Acta Cybernetica <div id="main-content" class="region clearfix"> <div class="region region-content"> <div id="block-system-main" class="block block-system"> <div class="content"> <div id="node-30" class="node node-page clearfix"> <div class="content"> <div class="field field-name-body field-type-text-with-summary field-label-hidden"> <div class="field-items"> <div class="field-item even"> <p><img style="margin-left: 10px; margin-right: 10px; float: right; width: 203px; height: 291px;" src="" alt=""></p> <p><a title="SCImago Journal &amp; Country Rank" href=";tip=sid&amp;exact=no"><img style="margin-left: 10px; margin-right: 10px; float: right; width: 203px; height: 203px;" src="" alt=""> </a></p> <p>A scientific journal published by the <a href="">Institute of Informatics</a>, <a href="">University of Szeged</a>, <a href="">Szeged</a>, <a href="">Hungary</a>.</p> <p>Acta Cybernetica is abstracted by <a href="">Mathematical Reviews</a>, <a href="">Computing Reviews</a>, <a href="">Zentralblatt für Mathematik</a>&nbsp;and <a href=";picked=prox" target="_blank" rel="noopener">ACM Digital Library</a></p> <p>It is also indexed by <a href="">Scopus</a>,&nbsp;<a href="">DBLP</a>, EBSCO and Emerging Sources Citation Index (ESCI).</p> <p>&nbsp;&nbsp; <a href=";tip=sid&amp;clean=0"><img style="width: 100px; height: 100px;" src="/public/site/images/boglarka/esci-button.png"></a> &nbsp;&nbsp;</p> </div> </div> </div> </div> </div> </div> </div> </div> </div> University of Szeged, Institute of Informatics en-US Acta Cybernetica 0324-721X An Information Theoretic Image Steganalysis for LSB Steganography <p>Steganography hides the data within a media file in an imperceptible way. Steganalysis exposes steganography by using detection measures. Traditionally, Steganalysis revealed steganography by targeting perceptible and statistical properties which results in developing secure steganography schemes. In this work, we target LSB image steganography by using entropy and joint entropy metrics for steganalysis. First, the Embedded image is processed for feature extraction then analyzed by entropy and joint entropy with their corresponding original image. Second, SVM and Ensemble classifiers are trained according to the analysis results. The decision of classifiers discriminates cover image from stego image. This scheme is further applied on attacked stego image for checking detection reliability. Performance evaluation of proposed scheme is conducted over grayscale image datasets. We analyzed LSB embedded images by Comparing information gain from entropy and joint entropy metrics. Results conclude that entropy of the suspected image is more preserving than joint entropy. As before histogram attack, detection rate with entropy metric is 70% and 98% with joint entropy metric. However after an attack, entropy metric ends with 30% detection rate while joint entropy metric gives 93% detection rate. Therefore, joint entropy proves to be better steganalysis measure with 93% detection accuracy and less false alarms with varying hiding ratio.</p> Sonam Chhikara Rajeev Kumar Copyright (c) 2020-07-25 2020-07-25 24 4 593 612 10.14232/actacyb.279174 On the Steps of Emil Post: from Normal Systems to the Correspondence Decision Problem <pre style="-qt-block-indent: 0; text-indent: 0px; margin: 0px;">In 1946, Emil Leon Post (Bulletin of Amer. Math. Soc. 52 (1946), 264-268) introduced his famouscorrespondence decision problem, nowadays known as the Post Correspondence Problem (PCP).Post proved the undecidability of the PCP by areduction from his normal systems. In the presentarticle we follow the steps of Post, and give another, somewhat simpler and more straightforwardproof of the undecidability of the problem by using the same source of reductions as Post did.We investigate these, very different, techniques, and point out out some peculiarities in theapproach used by Post.