Intrusion Tolerant Routing Protocols for Wireless Sensor Networks

This MSc thesis is focused in the study, solution proposal and experimental evaluation of security solutions for Wireless Sensor Networks (WSNs). The objectives are centered on intrusion tolerant routing services, adapted for the characteristics and requirements of WSN nodes and operation behavior. The main contribution addresses the establishment of pro-active intrusion tolerance properties at the network level, as security mechanisms for the proposal of a reliable and secure routing protocol. Those properties and mechanisms will augment a secure communication base layer supported by light-weigh cryptography methods, to improve the global network resilience capabilities against possible intrusion-attacks on the WSN nodes. Adapting to WSN characteristics, the design of the intended security services also pushes complexity away from resource-poor sensor nodes towards resource-rich and trustable base stations. The devised solution will construct, securely and efficiently, a secure tree-structured routing service for data-dissemination in large scale deployed WSNs. The purpose is to tolerate the damage caused by adversaries modeled according with the Dolev-Yao threat model and ISO X.800 attack typology and framework, or intruders that can compromise maliciously the deployed sensor nodes, injecting, modifying, or blocking packets, jeopardizing the correct behavior of internal network routing processing and topology management. The proposed enhanced mechanisms, as well as the design and implementation of a new intrusiontolerant routing protocol for a large scale WSN are evaluated by simulation. For this purpose, the evaluation is based on a rich simulation environment, modeling networks from hundreds to tens of thousands of wireless sensors, analyzing different dimensions: connectivity conditions, degree-distribution patterns, latency and average short-paths, clustering, reliability metrics and energy cost

Data and resource management in wireless networks via data compression, GPS-free dissemination, and learning

“This research proposes several innovative approaches to collect data efficiently from large scale WSNs. First, a Z-compression algorithm has been proposed which exploits the temporal locality of the multi-dimensional sensing data and adapts the Z-order encoding algorithm to map multi-dimensional data to a one-dimensional data stream. The extended version of Z-compression adapts itself to working in low power WSNs running under low power listening (LPL) mode, and comprehensively analyzes its performance compressing both real-world and synthetic datasets. Second, it proposed an efficient geospatial based data collection scheme for IoTs that reduces redundant rebroadcast of up to 95% by only collecting the data of interest. As most of the low-cost wireless sensors won’t be equipped with a GPS module, the virtual coordinates are used to estimate the locations. The proposed work utilizes the anchor-based virtual coordinate system and DV-Hop (Distance vector of hops to anchors) to estimate the relative location of nodes to anchors. Also, it uses circle and hyperbola constraints to encode the position of interest (POI) and any user-defined trajectory into a data request message which allows only the sensors in the POI and routing trajectory to collect and route. It also provides location anonymity by avoiding using and transmitting GPS location information. This has been extended also for heterogeneous WSNs and refined the encoding algorithm by replacing the circle constraints with the ellipse constraints. Last, it proposes a framework that predicts the trajectory of the moving object using a Sequence-to-Sequence learning (Seq2Seq) model and only wakes-up the sensors that fall within the predicted trajectory of the moving object with a specially designed control packet. It reduces the computation time of encoding geospatial trajectory by more than 90% and preserves the location anonymity for the local edge servers”--Abstract, page iv

Detecting Compromised Nodes in Wireless Sensor Networks

While wireless sensor networks are proving to be a versatile tool, many of the applications in which they are utilized have sensitive data. Therefore, security is crucial in many of these applications. Once a sensor node has been compromised, the security of the network degrades quickly if measures are not taken to deal with this event. There have been many approaches researched to tackle the issue. In this thesis, an anomaly-based intrusion detection protocol is developed to detect compromised nodes in wireless sensor networks. The proposed protocol is implemented after the sensors are deployed into the environment in which they will be used. They will start to learn the normal behavior of each of their neighbors with whom they communicate. All legitimate sensor nodes have the same code running on them. A compromised node that is present in the network is assumed to have different code running on it in order to cause some form of damage to the network. These malicious nodes are detected when one of its neighboring nodes identifies its behavior as deviating from what is expected, or in other words an anomaly. The base station is then contacted to confirm whether the suspected node is in fact compromised. If the base station concludes that the node is compromised, the rest of the network will be informed, and the appropriate actions will be taken. One of the unique features of the algorithm is that it is not only capable of sustaining security in wireless sensor networks, but handling the computing restraints as well as other limitations characteristic of these systems. Extensive simulations are performed to verify the algorithm designed

