Watermarking technology is a feasible approach to prevent copyright infringement. The practicality of the watermark itself affects the acceptance and penetration of relevant applications. In this study, a dual-mode FFT-based audio watermarking framework is devised to achieve both binary and numeric data hiding concurrently using respective modulations. We demonstrate: (1) the adaptive magnitude modulation (AMM) applied to large-magnitude FFT coefficients is competent to deliver efficient and effective binary watermarking at a rate of 678.46 bits per second; (2) the phase modulation (PM) in charge of the embedding of pixel values directly into medium-size FFT coefficients can operate at a rate of 508.85 numbers per second. With a tactical selection of embedding positions and strengths, both the FFT-based AMM and PM exhibit exceptional robustness against commonly encountered attacks. According to the perceptual evaluation of audio quality (PEAQ) metric, the resulting audio quality remains indistinguishable from the original audio, even at the aforementioned high payload capacity.

Stream ciphers are a type of symmetric encryption algorithm, and excel in speed and efficiency compared with block ciphers. They are applied in various applications, particularly in digital communications and real-time transmissions. In this paper, we propose lightweight chaotic keystream generators that utilize original one-dimensional (1D) chaotic maps with a counter to fit the requirement of a stream cipher for secure communications in the Internet of Things (IoT). The proposed chaotic scheme, referred to as expanded chaos, improves the limit of the chaotic range for the original 1D chaos. It can resist brute-force attacks, chosen-ciphertext attacks, guess-and-determine attacks, and other known attacks. We implement the proposed scheme on the IoT platform Raspberry Pi. Under NIST SP800-22 tests, the pass rates for the proposed improved chaotic maps with a counter and the proposed the mutual-coupled chaos are found to be at least about 90% and 92%, respectively.

With the rapid development of the Internet and wireless communications, as well as the popularization of personal communication systems, the security of real-time communications is demanded. The efficient technology of stream ciphers can satisfy this requirement of security. In this paper, to enhance the security strength of stream ciphers, we design a key-based multi-mode clock-controlled stream cipher for real-time secure communications of the Internet of things (IoT). The proposed stream cipher is equipped with a multi-mode depending on the key. The different working modes are shipped with different encrypting circuits depending on the user’s key. We analyze the period, the linear complexity, and use known attacks to verify the security strength of the proposed cipher. Compared with existing dual mode clock-controlled stream ciphers, the merits of our proposed cipher are its long period, high linear complexity, low hardware complex, low initialization clock, and simplicity in mode switching. Furthermore, the proposed cipher passes the FIPS PUB 140-1 and SP800-22 tests, obtaining at least 97.00%.

A secure data stream is important for the real time communications of Internet of Things (IoT). A stream cipher with the characteristics of simple and high speed is suitable in the secure communications of IoT for its security. Some stream ciphers based on coupled map lattices (CML) were proposed. However, the original coupled map lattice shows evidence of correlation between the contiguous points. In this paper, we present an improved CML with a counter to overcome the weakness. The proposed scheme has the advantage of simplicity and suits the resource constrained IoT environment. We implement the proposed improved CML and analyze the proposed ciphers against some attacks. For the balance performance analysis, the numbers of 0 and 1 in the keystream are almost balanced, and the difference rates show that the proposed schemes have high key sensitivity. Finally, we present some experimental results of statistical random number tests for the output keystreams. Under the pass rates of the statistical test of NIST SP800-22, the proposed ciphers with improved CML, and compound CML are at least 95% and 97%, respectively. All the pass rates of the proposed stream ciphers are 100% for the statistical test of FIPS PUB 140-1.

This paper presents a novel approach for directly hiding the pixel values of a small color watermark in a carrier color image. Watermark embedding is achieved by modulating the gap of paired coefficient magnitudes in the discrete cosine transform domain according to the intended pixel value, and watermark extraction is the process of regaining and regulating the gap distance back to the intensity value. In a comparison study of robustness against commonly encountered attacks, the proposed scheme outperformed seven watermarking schemes in terms of zero-normalized cross-correlation (ZNCC). To render a better visual rendition of the recovered color watermark, a generative adversarial network (GAN) was introduced to perform image denoising and super-resolution reconstruction. Except for JPEG compression attacks, the proposed scheme generally resulted in ZNCCs higher than 0.65. The employed GAN contributed to a noticeable improvement in perceptual quality, which is also manifested as high-level ZNCCs of no less than 0.78.