HADES: a Hybrid Anomaly Detection System for Large-Scale Cyber-Physical Systems

Smart cities rely on large-scale heterogeneous distributed systems known as Cyber-Physical Systems (CPS). Information systems based on CPS typically analyse a massive amount of data collected from various data sources that operate under noisy and dynamic conditions. How to determine the quality and reliability of such data is an open research problem that concerns the overall system safety, reliability and security. Our research goal is to tackle the challenge of real-time data quality assessment for large-scale CPS applications with a hybrid anomaly detection system. In this paper we describe the architecture of HADES, our Hybrid Anomaly DEtection System for sensors data monitoring, storage, processing, analysis, and management. Such data will be filtered with correlation-based outlier detection techniques, and then processed by predictive analytics for anomaly detection

무선 통신 기반의 스마트 관개 모니터링 시스템

학위논문 (석사) -- 서울대학교 대학원 : 공과대학 기계공학부, 2020. 8. 안성훈.농업은 개발 도상국들의 경제적 중추임에도 불구하고 대부분의 개발 도상국에서는 자동화된 장비나 데이터 모니터링 등의 지능형 시스템이 거의 적용되지 못한 상태에서 인력에 의해 농업의 모든 과정을 수행하고 있다. 관개는 농작물의 생산성에 결정적 영향을 미치는 필수적인 농업 공정중 하나로서, 연중 강우량의 변동에 대한 대응을 위하여 대부분의 농촌지역에는 농업용수 관개 시스템의 구축을 위해 노력하고 있다. 하지만, 이러한 인력에 의한 농업 방법에서의 관개 시스템은 스마트 센서를 이용한 모니터링 및 제어 등의 기술적 요소가 적용되지 못하여 효율적인 수자원의 활용이 제한되고 이로 인해 농작물의 생산성 또한 낮은 실정이다. 본 논문에서는 개발 도상국의 농촌 지역에서 적용 가능한 무선통신(RF: Radio Frequency) 기반의 스마트 관개 모니터링 시스템 및 요금 선불 시스템을 제안한다. 본 연구는 탄자니아 아루샤(Arusha) 지역의 응구루도토(Ngurudoto) 마을을 대상으로 수행되었다. 본 연구에서 제안하는 시스템은 기상 데이터와 토양 수분 데이터를 하이브리드로 분석하여 농업 용수의 소요를 모니터링한다. 하드웨어 시스템은 기상 측정 컨트롤러, 토양 수분 센서, 수류 센서, 솔레노이드 밸브 및 요금 선불 시스템 등으로 구성된다. 시스템의 각 센서는 무선 통신을 통해 서버로 수집된 데이터를 전송하도록 구축되었는데, 이러한 무선 통신 시스템 아키텍처는 인터넷의 운용이 제한되는 네트워크 오지 지역에 적합하도록 설계되었다. 수집된 데이터에 대한 분석 및 예측은 데이터 분석 알고리즘을 통해 수행되는데, 이를 통하여 농장에 용수를 공급할 시기 및 수량과 함께 요구되는 전력량이 자동으로 판단된다. 한편, 선불시스템은 데이터 분석 결과에 기반하여 용수 사용자가 용수를 공급받기 전에 비용을 우선 지불하도록 개발되었다. 본 시스템의 모든 센서에서 수집된 정보는 실시간으로 모니터링되도록 그래픽 기반의 사용자 인터페이스를 활용하여 정보를 제공한다. 본 연구를 통하여 개발된 무선 통신 기반 스마트 관개 모니터링 시스템은 사용자 중심의 편의성과 경제적인 관개 및 모니터링 시스템을 제공하여 개발 도상국의 경제적 기반인 농업 분야의 발전에 긍정적인 영향을 미칠것으로 기대한다.Agriculture is the backbone of the economy of most developing countries. In these countries, agriculture or farming is mostly done manually with little integration of machinery, intelligent systems and data monitoring. Irrigation is an essential process that influences crop production. The fluctuating amount of rainfall per year has led to the adaption of irrigation systems in most farms. This manual type of farming has proved to yield fair results, however, due to the absence of smart sensors monitoring methods and control, it has failed to be a better type of farming and thus leading to low harvests and draining water sources. In this paper, we introduce an RF (Radio Frequency) based Smart Irrigation Meter System and a water prepayment system in rural areas of Tanzania. Specifically, Ngurudoto area in Arusha region where it will be used as a case study for data collection. The proposed system is hybrid, comprising of both weather data (evapotranspiration) and soil moisture data. The architecture of the system has on-site weather measurement controllers, soil moisture sensors buried on the ground, water flow sensors, solenoid valve, and a prepayment system. These sensors send data to the server through wireless RF based communication architecture, which is suitable for areas where the internet is not reliable and, it is interpreted and decisions and predictions are made on the data by our data analysis algorithm. The decisions made are, when to automatically irrigate a farm and the amount of water and the power needed. Then, the user has to pay first before being supplied with water. All these sensors and water usage are monitored in real time and displaying the information on a custom built graphical user interface. The RF-based smart irrigation monitoring system has both economical and social impact on the developing countries' societies by introducing a convenient and affordable means of Irrigation system and autonomous monitoring.Chapter 1. Introduction 1 Chapter 2 Background of the study and Literature review 3 1.1.Purpose of Research 17 Chapter 3. Requirements and System Design 21 3.1. Key Components 21 3.1.1. System Architecture 21 3.1.2. The Smart Irrigation Meter 22 3.1.2. Parts of Smart Irrigation Meter 23 3.1.3. The pre-paid system and the monitoring device 26 3.2. The Monitoring Application and Cloud Server. 27 Chapter 4. Experiment Setup 30 4.1. Testing Location 30 4.2. Hardware & Software Setup 31 Chapter 5 Results and Analysis 36 5.1 Optimization and anomaly detection algorithm 36 5.1.1 Dynamic Regression Model 36 5.1.2 Nave classifier algorithm for anomaly detection. 38 Chapter 6. Conclusion 44 References 46 초 록 49Maste

