# Secure Image Transmission Using Multilevel Chaotic Encryption and Video Steganography
## 2 Related Works  
One of the most crucial multimedia security challenges is ensuring secure image transmission in video-based systems. Researchers have proposed numerous steganographic and encryption methods to solve this problem; each has unique benefits and drawbacks. In particular, they have extensively researched steganography to insert private information covertly into digital media. The basic ideas and techniques of steganography were thoroughly examined by [PERSON] (2009), who also described its security implications and uses [15]. Furthermore, [PERSON] et al. (2014) investigated digital watermarking methods and how they might improve multimedia security [16]. These works outlined the fundamental theories underlying contemporary steganographic techniques. However, traditional methods remain susceptible to detection, even with advancements in steganalysis. Despite efforts to improve steganographic techniques, popular methods such as LSB remain vulnerable to graph-based statistical attacks, machine learning-based techniques, and modern attacks such as regular and singular groups analysis (RS) [17]. Recent studies have confirmed that attackers can still detect steganographic information with high accuracy using these techniques [16]. This highlights the need for more robust hybrid security systems. This section delineates the research gaps that this study intends to fill by examining recent developments in encryption and steganography while highlighting their respective advantages and disadvantages. In 2024, a chaos theory-based steganography method for embedding sensitive medical data into images. This approach uses chaotic sequences to determine the embedding positions in the cover image, which enhances the unpredictability and durability of the hidden information. A combination of a linear-feedback shift register (LFSR) and Rabin cryptography is also used to secure the embedded data further. The experimental results showed that this method effectively hides the secret data without noticeable alterations to the cover image. The use of chaos theory makes the embedding patterns difficult to predict, providing enhanced security against various attacks [3]. This research explores multiple chaos-based systems for medical image steganography. However, its methodology is limited to image-based security. In contrast, our study enhances multimedia transmission capacity and bolsters security by applying this approach to video steganography. In 2025, a steganographic method was proposed that hides sensitive information in digital images using an optimized pixel selection process. The technique ensures that the hidden data is imperceptible to the human eye by leveraging advanced embedding strategies. The experimental results demonstrated that the proposed method successfully hides information with minimal impact on image quality. The method also strongly resists steganalysis techniques, making it a reliable option for secure data embedding [4]. This study proposes the LSB technique for achieving high PSNRs in image steganography. Nonetheless, it does not explore video-based steganography, which has the potential to improve security and resilience against attacks. Our research aims to fill this void by introducing a multilevel chaotic scheme to encrypt video frames. In 2024, a three-layer video steganography method was proposed that achieves high security using chaotic dynamic systems. The technique employs a chaotic key generator that combines logistic and sine maps to generate sensitive initial seeds for secure embedding in video frames. The system allows adaptive control of the embedding capacity, maintaining a hiding ratio between 7.1% and 28.125%. The experimental results showed that the method achieved high peak signal-to-noise ratios (PSNRs) ranging from 50.25 to 62.05 dB, yielding minimal video quality degradation and maintaining high security [18]. This study introduces a three-layer protected adaptive video steganography technique.