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Top1. Introduction
Watermarking in digital images is becoming an essential tool for claiming responsibility regulations as well as the traditional ownership authentication proofing (Gutub et al., 2007). This security tool is vital for today e-applications in order to ensure trust preserving acceptable secure utilization. Some researchers enhance this authentication by involving cryptography as sophisticated trust approaches (Rodríguez et al., 2019) while others adopt steganography, watermarking, or data hiding (Al-Asadi & Hadi-Ali, 2015) aiming to provide relevant efficient and acceptable authentication security (Almutairi et al., 2019). Lately, as IoT and Ad-hoc networks autonomous involvement is getting more into daily usages (Khari et al., 2016), mobile nodes configuration is requesting optimization effectiveness removing previous centralized complex controlling (Khari, 2012) starving for lightweight security innovative approaches (Khari et al., 2013). With this efficiency prospective, watermarking can be tuned as efficient judging evidence, assisting verification whenever claiming denial of authorization problem is raised, which is an opposite usage to conventional copyright protection, i.e. of enforcing permission for legal utilization (Gutub et al., 2010).
Data hiding for the purpose of information authentication or security involve several areas linking different methods to serve current applications of electronic media files (Hassan & Gutub, 2021a). Authentication of the IT services ensuring exchanged trusted data is the main concern in almost all IoT-applications in effective mode (Almulhim et al., 2019). Therefore, many investigations have been directed toward lightweight secure authentication addressing challenges for optimization from different aspects (Khari et al., 2016). For example, Dixit et al. (2014) presented a lossless semi fragile information protection in images that inspired our research lightweight watermarking objective, but using counting-based secret sharing. Relatively, Almulhim and Zaman (2018) presented an energy efficiency security authentication schemes in IoT using elliptic curve cryptography for lightweight protection against multiple impersonation attacks, man in the middle attack and unknown key sharing attacks, dedicated for IoT E-health systems. Wadhwa and Khari (2011) criticized standard systems by highlighting several security vulnerabilities to the features needing out of the box well-organized lightweight security schemes.
Al-Roithy and Gutub (2021) presented enhancing security via practical randomization prioritization. They improved their work building upon the trustworthy approach of involving stream of random digits presented in their basic privacy associated study (Al-Roithy & Gutub, 2020) as found in most similar standard watermarking, i.e. utilizing machine randomization for stream watermarking. This data hiding is different than reversible hiding work (Hassan & Gutub, 2021b) that cannot be utilized for ownership watermarking. These security hiding processes are found in combination to cryptography for fulfilling privacy critical situations such as medical 1-LSB and 2-LSB combinations (Bin-Hureib & Gutub, 2020).
In general, watermarking newly innovative benefits and applications can be classified as enhancements of these two main categorizations. It is claiming responsibility and proof of ownership, such as, owner identification, transaction tracking, broadcast monitoring, usage control, authentication and tamper proofing, persistent item identification, and enhancement of legacy systems (Almazrooie et al., 2020). Watermarking can be further classified based on its appearance within the image media-files in visible and invisible types applying some steganography data hiding strategies showing clear technical similarities. In fact, the main difference between watermarking and steganography is in its gearing of objective toward security authentication and integrity instead of confidentiality, as main stego intention (Gutub et al., 2010).