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

2016 ◽  
Vol 2016 ◽  
pp. 1-16 ◽  
Author(s):  
Iman Almomani ◽  
Bassam Al-Kasasbeh ◽  
Mousa AL-Akhras
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Intrusion Detection ◽  
Cross Validation ◽  
Denial Of Service ◽  
Wireless Sensor ◽  
Security Threats ◽  
Dos Attacks ◽  
Wide Range ◽  
Fold Cross Validation

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.

Attacks of Denial-of-Service on Networks Layer of OSI Model and Maintaining of Security

2017 ◽  
Vol 5 (1) ◽  
pp. 181 ◽  
Author(s):  
Azeem Mohammed Abdul ◽  
Syed Umar
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Sensor Network ◽  
Denial Of Service ◽  
Wireless Sensor ◽  
Security Threats ◽  
Dos Attacks ◽  
Network Resources ◽  
Vital Functions ◽  
Technology Trends

<p>The emergence of wireless sensor networks as one of the technology trends in the coming years, and some special tests of safety. The event will be thousands of tiny sensors that cheap devices, memory, radio and make, in most cases, no access to the production and energy. Some great challenges of sensor networks are different; we focus on security in the form of wireless sensor networks. To some network wireless sensor network in order to optimize use of the sensor, so that the network can be as long as possible. But the management of the important mission of the sensor network, denial of service (DoS) attacks against the destruction of the efficient use of network resources and the vital functions of the network. DoS attacks can be one of the greatest threats to security threats be considered. In fact, there are many different layers of the OSI-DOS.</p>

scholarly journals A Genetic-Based Extreme Gradient Boosting Model for Detecting Intrusions in Wireless Sensor Networks

Sensors ◽  
2019 ◽  
Vol 19 (20) ◽  
pp. 4383 ◽  
Author(s):  
Alqahtani ◽  
Gumaei ◽  
Mathkour ◽  
Maher Ben Ismail
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Intrusion Detection ◽  
Cross Validation ◽  
Detection System ◽  
Imbalanced Data ◽  
Wireless Sensor ◽  
Gradient Boosting ◽  
Extreme Gradient Boosting ◽  
Fold Cross Validation

An Intrusion detection system is an essential security tool for protecting services and infrastructures of wireless sensor networks from unseen and unpredictable attacks. Few works of machine learning have been proposed for intrusion detection in wireless sensor networks and that have achieved reasonable results. However, these works still need to be more accurate and efficient against imbalanced data problems in network traffic. In this paper, we proposed a new model to detect intrusion attacks based on a genetic algorithm and an extreme gradient boosting (XGBoot) classifier, called GXGBoost model. The latter is a gradient boosting model designed for improving the performance of traditional models to detect minority classes of attacks in the highly imbalanced data traffic of wireless sensor networks. A set of experiments were conducted on wireless sensor network-detection system (WSN-DS) dataset using holdout and 10 fold cross validation techniques. The results of 10 fold cross validation tests revealed that the proposed approach outperformed the state-of-the-art approaches and other ensemble learning classifiers with high detection rates of 98.2%, 92.9%, 98.9%, and 99.5% for flooding, scheduling, grayhole, and blackhole attacks, respectively, in addition to 99.9% for normal traffic.

scholarly journals Overview of DOS attacks on wireless sensor networks and experimental results for simulation of interference attacks

2018 ◽  
Vol 38 (1) ◽  
pp. 130-138 ◽  
Author(s):  
Željko Gavrić ◽  
Dejan Simić
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Denial Of Service ◽  
Wireless Sensor ◽  
Dos Attacks ◽  
Security Issue ◽  
Simulation Scenario ◽  
Simulation Results ◽  
Potential Methods

Wireless sensor networks are now used in various fields. The information transmitted in the wireless sensor networks is very sensitive, so the security issue is very important. DOS (denial of service) attacks are a fundamental threat to the functioning of wireless sensor networks. This paper describes some of the most common DOS attacks and potential methods of protection against them. The case study shows one of the most frequent attacks on wireless sensor networks – the interference attack. In the introduction of this paper authors assume that the attack interference can cause significant obstruction of wireless sensor networks. This assumption has been proved in the case study through simulation scenario and simulation results.

scholarly journals Anomaly Detection in Wireless Sensor Networks: A Proposed Framework

2020 ◽  
Vol 14 (10) ◽  
pp. 150
Author(s):  
Dina M. Ibrahim ◽  
Nada M. Alruhaily
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Intrusion Detection ◽  
Detection System ◽  
Denial Of Service ◽  
Research Problem ◽  
Sensor Nodes ◽  
Base Stations ◽  
Sensor Data ◽  
Wireless Sensor

With the rise of IOT devices and the systems connected to the internet, there was, accordingly, an ever-increasing number of network attacks (e.g. in DOS, DDOS attacks). A very significant research problem related to identifying Wireless Sensor Networks (WSN) attacks and the analysis of the sensor data is the detection of the relevant anomalies. In this paper, we propose a framework for intrusion detection system in WSN. The first two levels are located inside the WSN, one of them is between sensor nodes and the second is between the cluster heads. While the third level located on the cloud, and represented by the base stations. In the first level, which we called light mode, we simulated an intrusion traffic by generating data packets based on TCPDUMP data, which contain intrusion packets, our work, is done by using WSN technology. We used OPNET simulation for generating the traffic because it allows us to collect intrusion detection data in order to measure the network performance and efficiency of the simulated network scenarios. Finally, we report the experimental results by mimicking a Denial-of-Service (DOS) attack. <em> </em>

scholarly journals Practical Implementation of an Adaptive Detection-Defense Unit against Link Layer DoS Attacks for Wireless Sensor Networks

