@thesis{thesis,
		author={Deris  and DIMAS },
		title ={DETEKSI SERANGAN DENIAL OF SERVICE MENGGUNAKAN RULE BASED SIGNATURE ANALYSIS PADA JARINGAN INTERNET OF THINGS},
		year={2018},
		url={https://repository.unsri.ac.id/9947/},
		abstract={This research focus on pattern recognition of TCP FIN flood and zbassocflood/association flooding attacks on Internet of Things (IoT) network using rule based signature analysis method. The research was conducted on WiFi and IEEE 802.15.4 communication with normal traffic, attack traffic and combined normal ? attack traffic, fifteen different datasets were generated from these schemes, consisting of normal datasets, attack datasets and normal-attack datasets. The testing was performanced on two stages, there are : (i) testing with Snort Rules as Intrusion Detection System (IDS), and (ii) testing with rule based signature analysis method using Intrusion Detection Engine (IDE) naive string matching. In this research, the measurement of detection result using confusion matrix detection rate method bases on Snort IDS and Intrusion Detection Engine (IDE) naive string matching are presented. The Snort IDS shows that has average 17,7845% of TPR, 0,0266% FPR, 79,9734% TNR, 62,2155% for FNR and the detection accuracy is 26,3268%. While the Intrusion Detection Engine (IDE) using naive string matching that has average percentage 99,9131% of TPR, 0% FPR, 100% TNR, 0,0869% FNR and the detection accuracy is 99,9199%.}
		}