Improving System Reliability for Cyber-Physical Systems

Cyber-physical systems (CPS) are systems featuring a tight combination of, and coordination between, the system's computational and physical elements. Cyber-physical systems include systems ranging from critical infrastructure such as a power grid and transportation system to health and biomedical devices. System reliability, i.e., the ability of a system to perform its intended function under a given set of environmental and operational conditions for a given period of time, is a fundamental requirement of cyber-physical systems. An unreliable system often leads to disruption of service, financial cost and even loss of human life. An important and prevalent type of cyber-physical system meets the following criteria: processing large amounts of data; employing software as a system component; running online continuously; having operator-in-the-loop because of human judgment and an accountability requirement for safety critical systems. This thesis aims to improve system reliability for this type of cyber-physical system. To improve system reliability for this type of cyber-physical system, I present a system evaluation approach entitled automated online evaluation (AOE), which is a data-centric runtime monitoring and reliability evaluation approach that works in parallel with the cyber-physical system to conduct automated evaluation along the workflow of the system continuously using computational intelligence and self-tuning techniques and provide operator-in-the-loop feedback on reliability improvement. For example, abnormal input and output data at or between the multiple stages of the system can be detected and flagged through data quality analysis. As a result, alerts can be sent to the operator-in-the-loop. The operator can then take actions and make changes to the system based on the alerts in order to achieve minimal system downtime and increased system reliability. One technique used by the approach is data quality analysis using computational intelligence, which applies computational intelligence in evaluating data quality in an automated and efficient way in order to make sure the running system perform reliably as expected. Another technique used by the approach is self-tuning which automatically self-manages and self-configures the evaluation system to ensure that it adapts itself based on the changes in the system and feedback from the operator. To implement the proposed approach, I further present a system architecture called autonomic reliability improvement system (ARIS). This thesis investigates three hypotheses. First, I claim that the automated online evaluation empowered by data quality analysis using computational intelligence can effectively improve system reliability for cyber-physical systems in the domain of interest as indicated above. In order to prove this hypothesis, a prototype system needs to be developed and deployed in various cyber-physical systems while certain reliability metrics are required to measure the system reliability improvement quantitatively. Second, I claim that the self-tuning can effectively self-manage and self-configure the evaluation system based on the changes in the system and feedback from the operator-in-the-loop to improve system reliability. Third, I claim that the approach is efficient. It should not have a large impact on the overall system performance and introduce only minimal extra overhead to the cyberphysical system. Some performance metrics should be used to measure the efficiency and added overhead quantitatively. Additionally, in order to conduct efficient and cost-effective automated online evaluation for data-intensive CPS, which requires large volumes of data and devotes much of its processing time to I/O and data manipulation, this thesis presents COBRA, a cloud-based reliability assurance framework. COBRA provides automated multi-stage runtime reliability evaluation along the CPS workflow using data relocation services, a cloud data store, data quality analysis and process scheduling with self-tuning to achieve scalability, elasticity and efficiency. Finally, in order to provide a generic way to compare and benchmark system reliability for CPS and to extend the approach described above, this thesis presents FARE, a reliability benchmark framework that employs a CPS reliability model, a set of methods and metrics on evaluation environment selection, failure analysis, and reliability estimation. The main contributions of this thesis include validation of the above hypotheses and empirical studies of ARIS automated online evaluation system, COBRA cloud-based reliability assurance framework for data-intensive CPS, and FARE framework for benchmarking reliability of cyber-physical systems. This work has advanced the state of the art in the CPS reliability research, expanded the body of knowledge in this field, and provided some useful studies for further research

