391 research outputs found

    Intrusion Detection for Smart Grid Communication Systems

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    Transformation of the traditional power grid into a smart grid hosts an array of vulnerabilities associated with communication networks. Furthermore, wireless mediums used throughout the smart grid promote an environment where Denial of Service (DoS) attacks are very effective. In wireless mediums, jamming and spoofing attack techniques diminish system operations thus affecting smart grid stability and posing an immediate threat to Confidentiality, Integrity, and Availability (CIA) of the smart grid. Intrusion detection systems (IDS) serve as a primary defense in mitigating network vulnerabilities. In IDS, signatures created from historical data are compared to incoming network traffic to identify abnormalities. In this thesis, intrusion detection algorithms are proposed for attack detection in smart grid networks by means of physical, data link, network, and session layer analysis. Irregularities in these layers provide insight to whether the network is experiencing genuine or malicious activity

    Efficient Control Message Dissemination in Dense Wireless Lighting Networks

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    Modern lighting systems using LED light sources lead to dense lighting installations. The control of such systems using wireless Machine-to-Machine (M2M) where standard LED light sources are replaced by wirelessly controllable LED light sources create new problems which are investigated in this thesis. Current approaches for control message transmission is such networks are based on broadcasting messages among luminaires. However, adequate communication performance - in particular, sufficiently low latency and synchronicity - is difficult to ensure in such networks, in particular, if the network is part of a wireless building management system and carries not only low-latency broadcast messages but also collects data from sensors. In this thesis, the problem of simultaneously controlling dense wireless lighting control networks with a higher number of luminaires is addressed. Extensive computer simulation shows that current state-of-the-art protocols are not suitable for lighting control applications, especially if complex applications are required such as dimming or colour tuning. The novel D³LC-Suite is proposed, which is specially designed for dense wireless lighting control networks. This suite includes three sub-protocols. First, a protocol to organize a network in form of a cluster tree named CIDER. To ensure that intra-cluster messages can be exchanged simultaneously, a weighted colouring algorithm is applied to reduce the inter cluster interference. To disseminate efficiently control messages a protocol is proposed named RLL. The D³LC-Suite is evaluated and validated using different methods. A convergence analysis show that CIDER is able to form a network in a matter of minutes. Simulation results of RLL indicate that this protocol is well suited for dense wireless applications. In extensive experiments, it is shown that the D³LC-Suite advances the current state-of-the-art in several aspects. The suite is able to deliver control messages across multiple hops meeting the requirements of lighting applications. Especially, it provides a deterministic latency, very promising packet loss ratios in low interference environments, and mechanisms for simultaneous message delivery which is important in terms of Quality of Experience (QoE

    Sustainable Task Offloading in UAV Networks via Multi-Agent Reinforcement Learning

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    The recent growth of IoT devices, along with edge computing, has revealed many opportunities for novel applications. Among them, Unmanned Aerial Vehicles (UAVs), which are deployed for surveillance and environmental monitoring, are attracting increasing attention. In this context, typical solutions must deal with events that may change the state of the network, providing a service that continuously maintains a high level of performance. In this paper, we address this problem by proposing a distributed architecture that leverages a Multi-Agent Reinforcement Learning (MARL) technique to dynamically offload tasks from UAVs to the edge cloud. Nodes of the system co-operate to jointly minimize the overall latency perceived by the user and the energy usage on UAVs by continuously learning from the environment the best action, which entails the decision of offloading and, in this case, the best transmission technology, i.e., Wi-Fi or cellular. Results validate our distributed architecture and show the effectiveness of the approach in reaching the above targets

    Efficient Security Protocols for Constrained Devices

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    During the last decades, more and more devices have been connected to the Internet.Today, there are more devices connected to the Internet than humans.An increasingly more common type of devices are cyber-physical devices.A device that interacts with its environment is called a cyber-physical device.Sensors that measure their environment and actuators that alter the physical environment are both cyber-physical devices.Devices connected to the Internet risk being compromised by threat actors such as hackers.Cyber-physical devices have become a preferred target for threat actors since the consequence of an intrusion disrupting or destroying a cyber-physical system can be severe.Cyber attacks against power and energy infrastructure have caused significant disruptions in recent years.Many cyber-physical devices are categorized as constrained devices.A constrained device is characterized by one or more of the following limitations: limited memory, a less powerful CPU, or a limited communication interface.Many constrained devices are also powered by a battery or energy harvesting, which limits the available energy budget.Devices must be efficient to make the most of the limited resources.Mitigating cyber attacks is a complex task, requiring technical and organizational measures.Constrained cyber-physical devices require efficient security mechanisms to avoid overloading the systems limited resources.In this thesis, we present research on efficient security protocols for constrained cyber-physical devices.We have implemented and evaluated two state-of-the-art protocols, OSCORE and Group OSCORE.These protocols allow end-to-end protection of CoAP messages in the presence of untrusted proxies.Next, we have performed a formal protocol verification of WirelessHART, a protocol for communications in an industrial control systems setting.In our work, we present a novel attack against the protocol.We have developed a novel architecture for industrial control systems utilizing the Digital Twin concept.Using a state synchronization protocol, we propagate state changes between the digital and physical twins.The Digital Twin can then monitor and manage devices.We have also designed a protocol for secure ownership transfer of constrained wireless devices. Our protocol allows the owner of a wireless sensor network to transfer control of the devices to a new owner.With a formal protocol verification, we can guarantee the security of both the old and new owners.Lastly, we have developed an efficient Private Stream Aggregation (PSA) protocol.PSA allows devices to send encrypted measurements to an aggregator.The aggregator can combine the encrypted measurements and calculate the decrypted sum of the measurements.No party will learn the measurement except the device that generated it

