A Novel Locality Algorithm and Peer-to-Peer Communication Infrastructure for Optimizing Network Performance in Smart Microgrids

[EN] Peer-to-Peer (P2P) overlay communications networks have emerged as a new paradigm for implementing distributed services in microgrids due to their potential benefits: they are robust, scalable, fault-tolerant, and they can route messages even with a large number of nodes which are frequently entering or leaving from the network. However, current P2P systems have been mainly developed for file sharing or cycle sharing applications where the processes of searching and managing resources are not optimized. Locality algorithms have gained a lot of attention due to their potential to provide an optimized path to groups with similar interests for routing messages in order to get better network performance. This paper develops a fully functional decentralized communication architecture with a new P2P locality algorithm and a specific protocol for monitoring and control of microgrids. Experimental results show that the proposed locality algorithm reduces the number of lookup messages and the lookup delay time. Moreover, the proposed communication architecture heavily depends of the lookup used algorithm as well as the placement of the communication layers within the architecture. Experimental results will show that the proposed techniques meet the network requirements of smart microgrids even with a large number of nodes on stream.This work is supported by the Spanish Ministry of Economy and Competitiveness (MINECO) and the European Regional Development Fund (ERDF) under Grant ENE2015-64087-C2-2R. This work is supported by the Spanish Ministry of Economy and Competitiveness (MINECO) under BES-2013-064539.Marzal-Romeu, S.; González-Medina, R.; Salas-Puente, RA.; Figueres Amorós, E.; Garcerá, G. (2017). A Novel Locality Algorithm and Peer-to-Peer Communication Infrastructure for Optimizing Network Performance in Smart Microgrids. Energies. 10(9):1-25. https://doi.org/10.3390/en10091275S125109Khan, R. H., & Khan, J. Y. (2013). A comprehensive review of the application characteristics and traffic requirements of a smart grid communications network. Computer Networks, 57(3), 825-845. doi:10.1016/j.comnet.2012.11.002Dada, J. O. (2014). Towards understanding the benefits and challenges of Smart/Micro-Grid for electricity supply system in Nigeria. Renewable and Sustainable Energy Reviews, 38, 1003-1014. doi:10.1016/j.rser.2014.07.077Lidula, N. W. A., & Rajapakse, A. D. (2011). Microgrids research: A review of experimental microgrids and test systems. Renewable and Sustainable Energy Reviews, 15(1), 186-202. doi:10.1016/j.rser.2010.09.041Hussain, A., Arif, S. M., Aslam, M., & Shah, S. D. A. (2017). Optimal siting and sizing of tri-generation equipment for developing an autonomous community microgrid considering uncertainties. Sustainable Cities and Society, 32, 318-330. doi:10.1016/j.scs.2017.04.004Dehghanpour, K., Colson, C., & Nehrir, H. (2017). A Survey on Smart Agent-Based Microgrids for Resilient/Self-Healing Grids. Energies, 10(5), 620. doi:10.3390/en10050620Palizban, O., Kauhaniemi, K., & Guerrero, J. M. (2014). Microgrids in active network management – part II: System operation, power quality and protection. Renewable and Sustainable Energy Reviews, 36, 440-451. doi:10.1016/j.rser.2014.04.048Shi, W., Li, N., Chu, C.-C., & Gadh, R. (2017). Real-Time Energy Management in Microgrids. IEEE Transactions on Smart Grid, 8(1), 228-238. doi:10.1109/tsg.2015.2462294Deng, R., Yang, Z., Chow, M.