Z2Z4-Additive Perdect Codes in Steganography

Steganography is an information hiding application which aims to hide secret data imperceptibly into a cover object. In this paper, we describe a novel coding method based on Z2Z4-additive codes in which data is embedded by distorting each cover symbol by one unit at most (+-1-steganography). This method is optimal and solves the problem encountered by the most e cient methods known today, concerning the treatment of boundary values. The performance of this new technique is compared with that of the mentioned methods and with the well-known rate-distortion upper bound to conclude that a higher payload can be obtained for a given distortion by using the proposed method

Advances in Syndrome Coding based on Stochastic and Deterministic Matrices for Steganography

Steganographie ist die Kunst der vertraulichen Kommunikation. Anders als in der Kryptographie, wo der Austausch vertraulicher Daten für Dritte offensichtlich ist, werden die vertraulichen Daten in einem steganographischen System in andere, unauffällige Coverdaten (z.B. Bilder) eingebettet und so an den Empfänger übertragen. Ziel eines steganographischen Algorithmus ist es, die Coverdaten nur geringfügig zu ändern, um deren statistische Merkmale zu erhalten, und möglichst in unauffälligen Teilen des Covers einzubetten. Um dieses Ziel zu erreichen, werden verschiedene Ansätze der so genannten minimum-embedding-impact Steganographie basierend auf Syndromkodierung vorgestellt. Es wird dabei zwischen Ansätzen basierend auf stochastischen und auf deterministischen Matrizen unterschieden. Anschließend werden die Algorithmen bewertet, um Vorteile der Anwendung von Syndromkodierung herauszustellen

LizarMong: Excellent Key Encapsulation Mechanism based on RLWE and RLWR

The RLWE family algorithms submitted to the NIST post-quantum cryptography standardization process have each merit in terms of security, correctness, performance, and bandwidth. However, there is no splendid algorithm in all respects. Besides, various recent studies have been published that affect security and correctness, such as side-channel attacks and error dependencies. To date, though, no algorithm has fully considered all the aspects. We propose a novel Key Encapsulation Mechanism scheme called LizarMong, which is based on RLizard. LizarMong combines the merit of each algorithm and state-of-the-art studies. As a result, it achieves up to 85% smaller bandwidth and 3.3 times faster performance compared to RLizard. Compared to the NIST\u27s candidate algorithms with a similar security, the bandwidth is about 5-42% smaller, and the performance is about 1.2-4.1 times faster. Also, our scheme resists the known side-channel attacks