EVALUASI PERBANDINGAN PERFORMA JARINGAN WIRELESS SENSOR NETWORK DALAM SERANGAN SYBIL ATTACK DAN HELLO FLOOD ATTACK

Perkembangan ilmu pengetahuan pada bidang teknologi jaringan terjadi sangat cepat karena mengikuti perkembangan kebutuhan manusia. Salah satu teknologi jaringan yang saat ini menarik perhatian masyarakat adalah teknologi Wireless Sensor Network(WSN). WSN adalah jaringan dari kumpulan sensor yang terhubung menggunakan teknologi wireless secara ad-hoc dan setiap sensor node digunakan untuk proses pengumpulan data dan menghubungkan dengan node yang lain melalui jaringan wireless.Karena pada kebanyakan kasus aplikasi WSN digunakan pada lingkungan yang ekstrem dan sensor node harus dapat beroperasi secara otomatis tanpa campur tangan manusia, jaringan ini menjadi rentan akan beberapa ancaman jaringan dan dapat mempengaruhi performa dari jaringannya. Terdapat berbagai macam jenis serangan yang dapat membahayakan jaringan wireless sensor network diantaranya yang paling umum adalah sybil attack dan hello flood attack. Dalam penelitian ini, penulis meneliti performa WSN saat diserang oleh Sybil attack dan hello flood attack dengan cara mengukur throughput, PDR(packet delivery ratio), jitter dan delay dalam jaringan WSN. Penelitian ini juga menganalisa jumlah node yang bervariasi dari 10 node sampai 30 node dengan waktu simulasi dari 10 detik sampai 30 detik lalu dianalisa jaringan ketika jaringan normal dan diserang oleh node penyerang yang bervariasi dari 1 sampai 3 penyerang. Dengan melakukan analisa tersebut, diperoleh data berupa perbandingan dampak serangan dari Sybil attack dan hello flood attack. Dampak dari sybil attack lebih berpengaruh pada parameter throughput dan pdr yang mengalami penurunan nilai hingga 69,9% untuk pdr dan 56,4% untuk throughput. Sedangkan dampak dari hello flood attack lebih berpengaruh pada parameter delay dan jitter yang mengalami kenaikandari nilai semula 0,05 detik menjadi 0,576 detikuntuk delay dan 0,579 detik untuk jitter.AbstractThe development of science in the field of network technology occurs very quickly because it follows the development of human needs. One of the network technology that is currently attracting public attention is wireless sensor network technology (WSN). WSN is a network of connected sensors using ad-hoc wireless technology and each node sensor are used to process data collection and connect with other nodes over a wireless network. Because in most cases WSN applications are used in extreme environments and node sensors must operate automatically without human intervention, these networks become vulnerable to some network threats and may affect the performance of their networks. There are various types of attacks that can harm wireless sensor network network among the most common is sybil attack and hello flood attack. In this study, authors examined the performance of WSN when attacked by Sybil attack and hello flood attack by measuring throughput, PDR (packet delivery ratio), jitter and delay in WSN network. This study also analyzed the number of nodes that varied from 10 nodes to 30 nodes with simulated time from 10 seconds to 30 seconds and then analyzed the network when the network was normal and attacked by the attacking nodes that varied from 1 to 3 attackers. By doing the analysis, the datacan be obtained in the form of comparison of the impact of attacks from Sybil attack and hello flood attack. The impact of the sybil attack is more influential on the parameters of throughput and pdr which has decreased the maximum value up to 69.9% for pdr and 56.4% for throughput. While the impact of hello flood attack ismore influential on the delay and jitter parameters that increased from the original value of 0.05 seconds to 0.576 seconds for delay and 0.579 seconds for jitter.

Fuzzy Based Advanced Hybrid Intrusion Detection System to Detect Malicious Nodes in Wireless Sensor Networks

In this paper, an Advanced Hybrid Intrusion Detection System (AHIDS) that automatically detects the WSNs attacks is proposed. AHIDS makes use of cluster-based architecture with enhanced LEACH protocol that intends to reduce the level of energy consumption by the sensor nodes. AHIDS uses anomaly detection and misuse detection based on fuzzy rule sets along with the Multilayer Perceptron Neural Network. The Feed Forward Neural Network along with the Backpropagation Neural Network are utilized to integrate the detection results and indicate the different types of attackers (i.e., Sybil attack, wormhole attack, and hello flood attack). For detection of Sybil attack, Advanced Sybil Attack Detection Algorithm is developed while the detection of wormhole attack is done by Wormhole Resistant Hybrid Technique. The detection of hello flood attack is done by using signal strength and distance. An experimental analysis is carried out in a set of nodes; 13.33% of the nodes are determined as misbehaving nodes, which classified attackers along with a detection rate of the true positive rate and false positive rate. Sybil attack is detected at a rate of 99,40%; hello flood attack has a detection rate of 98, 20%; and wormhole attack has a detection rate of 99, 20%.