Modeling attacks on wireless sensor networks

A large body via eavesdropping on the wireless medium and captures nodes of research exists on the problem of information privacy, based on the learned information. We show that attacks in this adversary model correspond to NP-hard optimization problems aiming to prevent information leakage to eavesdroppers and and discuss the behavior of a reasonable heuristic algorithm.

Modeling attacks on wireless sensor networks

There are an increasing number of small companies producing WSN hardware and the commercial situation can be compared to home computing in the s.

Many of the nodes are still in the research and development stage, particularly their software. Also inherent to sensor network adoption is the use of very low power methods for radio communication and data acquisition.

The Gateway acts as a bridge between the WSN and the other network. This enables data to be stored and processed by devices with more resources, for example, in a remotely located server.

Modeling attacks on wireless sensor networks

Wireless[ edit ] There are several wireless standards and solutions for sensor node connectivity. Thread and ZigBee can connect sensors operating at 2. With the emergence of Internet of Thingsmany other proposals have been made to provide sensor connectivity.

Wi-SUN [19] connects devices at home. WSNs may be deployed in large numbers in various environments, including remote and hostile regions, where ad hoc communications are a key component. For this reason, algorithms and protocols need to address the following issues: Increased lifespan Robustness and fault tolerance Self-configuration Lifetime maximization: To conserve power, wireless sensor nodes normally power off both the radio transmitter and the radio receiver when not in use.

They more strongly resemble embedded systemsfor two reasons. First, wireless sensor networks are typically deployed with a particular application in mind, rather than as a general platform. Second, a need for low costs and low power leads most wireless sensor nodes to have low-power microcontrollers ensuring that mechanisms such as virtual memory are either unnecessary or too expensive to implement.

However, such operating systems are often designed with real-time properties. TinyOS is perhaps the first [22] operating system specifically designed for wireless sensor networks. TinyOS is based on an event-driven programming model instead of multithreading. TinyOS programs are composed of event handlers and tasks with run-to-completion semantics.

Wireless sensor network - Wikipedia

When an external event occurs, such as an incoming data packet or a sensor reading, TinyOS signals the appropriate event handler to handle the event. Event handlers can post tasks that are scheduled by the TinyOS kernel some time later.

Online collaborative sensor data management platforms[ edit ] Online collaborative sensor data management platforms are on-line database services that allow sensor owners to register and connect their devices to feed data into an online database for storage and also allow developers to connect to the database and build their own applications based on that data.

Examples include Xively and the Wikisensing platform. Such platforms simplify online collaboration between users over diverse data sets ranging from energy and environment data to that collected from transport services.

The architecture of the Wikisensing system [24] describes the key components of such systems to include APIs and interfaces for online collaborators, a middleware containing the business logic needed for the sensor data management and processing and a storage model suitable for the efficient storage and retrieval of large volumes of data.

Simulation[ edit ] At present, agent-based modeling and simulation is the only paradigm which allows the simulation of complex behavior in the environments of wireless sensors such as flocking.

Agent-based modelling was originally based on social simulation. Security[ edit ] Infrastructure-less architecture i. Therefore, security is a big concern when WSNs are deployed for special applications such as military and healthcare.

Owing to their unique characteristics, traditional security methods of computer networks would be useless or less effective for WSNs. Hence, lack of security mechanisms would cause intrusions towards those networks. These intrusions need to be detected and mitigation methods should be applied.

More interested readers would refer to Butun et al. Distributed sensor network[ edit ] If a centralized architecture is used in a sensor network and the central node fails, then the entire network will collapse, however the reliability of the sensor network can be increased by using a distributed control architecture.

Distributed control is used in WSNs for the following reasons: Sensor nodes are prone to failure, For better collection of data, To provide nodes with backup in case of failure of the central node. There is also no centralised body to allocate the resources and they have to be self organized.

Data integration and sensor web[ edit ] The data gathered from wireless sensor networks is usually saved in the form of numerical data in a central base station. Additionally, the Open Geospatial Consortium OGC is specifying standards for interoperability interfaces and metadata encodings that enable real time integration of heterogeneous sensor webs into the Internet, allowing any individual to monitor or control wireless sensor networks through a web browser.

As nodes can inspect the data they forward, they can measure averages or directionality for example of readings from other nodes. For example, in sensing and monitoring applications, it is generally the case that neighboring sensor nodes monitoring an environmental feature typically register similar values.

This kind of data redundancy due to the spatial correlation between sensor observations inspires techniques for in-network data aggregation and mining. Aggregation reduces the amount of network traffic which helps to reduce energy consumption on sensor nodes.problems of modeling attacks on network protocols and performance and design of network- ing protocols that are robust to attack.

We investigate secure communication link establishment in ad-hoc and sensor networks. Modeling Node Capture Attacks in Wireless Sensor Networks Invited Paper Patrick Tague and Radha Poovendran Network Security Lab (NSL), Electrical Engineering Department.

His current research interests include wireless networks, wireless sensor networks, mobile computing and distributed systems. Qinglin Zhao received the Ph.D.

degree from the Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China, in Wireless sensor network agent-based modeling and simulation is the only paradigm which allows the simulation of complex behavior in the environments of wireless sensors the encrypted data to perform aggregation.

This exposes the plaintext at the aggregators, making the data vulnerable to attacks from an adversary. Similarly an. modeling and simulation of computer networks and systems, wireless sensor networks, green ICT, wireless and wired networks, and information and network security, is a Professor of Computer Science at Monmouth University, NJ, USA.

Modeling Attacks In Wireless Sensor Networks Chinya V. Ravishankar University of California, Riverside. 1 Introduction Compromises in sensor networks are a .

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