# A False Negative Study of the Steganalysis Tool Stegdetect
## 4 Results
During the analysis, stegdetect detect other steganographic methods in the images other than jphide which we used. Figure 3 below shows that 0.2% of the detection was for other algorithms between 0.3 and 0.7 sensitivity which stegdetect claims was used in embedding secret messages in those images. Meanwhile, the percentage of other algorithm detected increased to 0.4% between (1.5 and 10.0). Finally, the images from the database were already manipulated before jphide method was used to embed the messages. It is therefore possible that the images were manipulated using any of the algorithms detected during the analysis. Phase two of the analysis was focused on 500 Seam-carve untouched (clean) images from SAM Houston university image database which were embedded with a secret message using jphide. Compared to the detection results of the manipulated images, there was slight increase in the detection for the false negative ratio, skipped (false positive likely) and jphide (*) while other algorithms and jphide (**, ***) experience a slight decreased with different sensitivity as shown in Table 3 below. As show in Table 3 above, 67.78% of the overall detection was false negative which is very high. However, with an increase in sensitivity, the detection ratio for false negative, jphide and other algorithm all changed. Furthermore, as shown in Table 4 below, there was a significant increase in the confidence detection of steganographic method jphide with changes in sensitivity values. We observe slight changes in the detection between the manipulated and the untouched Seam-carving images. Detection of jphide in the untouched images embedded with bits of messages started with 0.5 sensitivity while detection for jphide in the manipulated images started with 0.7 sensitivity, after which there was a continuous increase in the confidence in detection of jphide method. Figure 3: Changes in other algorithms detected with different sensitivities. \begin{table}
\begin{tabular}{l l l l l l l} \hline \hline
**Sensitivity** & **False Negative** & **Likely False** & **jphide(*)** & **jphide(**)** & **jphide(***)** & **OTHER** \\
**Value** & & & **Positive (Skipped)** & & & **ALG** \\ \hline
0.1–10.0 & 67.78\% & 2.40\% & 11.91\% & 14.09\% & 3.62\% & 0.20\% \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Rate of sensitivity results from 500 seam-carve untouched images. The false negative results for untouched seam-carving images at the beginning were high 97.60% as shown in Figure 4 with 0.1 sensitivity value, this result is not different from the manipulated images, however there was slight decrease between 0.1 and 3.4, then there was massive fall in the false negative between 5.2 and 10.0 with increase in sensitivity value. The detection results for jphide (*, **, ***) between 0.5 and 3.4 was very marginal until the sensitivity was increased to 5.2 when jphide (*) had sharp increase meanwhile, with continuous increase in the sensitivity value between 7.3 and 10.0 the detection of jphide (*) experience a continuous decline, at the same time between 5.2 and 10.0 the level of confidence in detecting jphide (**) had a continuous increase while jphide (***) maintained its steady increase as shown in Figure 5 below. Figure 6 shows that there was no effect of the sensitivity between 0.1 and 0.7 on the results for other algorithm detected, then between 1.5 and 10.0 there was a minor increase in the detection of other algorithms by the tool. However, between 3.4 and 10.0 the tool (stegdetect) maintain a constant detection ratio for other algorithms.