scholarly journals Modelling the Spread of Botnet Malware in IoT-Based Wireless Sensor Networks

2019 ◽  
Vol 2019 ◽  
pp. 1-13 ◽  
Author(s):  
Dilara Acarali ◽  
Muttukrishnan Rajarajan ◽  
Nikos Komninos ◽  
B. B. Zarpelão
Keyword(s):  
Real Life ◽  
Influential Factors ◽  
Propagation Model ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Wireless Sensor Nodes ◽  
Processing Power ◽  
The Monte Carlo Method ◽  
Attack Surface ◽  
The Impact

The propagation approach of a botnet largely dictates its formation, establishing a foundation of bots for future exploitation. The chosen propagation method determines the attack surface and, consequently, the degree of network penetration, as well as the overall size and the eventual attack potency. It is therefore essential to understand propagation behaviours and influential factors in order to better secure vulnerable systems. Whilst botnet propagation is generally well studied, newer technologies like IoT have unique characteristics which are yet to be thoroughly explored. In this paper, we apply the principles of epidemic modelling to IoT networks consisting of wireless sensor nodes. We build IoT-SIS, a novel propagation model which considers the impact of IoT-specific characteristics like limited processing power, energy restrictions, and node density on the formation of a botnet. Focusing on worm-based propagation, this model is used to explore the dynamics of spread using numerical simulations and the Monte Carlo method to discuss the real-life implications of our findings.

Cost Minimization of Sensor Placement and Routing in Wireless Sensor Networks

2020 ◽  
pp. 1286-1301
Author(s):  
Tata Jagannadha Swamy ◽  
Garimella Rama Murthy
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Cost Minimization ◽  
Real Life ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Wireless Sensor Nodes ◽  
Technological Advances ◽  
Strongly Connected ◽  
Placement And Routing

Wireless Sensor Nodes (WSNs) are small in size and have limited energy resources. Recent technological advances have facilitated widespread use of wireless sensor networks in many real world applications. In real life situations WSN has to cover an area or monitor a number of nodes on a plane. Sensor node's coverage range is proportional to their cost, as high cost sensor nodes have higher coverage ranges. The main goal of this paper is to minimize the node placement cost with the help of uniform and non-uniform 2D grid planes. Authors propose a new algorithm for data transformation between strongly connected sensor nodes, based on graph theory.

Measurements of Car Vibrations Under Real-Life Driving Conditions and Assessment of Energy Harvesting for Wireless Sensor Nodes

2013 ◽  
Author(s):  
A. Dompierre ◽  
M. S. Traore ◽  
L. G. Fréchette
Keyword(s):  
Energy Harvesting ◽  
Real Life ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Vibration Energy ◽  
Vehicle Speed ◽  
Vibration Energy Harvesting ◽  
Wireless Sensor Nodes ◽  
Driving Conditions ◽  
Continuous Power

This work presents a study of car vibrations measured under typical driving conditions to assess the potential of powering automotive sensors incorporated in cars via vibration energy harvesting (VEH). The locations where sensors or switches are currently used and the requirements of potential automotive wireless sensor nodes were used as criteria to narrow down the location of the measurements. A total of 20 locations were retained after keeping the sensors with lower requirements. Random vibrations due to the road perturbations as well as part of the structural responses of the vehicle from changing vehicle speed were observed through vibration peaks which shift in frequency and others which are steady despite the changing conditions. The spectral analyses indicate that most of the available vibration energy is in a frequency range below 200 Hz, with harvestable consistent peaks below 140 Hz on the front chassis, the rear and front plastic bumpers and the brake fluid tank. An analytical model is used to assess the power output from several linear harvester MEMS designs and we estimate that continuous power over 100 nW are achievable from those sources.

scholarly journals Indoor Localization by using Particle Filtering Approach with Wireless Sensor Nodes

2013 ◽  
Vol 9 (1) ◽  
pp. 74
Author(s):  
Hakan Koyuncu ◽  
Ahmet Çevik
Keyword(s):  
Particle Filtering ◽  
Indoor Localization ◽  
Propagation Model ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Distance Measurements ◽  
Wireless Sensor Nodes ◽  
Object Distance ◽  
Object Locations ◽  
Current Estimation

Jennic type wireless sensor nodes are utilized together with a novel particle filtering technique for indoor localization. Target objects are localized with an accuracy of around 0.25 meters. The proposed technique introduces a new particle generation and distribution technique to improve current estimation of object positions. Particles are randomly distributed around the object in the sensing area within a circular strip of 2 STD of object distance measurements. Particle locations are related to object locations by using Gaussian weight distribution methods. Object distances from the transmitters are determined by using received RSSI values and ITU-R indoor propagation model. Measured object distances are used together with the particle distances from the transmitters to predict the object locations.

Cost Minimization of Sensor Placement and Routing in Wireless Sensor Networks

2016 ◽  
pp. 115-134
Author(s):  
Tata Jagannadha Swamy ◽  
Garimella Rama Murthy
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Cost Minimization ◽  
Real Life ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Wireless Sensor Nodes ◽  
Technological Advances ◽  
Strongly Connected ◽  
Placement And Routing

Wireless Sensor Nodes (WSNs) are small in size and have limited energy resources. Recent technological advances have facilitated widespread use of wireless sensor networks in many real world applications. In real life situations WSN has to cover an area or monitor a number of nodes on a plane. Sensor node's coverage range is proportional to their cost, as high cost sensor nodes have higher coverage ranges. The main goal of this paper is to minimize the node placement cost with the help of uniform and non-uniform 2D grid planes. Authors propose a new algorithm for data transformation between strongly connected sensor nodes, based on graph theory.

scholarly journals QoS Framework for a Multi-stack based Heterogeneous Wireless Sensor Network

2017 ◽  
Vol 7 (5) ◽  
pp. 2713 ◽  
Author(s):  
K. Panimozhi ◽  
G. Mahadevan
Keyword(s):  
Routing Protocols ◽  
Wireless Sensors ◽  
Life Time ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Wireless Sensor Nodes ◽  
Processing Power ◽  
Reactive Routing ◽  
Heterogeneous Wireless Sensor Network ◽  
Battery Energy

Wireless sensor nodes consist of a collection of sensor nodes with constrained resources in terms of processing power and battery energy. Wireless sensors networks are used increasingly in many industrial and consumer applications. Sensors detect events and send via multi hop routing to the sink node for processing the event. The routing path is established through proactive or reactive routing protocols. To improve the performance of the Wireless Sensor Networks, multi stack architecture is addressed. But the multi stack architecture has many problems with respect to life time, routing loop and QOS. In this work we propose a solution to address all these three problems of life time, routing loop and QOS in case of multi stack architecture.

Number of sensors versus time to detection in wildfires

2009 ◽  
Vol 18 (7) ◽  
pp. 825 ◽  
Author(s):  
Pablo I. Fierens
Keyword(s):  
Probability Distribution ◽  
Propagation Model ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Independent Random Variables ◽  
Burned Area ◽  
Wireless Sensor Nodes ◽  
Time To Detection ◽  
The Moment ◽  
The Cost

The lack of extensive research in the application of inexpensive wireless sensor nodes for the early detection of wildfires motivated us to investigate the cost of such a network. As a first step, in this paper we present several results that relate the time to detection and the burned area to the number of sensor nodes in the region that is protected. We prove that the probability distribution of the size of the burned area at the moment of detection is approximately exponential, given that some hypotheses hold: the positions of the sensor nodes are independent random variables uniformly distributed and the number of sensor nodes is large. This conclusion depends neither on the number of ignition points nor on the propagation model of the fire.

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