Biblio

This paper explores using chaos-based cryptography for transmitting multimedia data, mainly speech and voice messages, over public communication channels, such as the internet. The secret message to be transmitted is first converted into a one-dimensional time series, that can be cast in a digital/binary format. The main feature of the proposed technique is mapping the two levels of every corresponding bit of the time series into different multiple chaotic orbits, using a simple encryption function. This one-to-many mapping robustifies the encryption technique and makes it resilient to crypto-analysis methods that rely on associating the energy level of the signal into two binary levels, using return map attacks. A chaotic nonautonomous Duffing oscillator is chosen to implement the suggested technique, using three different parameters that are assumed unknown at the receiver side. Synchronization between the transmitter and the receiver and reconstructing the secret message, at the receiver side, is done using a Lyapunov-based adaptive technique. Achieving stable operation, tuning the required control gains, as well as effective utilization of the bandwidth of the public communication channel are investigated. Two different case studies are presented; the first one deals with text that can be expressed as 8-bit ASCII code, while the second one corresponds to an analog acoustic signal that corresponds to the voice associated with pronouncing a short sentence. Advantages and limitation of the proposed technique are highlighted, while suggesting extensions to other multimedia signals, along with their required additional computational effort.

With the development of artificial intelligence (AI), multimedia privacy issues have become more challenging than ever. AI-assisted malicious entities can steal private information from multimedia data more easily than humans. Traditional multimedia privacy protection only considers the situation when humans are the adversaries, therefore they are ineffective against AI-assisted attackers. In this paper, we develop a new framework and new algorithms that can protect image privacy from both humans and AI. We combine the idea of adversarial image perturbation which is effective against AI and the obfuscation technique for human adversaries. Experiments show that our proposed methods work well for all types of attackers.

This paper explores using chaos-based cryptography for transmitting multimedia data, mainly speech and voice messages, over public communication channels, such as the internet. The secret message to be transmitted is first converted into a one-dimensional time series, that can be cast in a digital/binary format. The main feature of the proposed technique is mapping the two levels of every corresponding bit of the time series into different multiple chaotic orbits, using a simple encryption function. This one-to-many mapping robustifies the encryption technique and makes it resilient to crypto-analysis methods that rely on associating the energy level of the signal into two binary levels, using return map attacks. A chaotic nonautonomous Duffing oscillator is chosen to implement the suggested technique, using three different parameters that are assumed unknown at the receiver side. Synchronization between the transmitter and the receiver and reconstructing the secret message, at the receiver side, is done using a Lyapunov-based adaptive technique. Achieving stable operation, tuning the required control gains, as well as effective utilization of the bandwidth of the public communication channel are investigated. Two different case studies are presented; the first one deals with text that can be expressed as 8-bit ASCII code, while the second one corresponds to an analog acoustic signal that corresponds to the voice associated with pronouncing a short sentence. Advantages and limitation of the proposed technique are highlighted, while suggesting extensions to other multimedia signals, along with their required additional computational effort.

The frequency of power distribution networks in a power grid is called electrical network frequency (ENF). Because it provides the spatio-temporal changes of the power grid in a particular location, ENF is used in many application domains including the prediction of grid instability and blackouts, detection of system breakup, and even digital forensics. In order to build high performing applications and systems, it is necessary to capture a large-scale nationwide or worldwide ENF map. Consequently, many studies have been conducted on the distribution of specialized physical devices that capture the ENF signals. However, this approach is not practical because it requires significant effort from design to setup, moreover, it has a limitation in its efficiency to monitor and stably retain the collection equipment distributed throughout the world. Furthermore, this approach requires a significant budget. In this paper, we proposed a novel approach to constructing the worldwide ENF map by analyzing streaming data obtained by online multimedia services, such as "Youtube", "Earthcam", and "Ustream" instead of expensive specialized hardware. However, extracting accurate ENF from the streaming data is not a straightforward process because multimedia has its own noise and uncertainty. By applying several signal processing techniques, we can reduce noise and uncertainty, and improve the quality of the restored ENF. For the evaluation of this process, we compared the performance between the ENF signals restored by our proposed approach and collected by the frequency disturbance recorder (FDR) from FNET/GridEye. The experimental results show that our proposed approach outperforms in stable acquisition and management of the ENF signals compared to the conventional approach.

In recent years, more and more multimedia data are generated and transmitted in various fields. So, many encryption methods for multimedia content have been put forward to satisfy various applications. However, there are still some open issues. Each encryption method has its advantages and drawbacks. Our main goal is expected to provide a solution for multimedia encryption which satisfies the target application constraints and performs metrics of the encryption algorithm. The Advanced Encryption Standard (AES) is the most popular algorithm used in symmetric key cryptography. Furthermore, chaotic encryption is a new research direction of cryptography which is characterized by high initial-value sensitivity and good randomness. In this paper we propose a hybrid video cryptosystem which combines two encryption techniques. The proposed cryptosystem realizes the video encryption through the chaos and AES in CTR mode. Experimental results and security analysis demonstrate that this cryptosystem is highly efficient and a robust system for video encryption.

A novel secure arithmetic image coding algorithm based on Two-dimensional Generalized Logistic Mapping is proposed. Firstly, according to the digital image size m×n, two 2D chaotic sequences are generated by logistic chaotic mapping. Then, the original image data is scrambled by sorting the chaotic sequence. Secondly, the chaotic sequence is optimized to generate key stream which is used to mask the image data. Finally, to generate the final output, the coding interval order is controlled by the chaotic sequence during the arithmetic coding process. Experiment results show the proposed secure algorithm has good robustness and can be applied in the arithmetic coder for multimedia such as video and audio with little loss of coding efficiency.