-Y., & Chen, J. (2015). A Survey on Demand Response in Smart Grids: Mathematical Models and Approaches. IEEE Transactions on Industrial Informatics, 11(3), 570-582. doi:10.1109/tii.2015.2414719Moazami Goodarzi, H., & Kazemi, M. (2017). A Novel Optimal Control Method for Islanded Microgrids Based on Droop Control Using the ICA-GA Algorithm. Energies, 10(4), 485. doi:10.3390/en10040485Erol-Kantarci, M., Kantarci, B., & Mouftah, H. (2011). Reliable overlay topology design for the smart microgrid network. IEEE Network, 25(5), 38-43. doi:10.1109/mnet.2011.6033034Hassan Youssef, K. (2016). Optimal management of unbalanced smart microgrids for scheduled and unscheduled multiple transitions between grid-connected and islanded modes. Electric Power Systems Research, 141, 104-113. doi:10.1016/j.epsr.2016.07.015Giotitsas, C., Pazaitis, A., & Kostakis, V. (2015). A peer-to-peer approach to energy production. Technology in Society, 42, 28-38. doi:10.1016/j.techsoc.2015.02.002Kazmi, S. A. A., Shahzad, M. K., Khan, A. Z., & Shin, D. R. (2017). Smart Distribution Networks: A Review of Modern Distribution Concepts from a Planning Perspective. Energies, 10(4), 501. doi:10.3390/en10040501Werth, A., Andre, A., Kawamoto, D., Morita, T., Tajima, S., Tokoro, M., … Tanaka, K. (2018). Peer-to-Peer Control System for DC Microgrids. IEEE Transactions on Smart Grid, 9(4), 3667-3675. doi:10.1109/tsg.2016.2638462Deconinck, G., Vanthournout, K., Beitollahi, H., Qui, Z., Duan, R., Nauwelaers, B., … Belmans, R. (2008). A Robust Semantic Overlay Network for Microgrid Control Applications. Architecting Dependable Systems V, 101-123. doi:10.1007/978-3-540-85571-2_5Bandara, H. M. N. D., & Jayasumana, A. P. (2012). Collaborative applications over peer-to-peer systems–challenges and solutions. Peer-to-Peer Networking and Applications, 6(3), 257-276. doi:10.1007/s12083-012-0157-3Palizban, O., & Kauhaniemi, K. (2015). Hierarchical control structure in microgrids with distributed generation: Island and grid-connected mode. Renewable and Sustainable Energy Reviews, 44, 797-813. doi:10.1016/j.rser.2015.01.008Khatibzadeh, A., Besmi, M., Mahabadi, A., & Reza Haghifam, M. (2017). Multi-Agent-Based Controller for Voltage Enhancement in AC/DC Hybrid Microgrid Using Energy Storages. Energies, 10(2), 169. doi:10.3390/en10020169Planas, E., Gil-de-Muro, A., Andreu, J., Kortabarria, I., & Martínez de Alegría, I. (2013). General aspects, hierarchical controls and droop methods in microgrids: A review. Renewable and Sustainable Energy Reviews, 17, 147-159. doi:10.1016/j.rser.2012.09.032Olivares, D. E., Mehrizi-Sani, A., Etemadi, A. H., Canizares, C. A., Iravani, R., Kazerani, M., … Hatziargyriou, N. D. (2014). Trends in Microgrid Control. IEEE Transactions on Smart Grid, 5(4), 1905-1919. doi:10.1109/tsg.2013.2295514Vandoorn, T. L., Vasquez, J. C., De Kooning, J., Guerrero, J. M., & Vandevelde, L. (2013). Microgrids: Hierarchical Control and an Overview of the Control and Reserve Management Strategies. IEEE Industrial Electronics Magazine, 7(4), 42-55. doi:10.1109/mie.2013.2279306Zhou, B., Li, W., Chan, K. W., Cao, Y., Kuang, Y., Liu, X., & Wang, X. (2016). Smart home energy management systems: Concept, configurations, and scheduling strategies. Renewable and Sustainable Energy Reviews, 61, 30-40. doi:10.1016/j.rser.2016.03.047Ancillotti, E., Bruno, R., & Conti, M. (2013). The role of communication systems in smart grids: Architectures, technical solutions and research challenges. Computer Communications, 36(17-18), 1665-1697. doi:10.1016/j.comcom.2013.09.004Llaria, A., Terrasson, G., Curea, O., & Jiménez, J. (2016). Application of Wireless Sensor and Actuator Networks to Achieve Intelligent Microgrids: A Promising Approach towards a Global Smart Grid Deployment. Applied Sciences, 6(3), 61. doi:10.3390/app6030061Luna, A. C., Diaz, N. L., Graells, M., Vasquez, J. C., & Guerrero, J. M. (2016). Cooperative