    Ensuring Security and Availability through Model-Based Cross-Layer Adaptation

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    Abstract. Situation- and resource-aware security is essential for the process control systems, composed of networked entities with sensors and actuators, that monitor and control the national critical infrastructure. However, security cannot be addressed at a single layer because of the inherent dependencies and tradeoffs among crosscutting concerns. Tech-niques applied at one layer to improve security affect security, timing, and power consumption at other layers. This paper argues for an integrated treatment of security across multiple layers of abstraction (application, middleware, operating system including network stack, and hardware). An important step in realizing this integrated treatment of situation-and resource-aware security is first understanding the cross-layer inter-actions between security policies and then exploiting these interactions to design efficient adaptation strategies (i) to balance security, quality of service, and energy needs, and (ii) to maximize system availability. We propose a novel approach that employs a compositional method within an iterative tuning framework based on lightweight formal methods with dynamic adaptation.

    Contributions to Securing Software Updates in IoT

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    The Internet of Things (IoT) is a large network of connected devices. In IoT, devices can communicate with each other or back-end systems to transfer data or perform assigned tasks. Communication protocols used in IoT depend on target applications but usually require low bandwidth. On the other hand, IoT devices are constrained, having limited resources, including memory, power, and computational resources. Considering these limitations in IoT environments, it is difficult to implement best security practices. Consequently, network attacks can threaten devices or the data they transfer. Thus it is crucial to react quickly to emerging vulnerabilities. These vulnerabilities should be mitigated by firmware updates or other necessary updates securely. Since IoT devices usually connect to the network wirelessly, such updates can be performed Over-The-Air (OTA). This dissertation presents contributions to enable secure OTA software updates in IoT. In order to perform secure updates, vulnerabilities must first be identified and assessed. In this dissertation, first, we present our contribution to designing a maturity model for vulnerability handling. Next, we analyze and compare common communication protocols and security practices regarding energy consumption. Finally, we describe our designed lightweight protocol for OTA updates targeting constrained IoT devices. IoT devices and back-end systems often use incompatible protocols that are unable to interoperate securely. This dissertation also includes our contribution to designing a secure protocol translator for IoT. This translation is performed inside a Trusted Execution Environment (TEE) with TLS interception. This dissertation also contains our contribution to key management and key distribution in IoT networks. In performing secure software updates, the IoT devices can be grouped since the updates target a large number of devices. Thus, prior to deploying updates, a group key needs to be established among group members. In this dissertation, we present our designed secure group key establishment scheme. Symmetric key cryptography can help to save IoT device resources at the cost of increased key management complexity. This trade-off can be improved by integrating IoT networks with cloud computing and Software Defined Networking (SDN).In this dissertation, we use SDN in cloud networks to provision symmetric keys efficiently and securely. These pieces together help software developers and maintainers identify vulnerabilities, provision secret keys, and perform lightweight secure OTA updates. Furthermore, they help devices and systems with incompatible protocols to be able to interoperate

    Data Driven Energy Efficiency Strategies for Commercial Buildings Using Occupancy Information

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    Most building automation systems operate with settings based on design assumptions with fixed operational schedules and fixed occupancy, when in fact both schedules and occupancy levels vary dynamically. In particular, the heating ventilation and air conditioning (HVAC) system provides a minimum ventilation airflow calculated for the maximum room capacity, when rooms are rarely fully occupied. Energy is wasted by over-supplying and conditioning air that is not required, which also leads to thermal discomfort. In higher educational institutions, where classroom occupancy goals vary from 60% to 80% of their maximum capacity, potential savings are substantial. Existing occupancy and schedule information from academic registration can be integrated with the facility data and the building automation system, allowing dynamic resetting of the controllers. This dissertation provides a methodology to reduce HVAC energy consumption by using occupancy information from the academic registrar. The methodology integrates three energy conservation strategies: shortening schedules, modifying thermostat settings and reducing the minimum airflow. Analysis of the proposed solution includes an economic benefit estimation at a campus level with validation through an experimental study performed on a LEED platinum building. Experiment results achieved an electricity savings of 39% and a natural gas savings of 31% for classrooms’ air conditioning consumption. Extending these savings to the campus level yields 164 MWh of electricity savings per year, 48MMBtu natural gas savings per year, 35.16 MTCO2 of greenhouse gases emissions reduction per year, approximately $20k economic savings per year

