# Effective and Efficient DDoS Attack Detection Using Deep Learning Algorithm, Multi-Layer Perceptron
## 2 Literature Review
\begin{table}
\begin{tabular}{l c c c c c c} \hline
**Paper** & **Year** & **Objective** & **Incremental Analysis** & **Assumptions Used** & **Relative Complexity** & **Real-Time Detection** \\ \hline
[14] & 2017 & Mitigation of multi-page HTTP DDoS attacks & No & No & High & No \\ \hline
[15] & 2016 & To determine suitability of Levy walk for DDoS detection & No & Yes & Medium & No \\ \hline
[16] & 2017 & DDoS attack detection & Yes & Yes & Medium & No \\ \hline
[17] & 2017 & To detect DDoS attacks & No & Yes & High & No \\ \hline
[18] & 2017 & DDoS attack detection & No & No & High & No \\ \hline
[19] & 2016 & Attack detection & No & Yes & High & No \\ \hline
[20] & 2016 & Router protection system & No & Yes & Medium & No \\ \hline
[21] & 2016 & DDoS attack detection & No & Yes & Medium & No \\ \hline
[22] & 2017 & Increases resilience to DDoS attacks & No & Yes & High & No \\ \hline
[23] & 2016 & Flexible DDoS attack identifier & No & Yes & High & No \\ \hline
[24] & 2016 & DDoS attack detection & No & No & High & No \\ \hline
[25] & 2017 & Diagnosis method of attack on DDoS applications & No & No & High & No \\ \hline
[26] & 2017 & Fast and timely location of a DDoS application over HTTP floods & No & No & Low & No \\ \hline
[27] & 2017 & Cloud-based firewall to reduce DDoS attacks & Yes & Yes & Medium & No \\ \hline
[28] & 2017 & To detect and prevent multiple DDoS TCP attack & No & No & High & No \\ \hline
[29] & 2017 & An event detection module & No & Yes & High & No \\ \hline
[30] & 2016 & Mine learning and DDoS base discovery & No & No & High & Yes \\ \hline
[31] & 2016 & Classification of DDoS threats & No & Yes & Medium & No \\ \hline
[32] & 2017 & DDoS attack mitigation & No & No & Medium & No \\ \hline
[33] & 2014 & Detection of AI-DDoS attacks & No & Yes & High & No \\ \hline
[34] & 2018 & Early identification of DDoS attacks and flash occurrences & No & Yes & Medium & No \\ \hline \end{tabular}
\end{table} 
Table 1: Summary of literature review on DDoS attack detection. \begin{table}
\begin{tabular}{c c c c c c c} \hline
**Paper** & **Year** & **Objective** & **Incremental Analysis** & **Assumptions Used** & **Relative Complexity** & **Real-Time Detection** \\ \hline
[35] & 2018 & Unique DDoS attack detection and prevention technique & No & Yes & High & No \\ \hline
[36] & 2018 & Mitigation of the effects of DDoS attacks & No & Yes & High & No \\ \hline
[37] & 2018 & Real-time blocking DDoS application & No & Yes & High & Yes \\ \hline
[38] & 2018 & To detect DDoS attacks & No & No & Medium & No \\ \hline
[39] & 2018 & DDoS attacks classification as active and inactive & No & No & Medium & No \\ \hline
[40] & 2018 & Model to identify DDoS attack and mitigation & No & No & High & No \\ \hline
[41] & 2018 & Developed a secure system & No & No & High & No \\ \hline
[42] & 2018 & Manage multiple datasets and also detect botnets in the network & No & No & High & No \\ \hline
[43] & 2018 & To prevent DDoS attacks & No & No & High & No \\ \hline
[44] & 2018 & Novel entropy-based symbols to help reliably detect DDoS attacks & No & Yes & Medium & No \\ \hline
[45] & 2018 & Network protection schemes against end-to-end network attacks & No & No & High & No \\ \hline
[46] & 2018 & Reduction method based on the fuzzy control system & No & Yes & Medium & No \\ \hline
[47] & 2018 & Novel selection algorithm & No & No & High & No \\ \hline
[48] & 2018 & Accuracy of attack detection rate and false alarm rate & Yes & No & High & No \\ \hline
[49] & 2018 & To mark a malicious packet to be forwarded from the attacker & Yes & No & Medium & No \\ \hline
[50] & 2018 & Graphical data framework to identify and mitigate DDoS attacks & No & No & High & No \\ \hline
[51] & 2018 & Automatically reests security apps about incoming traffic & No & No & High & No \\ \hline \end{tabular}
\end{table} 
Table 2: Summary of literature review on DDoS attack detection.