</pre> Vesa Halava Tero Harju Copyright (c) 2020-07-25 2020-07-25 24 4 613 623 10.14232/actacyb.284625 Estimating the Dimension of the Subfield Subcodes of Hermitian Codes <p><span class="fontstyle0">In this paper, we study the behavior of the true dimension of the subfield subcodes of Hermitian codes. Our motivation is to use these classes of linear codes to improve the parameters of the McEliece cryptosystem, such<br>as key size and security level. The McEliece scheme is one of the promising alternative cryptographic schemes to the current public key schemes since in the last four decades, they resisted all known quantum computing attacks. By computing and analyzing a data collection of true dimensions of subfield subcodes, we concluded that they can be estimated by the extreme value distribution function.</span></p> Gábor Péter Nagy Sabira El Khalfaoui Copyright (c) 2020-07-25 2020-07-25 24 4 625 641 10.14232/actacyb.285453 Graph Coloring based Heuristic for Crew Rostering <pre>In the last years personnel cost became a huge factor in the financial management of many companies and institutions.The firms are obligated to employ their workers in accordance with the law prescribing labour rules. The companies can save costs with minimizing the differences between the real and the expected worktimes. Crew rostering is assigning the workers to the previously determined shifts, which has been widely studied in the literature. In this paper, a mathematical model of the problem is presented and a two-phase graph coloring method for the crew rostering problem is introduced. Our method has been tested on artificially generated and real life input data. The results of the new algorithm have been compared to the solutions of the integer programming model for moderate-sized problems instances.</pre> László Hajdu Attila Tóth Miklós Krész Copyright (c) 2020-08-19 2020-08-19 24 4 643 661 10.14232/actacyb.281106 Pixel Grouping of Digital Images for Reversible Data Hiding <p>Pixel Grouping (PG) of digital images has been a key consideration in recent development of the Reversible Data Hiding (RDH) schemes. While a PG kernel with&nbsp;neighborhood pixels helps compute image groups for better embedding rate-distortion&nbsp;performance, only horizontal neighborhood pixel group of size 1×3 has so far been&nbsp;considered. In this paper, we formulate PG kernels of sizes 3×1, 2×3 and 3×2 and&nbsp;investigate their effect on the rate-distortion performance of a prominent PG-based&nbsp;RDH scheme. Specially, a kernel of size 3×2 (or 2×3) that creates a pair of pixel-trios having triangular shape and offers a greater possible correlation among the pixels.&nbsp;This kernel thus can be better utilized for improving a PG-based RDH scheme. Considering this, we develop and present an improved PG-based RDH scheme and the&nbsp;computational models of its key processes. Experimental results demonstrated that our&nbsp;proposed RDH scheme offers reasonably better&nbsp; embedding rate-distortion performance&nbsp;than the original scheme.</p> Sultan Abdul Hasib Hussain Md Abu Nyeem Copyright (c) 2020-11-19 2020-11-19 24 4 663 678 10.14232/actacyb.277104 Semi Fragile Audio Crypto-Watermarking based on Sparse Sampling with Partially Decomposed Haar Matrix Structure <p>In the recent era the growth of technology is tremendous and at the same time, the misuse of technology is also increasing with an equal scale. Thus the owners have to protect the multimedia data from the malicious and piracy. This has led the researchers to the new era of cryptography and watermarking. In the traditional security algorithm for the audio, the algorithm is implemented on the digital data after the traditional analog to digital conversion. But in this article, we propose the crypto – watermarking algorithm based on sparse sampling to be implemented during the analog to digital conversion process only. The watermark is generated by exploiting the structure of HAAR transform. The performance of the algorithm is tested on various audio signals and the obtained SNR is greater than 30dB and the algorithm results in good robustness against various signal attacks such as echo addition, noise addition, reverberation etc.&nbsp;</p> Electa Alice Appadurai Mahabaleswara Ram Bhatt Geetha D.D. Copyright (c) 2020-11-19 2020-11-19 24 4 679 697 10.14232/actacyb.280899