    A study of the applicability of software-defined networking in industrial networks

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    173 p.Las redes industriales interconectan sensores y actuadores para llevar a cabo funciones de monitorización, control y protección en diferentes entornos, tales como sistemas de transporte o sistemas de automatización industrial. Estos sistemas ciberfísicos generalmente están soportados por múltiples redes de datos, ya sean cableadas o inalámbricas, a las cuales demandan nuevas prestaciones, de forma que el control y gestión de tales redes deben estar acoplados a las condiciones del propio sistema industrial. De este modo, aparecen requisitos relacionados con la flexibilidad, mantenibilidad y adaptabilidad, al mismo tiempo que las restricciones de calidad de servicio no se vean afectadas. Sin embargo, las estrategias de control de red tradicionales generalmente no se adaptan eficientemente a entornos cada vez más dinámicos y heterogéneos.Tras definir un conjunto de requerimientos de red y analizar las limitaciones de las soluciones actuales, se deduce que un control provisto independientemente de los propios dispositivos de red añadiría flexibilidad a dichas redes. Por consiguiente, la presente tesis explora la aplicabilidad de las redes definidas por software (Software-Defined Networking, SDN) en sistemas de automatización industrial. Para llevar a cabo este enfoque, se ha tomado como caso de estudio las redes de automatización basadas en el estándar IEC 61850, el cual es ampliamente usado en el diseño de las redes de comunicaciones en sistemas de distribución de energía, tales como las subestaciones eléctricas. El estándar IEC 61850 define diferentes servicios y protocolos con altos requisitos en terminos de latencia y disponibilidad de la red, los cuales han de ser satisfechos mediante técnicas de ingeniería de tráfico. Como resultado, aprovechando la flexibilidad y programabilidad ofrecidas por las redes definidas por software, en esta tesis se propone una arquitectura de control basada en el protocolo OpenFlow que, incluyendo tecnologías de gestión y monitorización de red, permite establecer políticas de tráfico acorde a su prioridad y al estado de la red.Además, las subestaciones eléctricas son un ejemplo representativo de infraestructura crítica, que son aquellas en las que un fallo puede resultar en graves pérdidas económicas, daños físicos y materiales. De esta forma, tales sistemas deben ser extremadamente seguros y robustos, por lo que es conveniente la implementación de topologías redundantes que ofrezcan un tiempo de reacción ante fallos mínimo. Con tal objetivo, el estándar IEC 62439-3 define los protocolos Parallel Redundancy Protocol (PRP) y High-availability Seamless Redundancy (HSR), los cuales garantizan un tiempo de recuperación nulo en caso de fallo mediante la redundancia activa de datos en redes Ethernet. Sin embargo, la gestión de redes basadas en PRP y HSR es estática e inflexible, lo que, añadido a la reducción de ancho de banda debida la duplicación de datos, hace difícil un control eficiente de los recursos disponibles. En dicho sentido, esta tesis propone control de la redundancia basado en el paradigma SDN para un aprovechamiento eficiente de topologías malladas, al mismo tiempo que se garantiza la disponibilidad de las aplicaciones de control y monitorización. En particular, se discute cómo el protocolo OpenFlow permite a un controlador externo configurar múltiples caminos redundantes entre dispositivos con varias interfaces de red, así como en entornos inalámbricos. De esta forma, los servicios críticos pueden protegerse en situaciones de interferencia y movilidad.La evaluación de la idoneidad de las soluciones propuestas ha sido llevada a cabo, principalmente, mediante la emulación de diferentes topologías y tipos de tráfico. Igualmente, se ha estudiado analítica y experimentalmente cómo afecta a la latencia el poder reducir el número de saltos en las comunicaciones con respecto al uso de un árbol de expansión, así como balancear la carga en una red de nivel 2. Además, se ha realizado un análisis de la mejora de la eficiencia en el uso de los recursos de red y la robustez alcanzada con la combinación de los protocolos PRP y HSR con un control llevado a cabo mediante OpenFlow. Estos resultados muestran que el modelo SDN podría mejorar significativamente las prestaciones de una red industrial de misión crítica
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