Mitigating Denial of Service Attacks in Fog-Based Wireless Sensor Networks Using Machine Learning Techniques

Wireless sensor networks are considered to be among the most significant and innovative technologies in the 21st century due to their wide range of industrial applications. Sensor nodes in these networks are susceptible to a variety of assaults due to their special qualities and method of deployment. In WSNs, denial of service attacks are common attacks in sensor networks. It is difficult to design a detection and prevention system that would effectively reduce the impact of these attacks on WSNs. In order to identify assaults on WSNs, this study suggests using two machine learning models: decision trees and XGBoost. The WSNs dataset was the subject of extensive tests to identify denial of service attacks. The experimental findings demonstrate that the XGBoost model, when applied to the entire dataset, has a higher true positive rate (98.3%) than the Decision tree approach (97.3%) and a lower false positive rate (1.7%) than the Decision tree technique (2.7%). Like this, with selected dataset assaults, the XGBoost approach has a higher true positive rate (99.01%) than the Decision tree technique (97.50%) and a lower false positive rate (0.99%) than the Decision tree technique (2.50%)

Configurable Secured Adaptive Routing Protocol for Mobile Wireless Sensor Networks

This paper aims at designing, building, and simulating a secured routing protocol to defend against packet dropping attacks in mobile WSNs (MWSNs). This research addresses the gap in the literature by proposing Configurable Secured Adaptive Routing Protocol (CSARP). CSARP has four levels of protection to allow suitability for different types of network applications. The protocol allows the network admin to configure the required protection level and the ratio of cluster heads to all nodes. The protocol has an adaptive feature, which allows for better protection and preventing the spread of the threats in the network. The conducted CSARP simulations with different conditions showed the ability of CSARP to identify all malicious nodes and remove them from the network. CSARP provided more than 99.97% packets delivery rate with 0% data packet loss in the existence of 3 malicious nodes in comparison with 3.17% data packet loss without using CSARP. When compared with LEACH, CSARP showed an improvement in extending the lifetime of the network by up to 39.5%. The proposed protocol has proven to be better than the available security solutions in terms of configurability, adaptability, optimization for MWSNs, energy consumption optimization, and the suitability for different MWSNs applications and conditions

Understanding the Performance of Software Defined Wireless Sensor Networks under Denial of Service Attack

Wireless sensor networks (WSN) are formed from restricted devices and are known to be vulnerable to denial of service (DoS) security attacks. In parallel, software-defined networking has been identified as a solution for many WSN challenges with respect to flexibility and reuse. Conversely, the SDN control plane centralization may bring about new security threats and vulnerabilities. In this work, we perform a traffic analysis of software-defined WSN (SDWSN) in order to gain understanding of the network's performance when it is under certain types of DoS attacks. In particular, we consider three different DoS scenarios of increasing aggressiveness: (i) false flow requests DoS, (ii) false data flow forwarding DoS, and, (iii) false neighbor information passing DoS. Our simulation results for the latter two types of attack showed significant changes both in the average value and the variance of the delivery rate and the overall overhead. These results demonstrate that it is possible to identify when a SDWSN is under a particular type of DoS, by monitoring the respective quantities

WSN-DS: A Dataset for Intrusion Detection Systems in Wireless Sensor Networks

Wireless Sensor Networks (WSN) have become increasingly one of the hottest research areas in computer science due to their wide range of applications including critical military and civilian applications. Such applications have created various security threats, especially in unattended environments. To ensure the security and dependability of WSN services, an Intrusion Detection System (IDS) should be in place. This IDS has to be compatible with the characteristics of WSNs and capable of detecting the largest possible number of security threats. In this paper a specialized dataset for WSN is developed to help better detect and classify four types of Denial of Service (DoS) attacks: Blackhole, Grayhole, Flooding, and Scheduling attacks. This paper considers the use of LEACH protocol which is one of the most popular hierarchical routing protocols in WSNs. A scheme has been defined to collect data from Network Simulator 2 (NS-2) and then processed to produce 23 features. The collected dataset is called WSN-DS. Artificial Neural Network (ANN) has been trained on the dataset to detect and classify different DoS attacks. The results show that WSN-DS improved the ability of IDS to achieve higher classification accuracy rate. WEKA toolbox was used with holdout and 10-Fold Cross Validation methods. The best results were achieved with 10-Fold Cross Validation with one hidden layer. The classification accuracies of attacks were 92.8%, 99.4%, 92.2%, 75.6%, and 99.8% for Blackhole, Flooding, Scheduling, and Grayhole attacks, in addition to the normal case (without attacks), respectively

Effect of Blackhole Attack on Single Hop and Multihop Leach Protocol

Abstract Wireless micro sensor networks provide reliable monitoring of remote areas for data-gathering. Due to the limited battery capacity of sensor nodes, energy consumption plays an important role in the operation of WSN. This can be improved by using a protocol called Low energy adaptive clustering hierarchy (LEACH).Malicious attacks are generated in the network due to power supply, processing abilities and capacity for high power radio transmission. In this paper one such attack namely BlackHole attack and its effect on single hop LEACH and multihop LEACH has been compared, simulated and analyzed

Formal modelling and analysis of denial of services attacks in wireless sensor networks

