used in many applications, such as mobile chatting, mobile banking, and mobile commerce. However, when we send a text message via short message service (SMS) or social media, the information contained in the text message transmits as a plain text, which exposes it to attacks. In some cases, this information may be confidential, such as banking credentials, secret missions, and confidential appointments; moreover, it is a major drawback to send such information via SMS or social media, as neither provides security before transmission. In this paper, we propose a novel text steganography technique called AITSteg, which provides end-to-end security during the transmission of text messages via SMS or social media between end users. The AITSteg technique is evaluated by considering a trusted scenario. We then evaluate the efficiency of the proposed technique in terms of embedding capacity, invisibility, robustness, and security. The experiments confirm that the AITSteg is able to prevent various attacks, including man-in-the-middle attacks, message disclosure, and manipulation by readers. Moreover, we compare the experimental results with the existing techniques to show the superiority of the proposed technique. To the best of our knowledge, this is the first text steganography technique that provides end-to-end secure transmission of the text message using symmetric keys via social media. © 2013 IEEE. 

This paper studies the nonlinear optimization problems subject to bipolar max-min fuzzy relation equation constraints. The feasible solution set of the problems is non-convex, in a general case. Therefore, conventional nonlinear optimization methods cannot be ideal for resolution of such problems. Hence, a Genetic Algorithm (GA) is proposed to find their optimal solution. This algorithm uses the structure of the feasible domain of the problems and lower and upper bound of the feasible solution set to choose the initial population. The GA employs two different crossover operations: 1-N-points crossover and 2-Arithmetic crossover. We run the GA with two crossover operations for some test problems and compare their results and performance to each other. Also, their results are compared with the results of other authors’ works. © 2018, University of Sistan and Baluchestan. All rights reserved. 

Embedding a hidden stream of bits in a cover file to prevent illegal use is called digital watermarking. The cover file could be a text, image, video, or audio. In this study, we propose invisible watermarking based on the text included in a webpage. Watermarks are based on predefined structural and syntactic rules, which are encrypted and then converted into zero-width control characters using binary model classification before embedding into a webpage. This concept means that HTML (Hyper Text Markup Language) is used as a cover file to embed the hashed and transparent zero-width watermarks. We have implemented the proposed invisible watermarking against various attacks to reach optimum robustness. © 2016 Taylor & Francis. 

In this paper a numerical approach combining the least squares method and the genetic algorithm (sequential and multi-core parallelization approach) is proposed for the determination of temperature in an inverse heat conduction problem (IHCP). Some numerical experiments confirm the utility of this algorithm as the results are in good agreement with the exact data. Results show that an excellent estimation can be obtained by implementation sequential genetic algorithm within a CPU with clock speed 2.7. GHz, and parallel genetic algorithm within a 16-core CPU with clock speed 2.7. GHz for each core. © 2013 Elsevier Inc. 

In this paper, a numerical approach combining the use of the least squares method and the genetic algorithm (sequential and multi-core parallelisation approach) is proposed for the determination of temperature in an inverse hyperbolic heat conduction problem (IHHCP). Some numerical experiments confirm the utility of this algorithm as the results are in good agreement with the exact data. Results show that an excellent estimation can be obtained by implementation sequential genetic algorithm within a CPU with clock speed 2.4 GHz, and parallel genetic algorithm within a 16-core CPU with clock speed 2.4 GHz for each core. © 2013 Inderscience Enterprises Ltd.