energy management for a cluster of households prosumers. IEEE Transactions on Consumer Electronics, 62(3), 235-242. doi:10.1109/tce.2016.7613189Gungor, V. C., Lu, B., & Hancke, G. P. (2010). Opportunities and Challenges of Wireless Sensor Networks in Smart Grid. IEEE Transactions on Industrial Electronics, 57(10), 3557-3564. doi:10.1109/tie.2009.2039455Zhao, C., He, J., Cheng, P., & Chen, J. (2017). Consensus-Based Energy Management in Smart Grid With Transmission Losses and Directed Communication. IEEE Transactions on Smart Grid, 8(5), 2049-2061. doi:10.1109/tsg.2015.2513772Lo, C.-H., & Ansari, N. (2013). Decentralized Controls and Communications for Autonomous Distribution Networks in Smart Grid. IEEE Transactions on Smart Grid, 4(1), 66-77. doi:10.1109/tsg.2012.2228282Li, C., Savaghebi, M., Guerrero, J., Coelho, E., & Vasquez, J. (2016). Operation Cost Minimization of Droop-Controlled AC Microgrids Using Multiagent-Based Distributed Control. Energies, 9(9), 717. doi:10.3390/en9090717Wu, X., Jiang, P., & Lu, J. (2014). Multiagent-Based Distributed Load Shedding for Islanded Microgrids. Energies, 7(9), 6050-6062. doi:10.3390/en7096050Kantamneni, A., Brown, L. E., Parker, G., & Weaver, W. W. (2015). Survey of multi-agent systems for microgrid control. Engineering Applications of Artificial Intelligence, 45, 192-203. doi:10.1016/j.engappai.2015.07.005Lopes, A. L., & Botelho, L. M. (2008). Improving Multi-Agent Based Resource Coordination in Peer-to-Peer Networks. Journal of Networks, 3(2). doi:10.4304/jnw.3.2.38-47Cameron, A., Stumptner, M., Nandagopal, N., Mayer, W., & Mansell, T. (2015). Rule-based peer-to-peer framework for decentralised real-time service oriented architectures. Science of Computer Programming, 97, 202-234. doi:10.1016/j.scico.2014.06.005Zhang, C., Wu, J., Cheng, M., Zhou, Y., & Long, C. (2016). A Bidding System for Peer-to-Peer Energy Trading in a Grid-connected Microgrid. Energy Procedia, 103, 147-152. doi:10.1016/j.egypro.2016.11.264Malatras, A. (2015). State-of-the-art survey on P2P overlay networks in pervasive computing environments. Journal of Network and Computer Applications, 55, 1-23. doi:10.1016/j.jnca.2015.04.014Eng Keong Lua, Crowcroft, J., Pias, M., Sharma, R., & Lim, S. (2005). A survey and comparison of peer-to-peer overlay network schemes. IEEE Communications Surveys & Tutorials, 7(2), 72-93. doi:10.1109/comst.2005.1610546Xu, J., Kumar, A., & Yu, X. (2004). On the Fundamental Tradeoffs Between Routing Table Size and Network Diameter in Peer-to-Peer Networks. IEEE Journal on Selected Areas in Communications, 22(1), 151-163. doi:10.1109/jsac.2003.818805Stoica, I., Morris, R., Karger, D., Kaashoek, M. F., & Balakrishnan, H. (2001). Chord. ACM SIGCOMM Computer Communication Review, 31(4), 149-160. doi:10.1145/964723.383071Rowstron, A., & Druschel, P. (2001). Pastry: Scalable, Decentralized Object Location, and Routing for Large-Scale Peer-to-Peer Systems. Lecture Notes in Computer Science, 329-350. doi:10.1007/3-540-45518-3_18Yuh-Jzer Joung, Li-Wei Yang, & Chien-Tse Fang. (2007). Keyword search in DHT-based peer-to-peer networks. IEEE Journal on Selected Areas in Communications, 25(1), 46-61. doi:10.1109/jsac.2007.070106Stoica, I., Morris, R., Liben-Nowell, D., Karger, D. R., Kaashoek, M. F., Dabek, F., & Balakrishnan, H. (2003). Chord: a scalable peer-to-peer lookup protocol for internet applications. IEEE/ACM Transactions on Networking, 11(1), 17-32. doi:10.1109/tnet.2002.808407Gottron, C., König, A., & Steinmetz, R. (2010). A Survey on Security in Mobile Peer-to-Peer Architectures—Overlay-Based vs. Underlay-Based Approaches. Future Internet, 2(4), 505-532. doi:10.3390/fi2040505Seyedi, Y., Karimi, H., & Guerrero, J. M. (2017). Centralized