Synoptic analysis techniques for intrusion detection in wireless networks

Current system administrators are missing intrusion alerts hidden by large numbers of false positives. Rather than accumulation more data to identify true alerts, we propose an intrusion detection tool that e?ectively uses select data to provide a picture of ?network health?. Our hypothesis is that by utilizing the data available at both the node and cooperative network levels we can create a synoptic picture of the network providing indications of many intrusions or other network issues. Our major contribution is to provide a revolutionary way to analyze node and network data for patterns, dependence, and e?ects that indicate network issues. We collect node and network data, combine and manipulate it, and tease out information about the state of the network. We present a method based on utilizing the number of packets sent, number of packets received, node reliability, route reliability, and entropy to develop a synoptic picture of the network health in the presence of a sinkhole and a HELLO Flood attacker. This method conserves network throughput and node energy by requiring no additional control messages to be sent between the nodes unless an attacker is suspected. We intend to show that, although the concept of an intrusion detection system is not revolutionary, the method in which we analyze the data for clues about network intrusion and performance is highly innovative

Guest Editorial Special Issue on: Big Data Analytics in Intelligent Systems

The amount of information that is being created, every day, is quickly growing. As such, it is now more common than ever to deal with extremely large datasets. As systems develop and become more intelligent and adaptive, analysing their behaviour is a challenge. The heterogeneity, volume and speed of data generation are increasing rapidly. This is further exacerbated by the use of wireless networks, sensors, smartphones and the Internet. Such systems are capable of generating a phenomenal amount of information and the need to analyse their behaviour, to detect security anomalies or predict future demands for example, is becoming harder. Furthermore, securing such systems is a challenge. As threats evolve, so should security measures develop and adopt increasingly intelligent security techniques. Adaptive systems must be employed and existing methods built upon to provide well-structured defence in depth. Despite the clear need to develop effective protection methods, the task is a difficult one, as there are significant weaknesses in the existing security currently in place. Consequently, this special issue of the Journal of Computer Sciences and Applications discusses big data analytics in intelligent systems. The specific topics of discussion include the Internet of Things, Web Services, Cloud Computing, Security and Interconnected Systems

Utilization of Internet of Things and wireless sensor networks for sustainable smallholder agriculture

Agriculture is the economy’s backbone for most developing countries. Most of these countries suffer from insufficient agricultural production. The availability of real-time, reliable and farm-specific information may significantly contribute to more sufficient and sustained production. Typically, such information is usually fragmented and often does fit one-on-one with the farm or farm plot. Automated, precise and affordable data collection and dissemination tools are vital to bring such information to these levels. The tools must address details of spatial and temporal variability. The Internet of Things (IoT) and wireless sensor networks (WSNs) are useful technology in this respect. This paper investigates the usability of IoT and WSN for smallholder agriculture applications. An in-depth qualitative and quantitative analysis of relevant work over the past decade was conducted. We explore the type and purpose of agricultural parameters, study and describe available resources, needed skills and technological requirements that allow sustained deployment of IoT and WSN technology. Our findings reveal significant gaps in utilization of the technology in the context of smallholder farm practices caused by social, economic, infrastructural and technological barriers. We also identify a significant future opportunity to design and implement affordable and reliable data acquisition tools and frameworks, with a possible integration of citizen science

Survivability modeling for cyber-physical systems subject to data corruption

Cyber-physical critical infrastructures are created when traditional physical infrastructure is supplemented with advanced monitoring, control, computing, and communication capability. More intelligent decision support and improved efficacy, dependability, and security are expected. Quantitative models and evaluation methods are required for determining the extent to which a cyber-physical infrastructure improves on its physical predecessors. It is essential that these models reflect both cyber and physical aspects of operation and failure. In this dissertation, we propose quantitative models for dependability attributes, in particular, survivability, of cyber-physical systems. Any malfunction or security breach, whether cyber or physical, that causes the system operation to depart from specifications will affect these dependability attributes. Our focus is on data corruption, which compromises decision support -- the fundamental role played by cyber infrastructure. The first research contribution of this work is a Petri net model for information exchange in cyber-physical systems, which facilitates i) evaluation of the extent of data corruption at a given time, and ii) illuminates the service degradation caused by propagation of corrupt data through the cyber infrastructure. In the second research contribution, we propose metrics and an evaluation method for survivability, which captures the extent of functionality retained by a system after a disruptive event. We illustrate the application of our methods through case studies on smart grids, intelligent water distribution networks, and intelligent transportation systems. Data, cyber infrastructure, and intelligent control are part and parcel of nearly every critical infrastructure that underpins daily life in developed countries. Our work provides means for quantifying and predicting the service degradation caused when cyber infrastructure fails to serve its intended purpose. It can also serve as the foundation for efforts to fortify critical systems and mitigate inevitable failures --Abstract, page iii

D5.1 SHM digital twin requirements for residential, industrial buildings and bridges

This deliverable presents a report of the needs for structural control on buildings (initial imperfections, deflections at service, stability, rheology) and on bridges (vibrations, modal shapes, deflections, stresses) based on state-of-the-art image-based and sensor-based techniques. To this end, the deliverable identifies and describes strategies that encompass state-of-the-art instrumentation and control for infrastructures (SHM technologies).Objectius de Desenvolupament Sostenible::8 - Treball Decent i Creixement EconòmicObjectius de Desenvolupament Sostenible::9 - Indústria, Innovació i InfraestructuraPreprin