The nodes in wireless sensor networks (WSNs) utilize the radio frequency (RF) channel to communicate. Given that the RF channel is the primary communication channel, many researchers have developed techniques for securing that channel. However, the RF channel is not the only interface into a sensor. The sensing components, which are primarily designed to sense characteristics about the outside world, can also be used (or misused) as a communication (side) channel. In this paper, we characterize the side channels for various sensory components (i.e., light sensor, acoustic sensor, and accelerometer). While previous work has focused on the use of these side channels to improve the security and performance of a WSN, we seek to determine if the side channels have enough capacity to potentially be used for malicious activity. Specifically, we evaluate the feasibility and practicality of the side channels using today's sensor technology and illustrate that these channels have enough capacity to enable the transfer of common, well-known malware. The ultimate goal of this work is to illustrate the need for intrusion detection systems (IDSs) that not only monitor the RF channel, but also monitor the values returned by the sensory components.

Examining the characteristics and implications of sensor side channels

This paper proposes the DISON framework, a generic management system for Wireless Sensor Networks (WSNs). The first objective of the DISON framework is to allow sensor nodes to adapt autonomously to changes in application requirements and network resources. The second objective is to provide a framework that enables both the developer and the administrator of WSNs to choose what management functions to perform, what conditions should trigger sensor nodes’ adaption, and how to adapt in both the development and run-time stages. To achieve these objectives, firstly we propose a multilevel management mechanism where every sensor node is empowered to participate in the management process at different levels according to its resources. Then, we explain how sensor nodes can be self adaptive by defining two data models, a context model and a policy model. We also discuss how context is validated and how it is used to trigger policies. We then present two management functions that can be applied to most applications, the monitoring function and the resource allocating function. We implement DISON in TinyOS operating system as an independent component which can interact with user applications and other network components through public interfaces. The feasibility of the resource allocating function is evaluated on a 26-node indoor testbed. The results of the experiments show that DISON can not only resolve the management problems but also improve network performance such as packet delivery rate or energy consumption. Finally, through experiments in another testbed with different number of nodes, we demonstrate the scalability of DISON.

Design of a generic management system for wireless sensor networks

Wireless Sensor Network (WSN) is a collection of small and low-powered gadgets called sensor nodes (motes), which are capable of sensing the environment, collecting and processing the sensed data, and communicating with each other to accomplish a specific task. Moreover, all sensed and processed data are finally handed over to a central gathering point called a base station (sink), where all collected data are stored and can be reviewed by the user. Most of the current methods concerning WSN development are application or platform-dependent; hence it is not a trivial task to reuse developed applications in another environment. Therefore, WSN application development is a challenging and complex task because of the low-level technical details and programming complexity. Furthermore, most WSN development projects are managed by software engineers, not application field experts or WSN end users. Consequently, WSN solutions are considered expensive, due to the amount of effort that has to be put into these projects. 
This research project aims to reduce the complexity in developing WSN applications, by abstracting the low-level technical and programming details for average developers and domain experts. In this research, we argue that reducing complexity can be achieved by defining a new Domain-Specific Language (DSL) as a new application development and programming abstraction, which supports multi-levels modelling (i.e. network, group, and node-level). The outcome of this work is the definition of a new language called SenNet, which is an open source DSL programming abstraction that enables application developers to concentrate on the high-level application logic rather than the low-level complex details. SenNet was developed using the principles of Model-Driven Development (MDD) and macro-programming. Developers can use SenNet as a high-level programming abstraction to auto-generate a ready-to-deploy single node nesC code for all sensor nodes that comprise the SenNet application. SenNet gives developers the flexibility they need by offering them a broad range of predefined monitoring tasks and activities, enabling developers to develop different application types such as Sense-Forward (SF), and Event-Triggered (ET); besides providing a set of node-level and in-network data processing tasks. The current SenNet version is configured to generate nesC code, yet SenNet can be set up to produce and generate any programming language such as Java, or C++, by reconfiguring the code generator to produce the new language format, without changing the language design and produced semantics. 
Various tests and user study have been used to evaluate SenNet’s usability and functional suitability. Evaluation results found that SenNet could save 88.45% of the LOC required to be programmed by a developer, and 87.14% of the required vocabularies. Furthermore, results showed that SenNet could save 92.86% and 96.47% of the program length and volume respectively. Most of the user study participants (96%) found SenNet to be usable and helps to achieve the required WSN application with reduced development effort. Moreover, 82% of the participants believe that SenNet is functionally suitable for WSN application development. Two real-world business case studies developed were used to assess SenNet’s appropriateness to develop WSN real applications, and how it can be used to develop applications related to data processing tasks. Based on the final evaluation results, it can be concluded that our research has been successful in introducing SenNet as a new abstraction to reduce complexity in the WSN application development process.

Reducing complexity in developing wireless sensor network systems using model-driven development

/pdf/proximity-based-attacks-in-wireless-sensor-networks-57k5obdkui.pdf

Proximity-based attacks in wireless sensor networks

Wireless Sensor Networks (WSNs) are rapidly gaining popularity in various critical domains like health care, critical infrastructure, and climate monitoring, where application builders have diversified development needs. Independent of the functionalities provided by the WSN applications, many of the developers use visualization, simulation, and programming tools. However, these tools are designed as separate stand-alone applications, which force developers to use multiple tools. This situation often poses confusion and hampers an efficient development experience. To avoid the complexity of using multiple tools, we have designed a new extensible, multi-platform, scalable, and open-source framework called PROVIZ, which is an integrated visualization and programming framework. In this paper, we explain the various features of PROVIZ's visualization and programming framework and discuss how PROVIZ can be used as a visual debugging tool to aid in providing a software fix.

PROVIZ: An integrated visualization and programming framework for WSNs

Wireless sensor networks (WSNs) are used for the monitoring of physical and environmental phenomena, and applicable in a range of different domains (e.g., health care, military, critical infrastructure). When using WSNs in a variety of real-world applications, security is a vital problem that should be considered by developers. As the development of security applications (SAs) for WSNs require meticulous procedures and operations, the software implementation process can be more challenging than regular applications. Hence, in an effort to facilitate the design, development and implementation of WSN security applications, we introduce the Monitoring Core (M-Core). The M-Core is a modular, lightweight, and extensible software layer that gathers necessary data including the internal and the external status of the sensor (e.g., information about ongoing communications, neighbors, and sensing), and provides relevant information for the development of new SAs. Similar to other software development tools, the M-Core was developed to facilitate the design and development of new WSN SAs on different platforms. Moreover, a new user-friendly domain-specific language, the M-Core Control Language (MCL), was developed to further facilitate the use of the M-Core and reduce the developer's coding time. With the MCL, a user can implement new SAs without the overhead of learning the details of the underlying sensor software architecture (e.g., TinyOS). The M-Core has been implemented in TinyOS-2.x and tested on real sensors (Tmote Sky and MicaZ). Using the M-Core architecture, we implemented several SAs to show that the M-Core allows easy and rapid development of security programs efficiently and effectively.

/pdf/the-monitoring-core-a-framework-for-sensor-security-2z7ahc8bd6.pdf

The Monitoring Core: A framework for sensor security application development

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The Monitoring Core: A framework for sensor security application development