# A False Negative Study of the Steganalysis Tool Stegdetect
## 6 Conclusions  
The main purpose of steganography is to hide secret data during communication to avoid intruders from discovering the hidden message within the stego image without the right permission. Meanwhile, [29] stated that steganalysis is not as straight forward as steganography, this is a disadvantage to the forensic analyst who will be trying to detect hidden data in stego images. However, in steganalysis, only a few can automatically analyse a bulk of stego images at the same. To check the accuracy of a steganalysis tool which will help forensic analyst, our research exam the false negative rate of Stegdetect one of the popular steganalysis tools in the market. In our experimental results, we observed that when the sensitivity values were sets between (0.3 and 0.7) for all the various image databases jphide started to be detected. It could be concluded that the different sensitivity value range affects the detection rate for this method (jphide). The main purpose of the study was about the false negative rate of the tool, we concluded that the tool has a high false negative rate, especially between (0.1 and 3.4) sensitivity. We recommend that the best sensitivity value for detection of jphide method should be 6.2. This detection sensitivity value is very important for the forensic analyst. Because the false negative ratio had a deep sharp fall from this point onwards. However, we recommended that forensic analyst using stegdetect need to take into consideration the sensitivity values with the high false negative value when analysing a huge bulk of images. Moreover, based on our analysis of the tool, we observed and proposed a reference point of the sensitivity value with its related quantified false negative rate based on the mean of all the various image databases. Overall, the mean proposed can act as a baseline which will help the forensic analyst in making a much better decision during their investigation proceedings. However, based on the mean of all the false negatives of the tool, it is also argued that it has a high probability of false negative ratio between 0 and 10% even if the sensitive value is set beyond our recommended. In conclusion, the fight between steganalysis methods and steganographic methods will ever continue. As more sophisticated steganographic algorithms are developed every day, a more powerful and sophisticated universals algorithms will also be required in detecting these steganography methods. This will be a more challenging but exciting research area in the near future. Currently, most steganalysis tools are very good in detecting specific steganographic methods. Example, Stegdetect which is an automated steganalysis tool is very good and effective in detecting content hidden in JPEG image formats than any other image format like Tiff, PNG and Gif. However, it is also more effective in detecting specific steganographic methods such as jphide, F5, invisible secret, jsteg and outguess than any other steganographic method. In this view, a future research should be conducted to consider a universal steganalysis tool. With current advancement in technologies for secure communication and its issues of privacy for individual users, a further research need to be considered to find the effect steganalysis tools will have on security protocols. Additionally, we also plan to conduct a more complete comparative study of the available steganalysis tools, in order to obtain a more general understanding of what can be achieved and the degree of accuracy. [PERSON] contributed through the outlining of the idea underlying the paper and the implementation of the analysis of the tool. [PERSON] contributed through applying the methodology and writing--the original draft. [PERSON] made a contribution through writing--reviewing and editing and supervising. [PERSON]-[PERSON] contributed through administrating the project and supporting resources. All authors have read and agreed to the published version of the manuscript. This work was supported by the 2020 Research Fund of University of Ulsan.