2017 ◽  
Vol 2017 ◽  
pp. 1-9
Author(s):  
Murat Dener ◽  
Omer Faruk Bay
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Denial Of Service ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Adaptive Detection ◽  
Dos Attacks ◽  
Data Link ◽  
Link Layer ◽  
Data Link Layer

Wireless sensor networks (WSNs) have become a very popular subject in both industrial and academic fields of study due to the fact that they can operate on their own, do not require extra maintenance, and can be utilized in a wide variety of applications. In addition, the sensor nodes having limited hardware resources and power units cause certain security problems awaiting to be resolved. The Denial-of-Service (DoS) attacks, which cause disrupts in the communication of sensor nodes or abnormal situations, thus resulting in the decrease of the lifespan of the network, constitute a serious threat against the WSN security. Especially in military applications in which security is the most important design criterion, the WSN used in chemical and biological intrusion detection applications must be resistant against all forms of attacks. In this study, an adaptive detection-defense unit has been developed against the DoS attacks (packet collision, exhaustion, and unfairness) which occur in the data link layer. The developed unit has also been implemented on the TelosB nodes. Due to the new unit that was designed the lifespan of the nodes has been extended without the need for additional hardware by making them more secure against DoS attacks in the data link layer of the WSN.

scholarly journals Dynamic Cipher Puzzle for Efficient Broadcast Authentication in Wireless Sensor Networks

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 4021 ◽  
Author(s):  
Farah Afianti ◽  
Wirawan ◽  
Titiek Suryani
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Denial Of Service ◽  
Quadratic Function ◽  
Zero Solution ◽  
Experimental Results ◽  
Wireless Sensor ◽  
Threshold Function ◽  
Dos Attacks ◽  
Broadcast Authentication

The use of signature-based broadcast authentication for code and data dissemination in wireless sensor networks (WSNs) cannot be avoided. It increases security but requires high computation. Adversaries can exploit the latter condition as an opportunity to send many false signatures. Filtering methods can overcome this vulnerability. Cipher Puzzle is a filtering method that has low storage overhead along with high security, especially against denial of service (DoS) attacks. However, its number of hash iterations cannot be bounded, which causes sender-side delay. This paper proposes a Dynamic Cipher Puzzle (DCP), which uses a threshold function to limit the number of hash iterations. Hence, time at the sender-side can be used more efficiently. Besides, its dynamic puzzle-strength increases the obscurity of the transmitted packet. Simulation and experimental results were analyzed with Arduino 2560. The theoretical results show that the quadratic function outperformed the compared methods. The scheme decreased sender-side delay by 94.6% with a guarantee of zero solution probability in 1.728 × 10 − 13 . The experimental results show that the consumption of resources at the sensor node increases with an acceptable value. Moreover, DCP increases the complexity for the attacker to implement probability and signature-based DoS attacks.

scholarly journals Intrusion Detection System for Hybrid DoS Attacks using Energy Trust in Wireless Sensor Networks*

2018 ◽  
Vol 131 ◽  
pp. 1188-1195 ◽  
Author(s):  
Xie Jinhui ◽  
Tao Yang ◽  
Yang Feiyue ◽  
Pan Leina ◽  
Xu Juan ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Detection System ◽  
Wireless Sensor ◽  
Dos Attacks

Fault Tolerant Reliable Protocol (FTRP) Performance Evaluation in Wireless Sensor Networks: An Extensitive Study

2019 ◽  
pp. 1-36
Keyword(s):  
Wireless Sensor Networks ◽  
Fault Tolerance ◽  
Sensor Networks ◽  
Fault Tolerant ◽  
Cluster Head ◽  
Biological Data ◽  
Wireless Sensor ◽  
Delivery Ratio ◽  
Good Performer ◽  
Wide Range

Fault Tolerant Reliable Protocol (FTRP) is proposed as a novel routing protocol designed for Wireless Sensor Networks (WSNs). FTRP offers fault tolerance reliability for packet exchange and support for dynamic network changes. The key concept used is the use of node logical clustering. The protocol delegates the routing ownership to the cluster heads where fault tolerance functionality is implemented. FTRP utilizes cluster head nodes along with cluster head groups to store packets in transient. In addition, FTRP utilizes broadcast, which reduces the message overhead as compared to classical flooding mechanisms. FTRP manipulates Time to Live values for the various routing messages to control message broadcast. FTRP utilizes jitter in messages transmission to reduce the effect of synchronized node states, which in turn reduces collisions. FTRP performance has been extensively through simulations against Ad-hoc On-demand Distance Vector (AODV) and Optimized Link State (OLSR) routing protocols. Packet Delivery Ratio (PDR), Aggregate Throughput and End-to-End delay (E-2-E) had been used as performance metrics. In terms of PDR and aggregate throughput, it is found that FTRP is an excellent performer in all mobility scenarios whether the network is sparse or dense. In stationary scenarios, FTRP performed well in sparse network; however, in dense network FTRP’s performance had degraded yet in an acceptable range. This degradation is attributed to synchronized nodes states. Reliably delivering a message comes to a cost, as in terms of E-2-E. results show that FTRP is considered a good performer in all mobility scenarios where the network is sparse. In sparse stationary scenario, FTRP is considered good performer, however in dense stationary scenarios FTRP’s E-2-E is not acceptable. There are times when receiving a network message is more important than other costs such as energy or delay. That makes FTRP suitable for wide range of WSNs applications, such as military applications by monitoring soldiers’ biological data and supplies while in battlefield and battle damage assessment. FTRP can also be used in health applications in addition to wide range of geo-fencing, environmental monitoring, resource monitoring, production lines monitoring, agriculture and animals tracking. FTRP should be avoided in dense stationary deployments such as, but not limited to, scenarios where high application response is critical and life endangering such as biohazards detection or within intensive care units.

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