Digital forensics has become important due to the daily use of digital devices in our life, which may lead to evidence that can be useful to law enforcement in legal cases. When using cloud services, a lot of artifacts that might be useful for investigations are stored in the cloud which means that the extraction must be from cloud computers systems. So, the legacy forensics tools may not be usable or less effective due to the geographically distribution of data and legal issues among other issues. The challenges of the cloud digital forensics are discussed in this paper. Also, this paper shows the types of extracting data from cloud services that are offline and online extraction. The offline extraction is concerned with extracting data from a local device that used to access cloud services. While online data extraction is concerned with remote extraction of data from cloud services. A comparison between such two types are demonstrated from many ways according to the result of recent papers to show the situations that each type is useful in.

In this paper, we propose an efficient image hiding method that combines image encryption and chaotic mapping to introduce adaptive data hiding for improving the security and robustness of image data hiding in cover audio. The feasibility of using chaotic maps to hide encrypted image in the high frequency band of the audio is investigated. The proposed method was based on hiding the image data in the noisiest part of the audio, which is the high frequency band that was extracted by the zero crossing filter. Six types of digital images were used, each of size fit the length of used audio, this to facilitate the process of hiding them among the audio samples. The input image was encrypted by a one-time pad method, then its bits were hidden in the audio by the chaotic map. The process of retrieving the image from the audio was in the opposite way, where the image data was extracted from the high frequency band of the audio file, and then the extracted image was decrypted to produce the retrieved image. Four qualitative metrics were used to evaluate the hiding method in two paths: the first depends on comparing the retrieved image with the original image, while the second depends on comparing the audio containing the image data with the original audio once, and another time by comparing the cover audio with the original audio. The results of the quality metrics proved the efficiency of the proposed method, and it showed a slight and unnoticed effect between the research materials, which indicates the success of the hiding process and the validity of the research path.