Disturbance Detection in Smart Microgrids With Noisy and Intermittent Synchrophasor Data. IEEE Transactions on Smart Grid, 8(6), 2775-2783. doi:10.1109/tsg.2016.2539947Youssef, T., Elsayed, A., & Mohammed, O. (2016). Data Distribution Service-Based Interoperability Framework for Smart Grid Testbed Infrastructure. Energies, 9(3), 150. doi:10.3390/en9030150Liu, X., Xia, H., & Chien, A. A. (2004). Validating and Scaling the MicroGrid: A Scientific Instrument for Grid Dynamics. Journal of Grid Computing, 2(2), 141-161. doi:10.1007/s10723-004-4200-3Kansal, P., & Bose, A. (2012). Bandwidth and Latency Requirements for Smart Transmission Grid Applications. IEEE Transactions on Smart Grid, 3(3), 1344-1352. doi:10.1109/tsg.2012.2197229Kuo, M.-T., & Lu, S.-D. (2013). Design and Implementation of Real-Time Intelligent Control and Structure Based on Multi-Agent Systems in Microgrids. Energies, 6(11), 6045-6059. doi:10.3390/en6116045Del Val, E., Rebollo, M., & Botti, V. (2012). Enhancing decentralized service discovery in open service-oriented multi-agent systems. Autonomous Agents and Multi-Agent Systems, 28(1), 1-30. doi:10.1007/s10458-012-9210-0Howell, S., Rezgui, Y., Hippolyte, J.-L., Jayan, B., & Li, H. (2017). Towards the next generation of smart grids: Semantic and holonic multi-agent management of distributed energy resources. Renewable and Sustainable Energy Reviews, 77, 193-214. doi:10.1016/j.rser.2017.03.107Frey, S., Diaconescu, A., Menga, D., & Demeure, I. (2015). A Generic Holonic Control Architecture for Heterogeneous Multiscale and Multiobjective Smart Microgrids. ACM Transactions on Autonomous and Adaptive Systems, 10(2), 1-21. doi:10.1145/2700326Miers, C., Simplicio, M., Gallo, D., Carvalho, T., Bressan, G., Souza, V., … Damola, A. (2010). A Taxonomy for Locality Algorithms on Peer-to-Peer Networks. IEEE Latin America Transactions, 8(4), 323-331. doi:10.1109/tla.2010.5595121Porsinger, T., Janik, P., Leonowicz, Z., & Gono, R. (2017). Modelling and Optimization in Microgrids. Energies, 10(4), 523. doi:10.3390/en10040523Ali, M., Zakariya, M., Asif, M., & Ullah, A. (2012). TCP/IP Based Intelligent Load Management System in Micro-Grids Network Using MATLAB/Simulink. Energy and Power Engineering, 04(04), 283-289. doi:10.4236/epe.2012.44038Shin, I.-J., Song, B.-K., & Eom, D.-S. (2017). International Electronical Committee (IEC) 61850 Mapping with Constrained Application Protocol (CoAP) in Smart Grids Based European Telecommunications Standard Institute Machine-to-Machine (M2M) Environment. Energies, 10(3), 393. doi:10.3390/en10030393Loh, P. C., Li, D., Chai, Y. K., & Blaabjerg, F. (2013). Autonomous Operation of Hybrid Microgrid With AC and DC Subgrids. IEEE Transactions on Power Electronics, 28(5), 2214-2223. doi:10.1109/tpel.2012.2214792Overlay networks for smart gridshttp://users.atlantis.ugent.be/cdvelder/papers/2013/wauters2013sgv.pdfEugster, P. T., Felber, P. A., Guerraoui, R., & Kermarrec, A.-M. (2003). The many faces of publish/subscribe. ACM Computing Surveys, 35(2), 114-131. doi:10.1145/857076.857078Ali, I. (2012). High-speed Peer-to-peer Communication based Protection Scheme Implementation and Testing in Laboratory. International Journal of Computer Applications, 38(4), 16-24. doi:10.5120/4596-6793Yoo, B.-K., Yang, S.-H., Yang, H.-S., Kim, W.-Y., Jeong, Y.-S., Han, B.-M., & Jang, K.-S. (2011). Communication Architecture of the IEC 61850-based Micro Grid System. Journal of Electrical Engineering and Technology, 6(5), 605-612. doi:10.5370/jeet.2011.6.5.605Dou, X., Quan, X., Wu, Z., Hu, M., Yang, K., Yuan, J., & Wang, M. (2014). Hybrid Multi-Agent Control in Microgrids: Framework, Models and Implementations Based on IEC 61850. Energies, 8(1), 31-58. doi:10.3390/en801003

