DI-SEC: Distributed Security Framework for Heterogeneous Wireless Sensor Networks

Wireless Sensor Networks (WSNs) are deployed for monitoring in a range of critical domains (e.g., health care, military, critical infrastructure). Accordingly, these WSNs should be resilient to attacks. The current approach to defending against malicious threats is to develop and deploy a specific defense mechanism for a specific attack. However, the problem with this traditional approach to defending sensor networks is that the solution for one attack (i.e., Jamming attack) does not defend against other attacks (e.g., Sybil and Selective Forwarding). This work addresses the challenges with the traditional approach to securing sensor networks and presents a comprehensive framework, Di-Sec, that can defend against all known and forthcoming attacks. At the heart of Di-Sec lies the monitoring core (M-Core), which is an extensible and lightweight layer that gathers information and statistics relevant for creating defense modules. Along with Di-Sec, a new user-friendly domain-specific language was developed, the M-Core Control Language (MCL). Using the MCL, a user can implement new defense mechanisms without the overhead of learning the details of the underlying software architecture (i.e., TinyOS, Di-Sec). Hence, the MCL expedites the development of sensor defense mechanisms by significantly simplifying the coding process for developers. The Di-Sec framework has been implemented and tested on real sensors to evaluate its feasibility and performance. Our evaluation shows that Di-Sec is feasible on today’s resource-limited sensors and has a nominal overhead. Furthermore, we illustrate the functionality of Di-Sec by implementing four detection and defense mechanisms for attacks at various layers of the communication stack

Optimizing Sensor Network Reprogramming via In-situ Reconfigurable Components

International audienceWireless reprogramming of sensor nodes is a critical requirement in long-lived Wireless Sensor Networks (WSNs) for several concerns, such as fixing bugs, upgrading the operating system and applications, and adapting applications behavior according to the physical environment. In such resource-poor platforms, the ability to efficiently delimit and reconfigure the necessary portion of sensor software--instead of updating the full binary image--is of vital importance. However, most of existing approaches in this field have not been widely adopted to date due to the extensive use of WSN resources or lack of generality. In this article, we therefore consider WSN programming models and run-time reconfiguration models as two interrelated factors and we present an integrated approach for addressing efficient reprogramming in WSNs. The middleware solution we propose, RemoWare, is characterized by mitigating the cost of post-deployment software updates on sensor nodes via the notion of in-situ reconfigurability and providing a component-based programming abstraction to facilitate the development of dynamic WSN applications. Our evaluation results show that RemoWare imposes a very low energy overhead in code distribution and component reconfiguration, and consumes approximately 6% of the total code memory on a TelosB sensor platform