Wireless Sensor Networks (WSNs) have attracted considerable research attention in recent years because of the perceived potential benefits offered by self-organising, multi-hop networks consisting of low-cost and small wireless devices for monitoring or control applications in di±cult environments. WSN may be deployed in hostile or inaccessible environments and are often unattended. These conditions present many challenges in ensuring that WSNs work effectively and survive long enough to fulfil their functionalities. Securing a WSN against any malicious attack is a particular challenge. Due to the limited resources of nodes, traditional routing protocols are not appropriate in WSNs and innovative methods are used to route data from source nodes to sink nodes (base stations). To evaluate the routing protocols against DoS attacks, an innovative design method of combining formal modelling and computer simulations has been proposed. This research has shown that by using formal modelling hidden bugs (e.g. vulnerability to attacks) in routing protocols can be detected automatically. In addition, through a rigorous testing, a new routing protocol, RAEED (Robust formally Analysed protocol for wirEless sEnsor networks Deployment), was developed which is able to operate effectively in the presence of hello flood, rushing, wormhole, black hole, gray hole, sink hole, INA and jamming attacks. It has been proved formally and using computer simulation that the RAEED can pacify these DoS attacks. A second contribution of this thesis relates to the development of a framework to check the vulnerability of different routing protocols against Denial of Service(DoS) attacks. This has allowed us to evaluate formally some existing and known routing protocols against various DoS attacks iand these include TinyOS Beaconing, Authentic TinyOS using uTesla, Rumour Routing, LEACH, Direct Diffusion, INSENS, ARRIVE and ARAN protocols. This has resulted in the development of an innovative and simple defence technique with no additional hardware cost for deployment against wormhole and INA attacks. In the thesis, the detection of weaknesses in INSENS, Arrive and ARAN protocols was also addressed formally. Finally, an e±cient design methodology using a combination of formal modelling and simulation is propose to evaluate the performances of routing protocols against DoS attacks

Distribuirani obrambeni mehanizmi za clone napade temeljeni na algoritmu za istraživanje gravitacije (GSA) u WSN

Wireless Sensor Networks (WSN) are often deployed in hostile environment and are vulnerable to attacks because of the resource constrained nature of the sensors. Clone attack in WSN is one of the major issues where the messages are eavesdropped, the captured node is cloned, and multiple nodes with same identity are produced by attacker. In order to overcome these issues, in this paper, a Distributed Defense Mechanism for Clone Attacks based on Gravitational Search Algorithm (GSA) in WSN is proposed. For efficiently detecting the suspect nodes, the nodes in the channel can be divided into witness node and the claimer node. The witness nodes are responsible for the suspect nodes detection, whereas the claimer nodes should provide their identities for the detection process. For the witness nodes selection, we utilize the GSA to pick out the best witness nodes set. After selecting the witness nodes, clone attack detection is performed by observing the behavior of the neighbor nodes. On detecting the clone attack, revocation procedure is triggered to revoke the clone attack in the witness nodes. By simulation results, it can be concluded that the proposed algorithm provides better protection to clone attacks by reducing the packet drop and increasing the packet delivery ratio.Bežične senzorske mreže (WSN) često su raspoređene u neprijateljskom okruženju i ranjive su na napade zbog prirode senzora koji su tehnološki ograničeni. Clone napad u WSN jedan je od glavnih problema gdje se poruke prisluškuju, zarobljeni čvor se klonira te napadač proizvede višestruke čvorove istog identiteta. Kako bi nadvladali te probleme, ovaj rad predlaže distribuirani obrambeni mehanizam za clone napade temeljen na algoritmu za istraživanje gravitacije (GSA) u WSN. Kako bi se sumnjivi čvorovi efikasno detektirali, čvorovi u kanalu mogu se podijeliti u čvorove svjedoke i tražene čvorove. Čvorovi svjedoci odgovorni su za otkrivanje sumnjivih čvorova, dok traženi čvorovi trebaju za potrebe procesa detekcije navesti svoj identitet. Za izbor čvorova svjedoka, koristi se GSA kako bi se izabrala grupa čvorova koji su najprikladniji. Nakon izbora čvorova svjedoka, otkivanje clone napada vrši se promatranjem ponašanja susjednih čvorova. Otkrivanjem clone napada aktivira se proces opoziva kako bi se opozvao clone napad u čvorovima svjedocima. Prema rezultatima dobivenim iz simulacije može se zaključiti kako predloženi algoritam pruža bolju zaštitu od clone napada smanjivanjem odbacivanja paketa i povećavanjem omjera isporuke paketa

Performance Analysis of Routing Protocols in MANET under Malicious Attacks

MANETs routing protocols are vulnerable to various types of security attacks such as selfish nodes, grey-hole and black-hole attacks. These routing protocols are unprotected and subsequently result in various kinds of malicious mobile nodes being injected into the networks. In this paper, three types of attacks such as selfish, gray-hole and black-hole attacks have been applied to two important MANET routing protocols; Ad-hoc On demand Distance Vector (OADV) and Dynamic Source Routing (DSR) in order to analyze and compare the impact of these attacks on the network performance based on throughput, average delay, packet loss and consumption of energy