Data Acquisition Applications

Data acquisition systems have numerous applications. This book has a total of 13 chapters and is divided into three sections: Industrial applications, Medical applications and Scientific experiments. The chapters are written by experts from around the world, while the targeted audience for this book includes professionals who are designers or researchers in the field of data acquisition systems. Faculty members and graduate students could also benefit from the book

System-on-chip architecture for secure sub-microsecond synchronization systems

213 p.En esta tesis, se pretende abordar los problemas que conlleva la protección cibernética del Precision Time Protocol (PTP). Éste es uno de los protocolos de comunicación más sensibles de entre los considerados por los organismos de estandarización para su aplicación en las futuras Smart Grids o redes eléctricas inteligentes. PTP tiene como misión distribuir una referencia de tiempo desde un dispositivo maestro al resto de dispositivos esclavos, situados dentro de una misma red, de forma muy precisa. El protocolo es altamente vulnerable, ya que introduciendo tan sólo un error de tiempo de un microsegundo, pueden causarse graves problemas en las funciones de protección del equipamiento eléctrico, o incluso detener su funcionamiento. Para ello, se propone una nueva arquitectura System-on-Chip basada en dispositivos reconfigurables, con el objetivo de integrar el protocolo PTP y el conocido estándar de seguridad MACsec para redes Ethernet. La flexibilidad que los modernos dispositivos reconfigurables proporcionan, ha sido aprovechada para el diseño de una arquitectura en la que coexisten procesamiento hardware y software. Los resultados experimentales avalan la viabilidad de utilizar MACsec para proteger la sincronización en entornos industriales, sin degradar la precisión del protocolo