Intrusion tolerant routing with data consensus in wireless sensor networks

Dissertação para obtenção do Grau de Mestre em Engenharia InformáticaWireless sensor networks (WSNs) are rapidly emerging and growing as an important new area in computing and wireless networking research. Applications of WSNs are numerous, growing, and ranging from small-scale indoor deployment scenarios in homes and buildings to large scale outdoor deployment settings in natural, industrial, military and embedded environments. In a WSN, the sensor nodes collect data to monitor physical conditions or to measure and pre-process physical phenomena, and forward that data to special computing nodes called Syncnodes or Base Stations (BSs). These nodes are eventually interconnected, as gateways, to other processing systems running applications. In large-scale settings, WSNs operate with a large number of sensors – from hundreds to thousands of sensor nodes – organised as ad-hoc multi-hop or mesh networks, working without human supervision. Sensor nodes are very limited in computation, storage, communication and energy resources. These limitations impose particular challenges in designing large scale reliable and secure WSN services and applications. However, as sensors are very limited in their resources they tend to be very cheap. Resilient solutions based on a large number of nodes with replicated capabilities, are possible approaches to address dependability concerns, namely reliability and security requirements and fault or intrusion tolerant network services. This thesis proposes, implements and tests an intrusion tolerant routing service for large-scale dependable WSNs. The service is based on a tree-structured multi-path routing algorithm, establishing multi-hop and multiple disjoint routes between sensors and a group of BSs. The BS nodes work as an overlay, processing intrusion tolerant data consensus over the routed data. In the proposed solution the multiple routes are discovered, selected and established by a self-organisation process. The solution allows the WSN nodes to collect and route data through multiple disjoint routes to the different BSs, with a preventive intrusion tolerance approach, while handling possible Byzantine attacks and failures in sensors and BS with a pro-active recovery strategy supported by intrusion and fault tolerant data-consensus algorithms, performed by the group of Base Stations

Development of a web-based interface for a wireless sensor network monitoring system

In the recent past, wireless sensor technology has undergone advancements in its autonomous data collecting aspects, and has become an area worth investigating in relation to structural monitoring applications. The system described in this thesis aims at acquiring, storing and displaying overhead transmission line related data collected from a wireless sensor network. Open source tools were used in its development and implementation. The inherent linearly aligned topology of transmission line monitoring devices is not without shortcomings; hence analysis of linear node placement, hardware and software components was carried out to determine the feasibility of the system. Their limited data processing capabilities has motivated the development of a post processing wireless sensor application in order to present any collected structural data in an understandable format

New platform for intelligent context-based distributed information fusion

Tesis por compendio de publicaciones[ES]Durante las últimas décadas, las redes de sensores se han vuelto cada vez más importantes y hoy en día están presentes en prácticamente todos los sectores de nuestra sociedad. Su gran capacidad para adquirir datos y actuar sobre el entorno, puede facilitar la construcción de sistemas sensibles al contexto, que permitan un análisis detallado y flexible de los procesos que ocurren y los servicios que se pueden proporcionar a los usuarios. Esta tesis doctoral se presenta en el formato de “Compendio de Artículos”, de tal forma que las principales características de la arquitectura multi-agente distribuida propuesta para facilitar la interconexión de redes de sensores se presentan en tres artículos bien diferenciados. Se ha planteado una arquitectura modular y ligera para dispositivos limitados computacionalmente, diseñando un mecanismo de comunicación flexible que permite la interacción entre diferentes agentes embebidos, desplegados en dispositivos de tamaño reducido. Se propone un nuevo modelo de agente embebido, como mecanismo de extensión para la plataforma PANGEA. Además, se diseña un nuevo modelo de organización virtual de agentes especializada en la fusión de información. De esta forma, los agentes inteligentes tienen en cuenta las características de las organizaciones existentes en el entorno a la hora de proporcionar servicios. El modelo de fusión de información presenta una arquitectura claramente diferenciada en 4 niveles, siendo capaz de obtener la información proporcionada por las redes de sensores (capas inferiores) para ser integrada con organizaciones virtuales de agentes (capas superiores). El filtrado de señales, minería de datos, sistemas de razonamiento basados en casos y otras técnicas de Inteligencia Artificial han sido aplicadas para la consecución exitosa de esta investigación. Una de las principales innovaciones que pretendo con mi estudio, es investigar acerca de nuevos mecanismos que permitan la adición dinámica de redes de sensores combinando diferentes tecnologías con el propósito final de exponer un conjunto de servicios de usuario de forma distribuida. En este sentido, se propondrá una arquitectura multiagente basada en organizaciones virtuales que gestione de forma autónoma la infraestructura subyacente constituida por el hardware y los diferentes sensores

Ambient Agents: Embedded Agents for Remote Control and Monitoring Using the PANGEA Platform