The energy problem in resource constrained wireless networks

Today Wireless Sensor Networks are part of a wider scenario involving several wireless and wired communication technology: the Internet Of Things (IoT). The IoT envisions billions of tiny embedded devices, called Smart Objects, connected in a Internet-like structure. Even if the integration of WSNs into the IoT scenario is nowadays a reality, the main bottleneck of this technology is the energy consumption of sensor nodes, which quickly deplete the limited amount of energy of available in batteries. This drawback, referred to as the energy problem, was addressed in a number of research papers proposing various energy optimization approaches to extend sensor nodes lifetime. However, energy problem is still an open issue that prevents the full exploitation of WSN technology. This thesis investigates the energy problem in WSNs and introduces original solutions trying to mitigate drawbacks related to this phenomenon. Starting from solutions proposed by the research community in WSNs, we deeply investigate critical and challenging factors concerning the energy problem and we came out with cutting-edge low-power hardware platforms, original software energy-aware protocols and novel energy-neutral hardware/software solutions overcoming the state-of-art. Concerning low-power hardware, we introduce the MagoNode, a new WSN mote equipped with a radio frequency (RF) front-end which enhances radio performance. We show that in real applicative contexts, the advantages introduced by the RF front-end keep packet re-trasmissions and forwards low. Furthermore, we present the ultra low-power Wake-Up Radio (WUR) system we designed and the experimental activity to validate its performance. In particular, our Wake-up Radio Receiver (WRx) features a sensitivity of -50 dBm, has a current consumption of 579nA in idle-listening and features a maximum radio range of about 19 meters. What clearly resulted from the experimental activity is that performance of the WRx is strongly affected by noise. To mitigate the impact of noise on WUR communication we implemented a Forward Error Correction (FEC) mechanism based on Hamming code. We performed several test to determine the effectiveness of the proposed solution. The outcome show that our WUR system can be employed in environment where the Bit Error Rate (BER) induced by noise is up to 10^2, vice versa, when the BER induced by noise is in the order of 10´3 or below, it is not worth to use any Forward Error Correction (FEC) mechanism since it does not introduce any advantages compared to uncoded data. In the context of energy-aware solutions, we present two protocols: REACTIVE and ALBA-WUR. REACTIVE is a low-power over-the-air programming (OAP) protocol we implemented to improve the energy efficiency and lower the image dissemination time of Deluge T2, a well-known OAP protocol implemented in TinyOS. To prove the effectiveness of REACTIVE we compared it to Deluge exploiting a testbed made of MagoNode motes. Results of our experiments show that the image dissemination time is 7 times smaller than Deluge, while the energy consumption drops 2.6 times. ALBA-WUR redesigns ALBA-R protocol, extending it to exploit advantages of WUR technology. We compared ALBA-R and ALBA-WUR in terms of current consumption and latency via simulations. Results show that ALBA-WUR estimated network lifetime is decades longer than that achievable by ALBA-R. Furthermore, end-to-end packet latency features by ALBA-WUR is comparable to that of ALBA-R. While the main goal of energy optimization approaches is motes lifetime maximization, in recent years a new research branch in WSN emerged: Energy Neutrality. In contrast to lifetime maximization approach, energy neutrality foresees the perennial operation of the network. This can be achieve only making motes use the harvested energy at an appropriate rate that guarantees an everlasting lifetime. In this thesis we stress that maximizing energy efficiency of a hardware platform dedicated to WSNs is the key to reach energy neutral operation (ENO), still providing reasonable data rates and delays. To support this conjecture, we designed a new hardware platform equipped with our wake-up radio (WUR) system able to support ENO, the MagoNode++. The MagoNode++ features a energy harvester to gather energy from solar and thermoelectric sources, a ultra low power battery and power management module and our WUR system to improve the energy efficiency of wireless communications. To prove the goodness in terms of current consumption of the MagoNode++ we ran a series of experiments aimed to assess its performance. Results show that the MagoNode++ consumes only 2.8 µA in Low Power Mode with its WRx module in listening mode. While carrying on our research work on solutions trying to mitigate the energy problem, we also faced a challenging application context where the employment of WSNs is considered efficient and effective: structural health monitoring (SHM). SHM deals with the early detection of damages to civil and industrial structures and is emerging as a fundamental tool to improve the safety of these critical infrastructures. In this thesis we present two real world WSNs deployment dedicated to SHM. The first concerned the monitoring of the Rome B1 Underground construction site. The goal was to monitor the structural health of a tunnel connecting two stops. The second deployment concerned the monitoring of the structural health of buildings in earthquake-stricken areas. From the experience gained during these real world deployments, we designed the Modular Monitoring System (MMS). The MMS is a new low-power platform dedicated to SHM based on the MagoNode. We validated the effectiveness of the MMS low-power design performing energy measurements during data acquisition from actual transducers

Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey

Wireless sensor networks (WSNs) consist of autonomous and resource-limited devices. The devices cooperate to monitor one or more physical phenomena within an area of interest. WSNs operate as stochastic systems because of randomness in the monitored environments. For long service time and low maintenance cost, WSNs require adaptive and robust methods to address data exchange, topology formulation, resource and power optimization, sensing coverage and object detection, and security challenges. In these problems, sensor nodes are to make optimized decisions from a set of accessible strategies to achieve design goals. This survey reviews numerous applications of the Markov decision process (MDP) framework, a powerful decision-making tool to develop adaptive algorithms and protocols for WSNs. Furthermore, various solution methods are discussed and compared to serve as a guide for using MDPs in WSNs

Seluge++: A Secure Over-the-Air Programming Scheme in Wireless Sensor Networks

Over-the-air dissemination of code updates in wireless sensor networks have been researchers’ point of interest in the last few years, and, more importantly, security challenges toward the remote propagation of code updating have occupied the majority of efforts in this context. Many security models have been proposed to establish a balance between the energy consumption and security strength, having their concentration on the constrained nature of wireless sensor network (WSN) nodes. For authentication purposes, most of them have used a Merkle hash tree to avoid using multiple public cryptography operations. These models mostly have assumed an environment in which security has to be at a standard level. Therefore, they have not investigated the tree structure for mission-critical situations in which security has to be at the maximum possible level (e.g., military applications, healthcare). Considering this, we investigate existing security models used in over-the-air dissemination of code updates for possible vulnerabilities, and then, we provide a set of countermeasures, correspondingly named Security Model Requirements. Based on the investigation, we concentrate on Seluge, one of the existing over-the-air programming schemes, and we propose an improved version of it, named Seluge++, which complies with the Security Model Requirements and replaces the use of the inefficient Merkle tree with a novel method. Analytical and simulation results show the improvements in Seluge++ compared to Seluge