Fingerprinting Vulnerabilities in Intelligent Electronic Device Firmware

Modern smart grid deployments heavily rely on the advanced capabilities that Intelligent Electronic Devices (IEDs) provide. Furthermore, these devices firmware often contain critical vulnerabilities that if exploited could cause large impacts on national economic security, and national safety. As such, a scalable domain specific approach is required in order to assess the security of IED firmware. In order to resolve this lack of an appropriate methodology, we present a scalable vulnerable function identification framework. It is specifically designed to analyze IED firmware and binaries that employ the ARM CPU architecture. Its core functionality revolves around a multi-stage detection methodology that is specifically designed to resolve the lack of specialization that limits other general-purpose approaches. This is achieved by compiling an extensive database of IED specific vulnerabilities and domain specific firmware that is evaluated. Its analysis approach is composed of three stages that leverage function syntactic, semantic, structural and statistical features in order to identify vulnerabilities. As such it (i) first filters out dissimilar functions based on a group of heterogeneous features, (ii) it then further filters out dissimilar functions based on their execution paths, and (iii) it finally identifies candidate functions based on fuzzy graph matching . In order to validate our methodologies capabilities, it is implemented as a binary analysis framework entitled BinArm. The resulting algorithm is then put through a rigorous set of evaluations that demonstrate its capabilities. These include the capability to identify vulnerabilities within a given IED firmware image with a total accuracy of 0.92

System-on-chip architecture for secure sub-microsecond synchronization systems

213 p.En esta tesis, se pretende abordar los problemas que conlleva la protección cibernética del Precision Time Protocol (PTP). Éste es uno de los protocolos de comunicación más sensibles de entre los considerados por los organismos de estandarización para su aplicación en las futuras Smart Grids o redes eléctricas inteligentes. PTP tiene como misión distribuir una referencia de tiempo desde un dispositivo maestro al resto de dispositivos esclavos, situados dentro de una misma red, de forma muy precisa. El protocolo es altamente vulnerable, ya que introduciendo tan sólo un error de tiempo de un microsegundo, pueden causarse graves problemas en las funciones de protección del equipamiento eléctrico, o incluso detener su funcionamiento. Para ello, se propone una nueva arquitectura System-on-Chip basada en dispositivos reconfigurables, con el objetivo de integrar el protocolo PTP y el conocido estándar de seguridad MACsec para redes Ethernet. La flexibilidad que los modernos dispositivos reconfigurables proporcionan, ha sido aprovechada para el diseño de una arquitectura en la que coexisten procesamiento hardware y software. Los resultados experimentales avalan la viabilidad de utilizar MACsec para proteger la sincronización en entornos industriales, sin degradar la precisión del protocolo

System-on-chip architecture for secure sub-microsecond synchronization systems

213 p.En esta tesis, se pretende abordar los problemas que conlleva la protección cibernética del Precision Time Protocol (PTP). Éste es uno de los protocolos de comunicación más sensibles de entre los considerados por los organismos de estandarización para su aplicación en las futuras Smart Grids o redes eléctricas inteligentes. PTP tiene como misión distribuir una referencia de tiempo desde un dispositivo maestro al resto de dispositivos esclavos, situados dentro de una misma red, de forma muy precisa. El protocolo es altamente vulnerable, ya que introduciendo tan sólo un error de tiempo de un microsegundo, pueden causarse graves problemas en las funciones de protección del equipamiento eléctrico, o incluso detener su funcionamiento. Para ello, se propone una nueva arquitectura System-on-Chip basada en dispositivos reconfigurables, con el objetivo de integrar el protocolo PTP y el conocido estándar de seguridad MACsec para redes Ethernet. La flexibilidad que los modernos dispositivos reconfigurables proporcionan, ha sido aprovechada para el diseño de una arquitectura en la que coexisten procesamiento hardware y software. Los resultados experimentales avalan la viabilidad de utilizar MACsec para proteger la sincronización en entornos industriales, sin degradar la precisión del protocolo

Secure Control and Operation of Energy Cyber-Physical Systems Through Intelligent Agents