Ambient intelligence has advanced significantly during the last few years. The incorporation of image processing and artificial intelligence techniques have opened the possibility for such aspects as pattern recognition, thus allowing for a better adaptation of these systems. This study presents a new model of an embedded agent especially designed to be implemented in sensing devices with resource constraints. This new model of an agent is integrated within the PANGEA (Platform for the Automatic Construction of Organiztions of Intelligent Agents) platform, an organizational-based platform, defining a new sensor role in the system and aimed at providing contextual information and interacting with the environment. A case study was developed over the PANGEA platform and designed using different agents and sensors responsible for providing user support at home in the event of incidents or emergencies. The system presented in the case study incorporates agents in Arduino hardware devices with recognition modules and illuminated bands; it also incorporates IP cameras programmed for automatic tracking, which can connect remotely in the event of emergencies. The user wears a bracelet, which contains a simple vibration sensor that can receive notifications about the emergency situation

Security techniques for sensor systems and the Internet of Things

Sensor systems are becoming pervasive in many domains, and are recently being generalized by the Internet of Things (IoT). This wide deployment, however, presents significant security issues. We develop security techniques for sensor systems and IoT, addressing all security management phases. Prior to deployment, the nodes need to be hardened. We develop nesCheck, a novel approach that combines static analysis and dynamic checking to efficiently enforce memory safety on TinyOS applications. As security guarantees come at a cost, determining which resources to protect becomes important. Our solution, OptAll, leverages game-theoretic techniques to determine the optimal allocation of security resources in IoT networks, taking into account fixed and variable costs, criticality of different portions of the network, and risk metrics related to a specified security goal. Monitoring IoT devices and sensors during operation is necessary to detect incidents. We design Kalis, a knowledge-driven intrusion detection technique for IoT that does not target a single protocol or application, and adapts the detection strategy to the network features. As the scale of IoT makes the devices good targets for botnets, we design Heimdall, a whitelist-based anomaly detection technique for detecting and protecting against IoT-based denial of service attacks. Once our monitoring tools detect an attack, determining its actual cause is crucial to an effective reaction. We design a fine-grained analysis tool for sensor networks that leverages resident packet parameters to determine whether a packet loss attack is node- or link-related and, in the second case, locate the attack source. Moreover, we design a statistical model for determining optimal system thresholds by exploiting packet parameters variances. With our techniques\u27 diagnosis information, we develop Kinesis, a security incident response system for sensor networks designed to recover from attacks without significant interruption, dynamically selecting response actions while being lightweight in communication and energy overhead

Analysis of the IEEE 802.15.4a ultra wideband physical layer through wireless sensor network simulations in OMNET++

Wireless Sensor Networks are the main representative of pervasive computing in large-scale physical environments. These networks consist of a large number of small, wireless devices embedded in the physical world to be used for surveillance, environmental monitoring or other data capture, processing and transfer applications. Ultra wideband has emerged as one of the newest and most promising concepts for wireless technology. Considering all its advantages it seems a likely communication technology candidate for future wireless sensor networks. This paper considers the viability of ultra wideband technology in wireless sensor networks by employing an IEEE 802.15.4a low-rate ultra wideband physical layer model in the OMNET++ simulation environment. An elaborate investigation into the inner workings of the IEEE 802.15.4a UWB physical layer is performed. Simulation experiments are used to provide a detailed analysis of the performance of the IEEE 802.15.4a UWB physical layer over several communication distances. A proposal for a cognitive, adaptive communication approach to optimize for speed and distance is also presented. AFRIKAANS : Draadlose Sensor Netwerke is die hoof verteenwoordiger vir deurdringende rekenarisering in groot skaal fisiese omgewings. Hierdie tipe netwerke bestaan uit ’n groot aantal klein, draadlose apparate wat in die fisiese wêreld ingesluit word vir die doel van bewaking, omgewings monitering en vele ander data opvang, verwerk en oordrag applikasies. Ultra wyeband het opgestaan as een van die nuutste en mees belowend konsepte vir draadlose kommunikasie tegnologie. As al die voordele van dié kommunikasie tegnologie in ag geneem word, blyk dit om ’n baie goeie kandidaat te wees vir gebruik in toekomstige draadlose sensor netwerke. Hierdie verhandeling oorweeg die vatbaarheid van die gebruik van die ultra wyeband tegnologie in draadlose sensor netwerke deur ’n IEEE 802.15.4a lae-tempo ultra wyeband fisiese laag model in die OMNET++ simulasie omgewing toe te pas. ’n Breedvoerige ondersoek word geloots om die fyn binneste werking van die IEEE 802.15.4a UWB fisiese laag te verstaan. Simulasie eksperimente word gebruik om ’n meer gedetaileerde analiese omtrent die werkverrigting van die IEEE 802.15.4a UWB fisiese laag te verkry oor verskillende kommunikasie afstande. ’n Voorstel vir ’n omgewings bewuste, aanpasbare kommunikasie tegniek word bespreek met die doel om die spoed en afstand van kommunikasie te optimiseer.Dissertation (MEng)--University of Pretoria, 2011.Electrical, Electronic and Computer Engineeringunrestricte