## 4 Results and Discussions
### Comparison of CIAA-RepDroid to SERS and Google Play Rating
\begin{table}
\begin{tabular}{c c c c c c c c c c c c} \hline \hline  & & \multicolumn{3}{c}{**Our Scheme**} & \multicolumn{3}{c}{**SERS**} & \multicolumn{3}{c}{**Google**} & \multicolumn{3}{c}{**Gaps**} \\ \hline \multirow{2}{*}{**App Id**} & \# Total & **\# Security** & **Global Reputation** & **Rating Based** & **Rating Based Static** & **Global** & **Traditional** & **Gap** & **Gap** & **Gap** & **Gap** \\  & **Reviews** & **Reviews** & **(R1)** & **Reviews** & **(R2)** & **Analysis (R3)** & **Rating (R4)** & **Rating (R5)** & **R1-R2** & **R1-R3** & **R1-R4** & **R1-R5** \\ \hline
1 & 2573 & 21 & 1.9 & 4.09 & 4.22 & 3.66 & 4.1 & 2.19 & 2.32 & 1.76 & 2.2 \\
2 & 2586 & 5 & 2.2 & 4.44 & 3.98 & 3.95 & 4.6 & 2.24 & 1.78 & 1.75 & 2.4 \\
3 & 2590 & 52 & 1.7 & 4.21 & 4.08 & 3.82 & 4.5 & 2.51 & 2.38 & 2.12 & 2.8 \\
4 & 2567 & 41 & 1.6 & 4.23 & 4.46 & 3.86 & 4.5 & 2.63 & 2.86 & 2.26 & 2.9 \\
5 & 2598 & 28 & 1.6 & 4.37 & 4.92 & 4.46 & 4.5 & 2.77 & 3.32 & 2.86 & 2.9 \\
6 & 2586 & 62 & 1.6 & 2.81 & 4.51 & 3.43 & 4.3 & 1.21 & 2.91 & 1.83 & 2.7 \\
7 & 2566 & 24 & 1.8 & 4.22 & 4.37 & 3.95 & 4.1 & 2.42 & 2.57 & 21.5 & 2.3 \\
8 & 2546 & 22 & 1.6 & 4.32 & 2.81 & 4.52 & 4.4 & 2.72 & 1.21 & 2.92 & 2.8 \\
9 & 2578 & 37 & 1.6 & 3.79 & 4.22 & 2.51 & 4 & 2.19 & 2.62 & 0.91 & 2.4 \\
10 & 2580 & 40 & 1.7 & 3.61 & 4.32 & 4.25 & 4.1 & 1.91 & 2.62 & 2.55 & 2.4 \\
11 & 2572 & 54 & 1.6 & 4.27 & 3.79 & 4.19 & 4.6 & 2.67 & 2.19 & 2.59 & 3 \\
12 & 2598 & 43 & 1.7 & 3.91 & 3.61 & 3.44 & 4.6 & 2.21 & 1.91 & 1.74 & 2.9 \\
13 & 2500 & 42 & 1.6 & 3.51 & 4.27 & 3.29 & 4.2 & 1.91 & 2.67 & 1.69 & 2.6 \\
14 & 2598 & 43 & 1.7 & 2.79 & 3.91 & 3.89 & 4.2 & 1.09 & 2.21 & 2.19 & 2.5 \\
15 & 2552 & 65 & 1.7 & 3.32 & 3.51 & 2.55 & 4.1 & 1.62 & 1.81 & 0.85 & 2.4 \\ Average & 2573 & 39 & 1.70 & 3.85 & 4.06 & 3.71 & 4 & 2.15 & 2.35 & 2.01 & 2.61 \\ \hline \hline \end{tabular}
\end{table} 
Table 8: Results about reputation and rating with gaps. Now that we showed the completeness of what we propose against SERS reviews analysis, we come to compare to the second SERS rating. Since it relies on app features to detect data leaks (R3), we think that this rating is the more appropriate to compare with. Again, a distance exists between, R1 and R3. Unfortunately, the gap existing between R1 and R3 means that SERS's second rating is not really expressive in terms of security. The average value in R3 is 4.06 which mean that applications do not leak any data by the use of risky permissions. This result is false since App ID #2 deals with a dangerous permission access (such as \(READ\_PHONE\_STATE\)). Our reputation expresses more reliably this situation. From Table 9, we note some more important points concerning our proposal. The first is that app 2 has the highest reputation in terms of security and the same has the highest reputation in terms of functional aspect. This coincidence has a sense. In fact, it means that authors of this app made a lot of effort to strengthen it against security flaws. Indeed, only five security reviews are stated among 2586 reviews. This application happens to be considered as the more secure since few users confront security problems. The second is that the app 9 has the lowest reputation in terms of security and the lowest reputation in terms of functional aspect. This result simply means that users note through their 37 security reviews that this app has severe security pitfalls and users do not really recommend this app. The number of users put the Google rate to 4 since Google aggregates all the rates. Table 9 shows the five reviews which relate security from our scheme. Effectively, they stipulate hacking, phishing via terms such as fake and denial of service through terms such as crash. Unlike SERS and Google that finally express functional aspects, we are able to see that developers miss to look at these aspects and customers suffer from consequences. Although our scheme reveals CIAA flaws, improvements should be made to indicate type of vulnerability or threat based on semantics and ontology in words.