The operation of the smart grid is expected to be heavily reliant on microprocessor-based control. Thus, there is a strong need for interoperability standards to address the heterogeneous nature of the data in the smart grid. In this research, we analyzed in detail the security threats of the Generic Object Oriented Substation Events (GOOSE) and Sampled Measured Values (SMV) protocol mappings of the IEC 61850 data modeling standard, which is the most widely industry-accepted standard for power system automation and control. We found that there is a strong need for security solutions that are capable of defending the grid against cyber-attacks, minimizing the damage in case a cyber-incident occurs, and restoring services within minimal time. To address these risks, we focused on correlating cyber security algorithms with physical characteristics of the power system by developing intelligent agents that use this knowledge as an important second line of defense in detecting malicious activity. This will complement the cyber security methods, including encryption and authentication. Firstly, we developed a physical-model-checking algorithm, which uses artificial neural networks to identify switching-related attacks on power systems based on load flow characteristics. Secondly, the feasibility of using neural network forecasters to detect spoofed sampled values was investigated. We showed that although such forecasters have high spoofed-data-detection accuracy, they are prone to the accumulation of forecasting error. In this research, we proposed an algorithm to detect the accumulation of the forecasting error based on lightweight statistical indicators. The effectiveness of the proposed algorithms was experimentally verified on the Smart Grid testbed at FIU. The test results showed that the proposed techniques have a minimal detection latency, in the range of microseconds. Also, in this research we developed a network-in-the-loop co-simulation platform that seamlessly integrates the components of the smart grid together, especially since they are governed by different regulations and owned by different entities. Power system simulation software, microcontrollers, and a real communication infrastructure were combined together to provide a cohesive smart grid platform. A data-centric communication scheme was selected to provide an interoperability layer between multi-vendor devices, software packages, and to bridge different protocols together

Cyber Security of Critical Infrastructures

Critical infrastructures are vital assets for public safety, economic welfare, and the national security of countries. The vulnerabilities of critical infrastructures have increased with the widespread use of information technologies. As Critical National Infrastructures are becoming more vulnerable to cyber-attacks, their protection becomes a significant issue for organizations as well as nations. The risks to continued operations, from failing to upgrade aging infrastructure or not meeting mandated regulatory regimes, are considered highly significant, given the demonstrable impact of such circumstances. Due to the rapid increase of sophisticated cyber threats targeting critical infrastructures with significant destructive effects, the cybersecurity of critical infrastructures has become an agenda item for academics, practitioners, and policy makers. A holistic view which covers technical, policy, human, and behavioural aspects is essential to handle cyber security of critical infrastructures effectively. Moreover, the ability to attribute crimes to criminals is a vital element of avoiding impunity in cyberspace. In this book, both research and practical aspects of cyber security considerations in critical infrastructures are presented. Aligned with the interdisciplinary nature of cyber security, authors from academia, government, and industry have contributed 13 chapters. The issues that are discussed and analysed include cybersecurity training, maturity assessment frameworks, malware analysis techniques, ransomware attacks, security solutions for industrial control systems, and privacy preservation methods

Honeypot-based Security Enhancements for Information Systems

The purpose of this thesis is to explore honeypot-based security enhancements for information systems. First, we provide a comprehensive survey of the research that has been carried out on honeypots and honeynets for Internet of Things (IoT), Industrial Internet of Things (IIoT), and Cyber-physical Systems (CPS). We provide a taxonomy and extensive analysis of the existing honeypots and honeynets, state key design factors for the state-of-the-art honeypot/honeynet research and outline open issues. Second, we propose S-Pot, a smart honeypot framework based on open-source resources. S-Pot uses enterprise and IoT honeypots to attract attackers, learns from attacks via ML classifiers, and dynamically configures the rules of SDN. Our performance evaluation of S-Pot in detecting attacks using various ML classifiers shows that it can detect attacks with 97% accuracy using J48 algorithm. Third, for securing host-based Docker containers from cryptojacking, using honeypots, we perform a forensic analysis to identify indicators for the detection of unauthorized cryptomining, present measures for securing them, and propose an approach for monitoring host-based Docker containers for cryptojacking detection. Our results reveal that host temperature, combined with container resource usage, Stratum protocol, keywords in DNS requests, and the use of the container’s ephemeral ports are notable indicators of possible unauthorized cryptomining