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Survey on security and privacy issues in cyber physical systems

1 Faculty of Sciences and Technology, Nova University of Lisbon, Monte Caparica, Portugal
2 School of Computer Science and Technology, University of Bedfordshire, University Square,Luton, LU1 3JU, UK

Topical Section: Communications and Networks

The notion of Cyber-Physical Systems (CPS) is proposed by the National ScientificFoundation to describe a type of systems which combine hardware and software components andbeing the next step in development of embedded systems. CPS includes a wide range of researchtopics ranging from signal processing to data analysis. This paper contains a brief review of the basicinfrastructure for CPS including smart objects and network aspects in relation to TCP/IP stack. AsCPS reflect the processes of the physical environment onto the cyber space, virtualisation as animportant tool for abstraction plays crucial role in CPS. In this context paper presents the challengesassociated with mobility and vritualisation; accordingly three main types of virtualisation, namelynetwork, devices and applications virtualisation are presented in the paper. These aspects are tightlycoupled with security and safety issues. Therefore, different threats, attack types with correspondingsubtypes and possible consequences are discussed as well as analysis of various approaches to copewith existing threats is introduced. In addition threat modelling approaches were also in scope of thiswork. Furthermore, needs and requirements for safety-critical CPS are reviewed. Thus the mainefforts of this paper are directed on introducing various aspects of the CPS with regard to securityand safety issues.
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Keywords cyber physical systems ; security ; safety

Citation: Artem A. Nazarenko , Ghazanfar Ali Safdar. Survey on security and privacy issues in cyber physical systems. AIMS Electronics and Electrical Engineering, 2019, 3(2): 111-143. doi: 10.3934/ElectrEng.2019.2.111


  • 1. National Science Foundation (NSF): Cyber-Physical Systems, USA, 2015. Available from: http://www.nsf.gov/pubs/2015/nsf15541/nsf15541.pdf.
  • 2. Camarinha-Matos LM, Goes J, Gomes L, et al. (2013) Contributing to the Internet of Things, In: Doctoral Conference on Computing, Electrical and Industrial Systems, pp. 312. Springer, Berlin, Heidelberg.
  • 3. Hermann M, Pentek T, Otto B (2015) Design Principles for Industrie 4.0 Scenarios: A Literature Review. Working Paper, Technical University of Dortmund, Dortmund, Germany.
  • 4. Evans PC, Annunziata M (2012) Industrial Internet: Pushing the Boundaries of Minds and Machines. Available from: http://www.ge.com/docs/chapters/Industrial_Internet.pdf.
  • 5. Schmidt DC, White J, Gill CD (2014) Elastic Infrastructure to Support Computing Clouds for Large-scale Cyber-Physical Systems, In: 2014 IEEE 17th International Symposium on Object/Component/Service-Oriented Real-Time Distributed Computing, pp. 5663, IEEE.
  • 6. Koubaa A, Björn A (2009) A Vision of Cyber-Physical Internet, In: 8th International Workshop on Real Time Networks (RTN'09), pp. 16. Instituo Politécnico do Porto. Instituto Superior de Engenharia do Porto.
  • 7. Tan Y, Goddard S, Pérez LC (2008) A prototype architecture for cyber-physical systems. ACM SIGBED Review 5: 26.
  • 8. Sztipanovits J, Koutsoukos X, Karsai G, et al. (2012) Toward a science of cyberphysical system integration. Proceedings of the IEEE 100: 2944.
  • 9. Kocabas O, Soyata T, Aktas MK (2016) Emerging Security Mechanisms for Medical Cyber Physical Systems. IEEE/ACM Transactions on Computational Biology and Bioinformatics 13: 401416.
  • 10. Gunes V, Peter S, Givargis T, et al. (2014) A Survey on Concepts, Applications, and Challenges in Cyber-Physical Systems. KSII T Internet Inf 8: 42424268.
  • 11. Baheti R, Gill H (2011) Cyber-physical Systems. The Impact of Control Technology 12: 161166.
  • 12. Ding W, Engel W, Goode A, et al. (2016) Declarative Modeling Cases of Cyber Physical Systems. In: 2016 International Conference on Logistics, Informatics and Service Sciences (LISS), pp. 16. IEEE.
  • 13. Ahmad A, Paul A, Rathore MM, et al. (2016) Smart cyber society: Integration of capillary devices with high usability based on CyberPhysical System. Future Gener Comp Sy 56: 493503.
  • 14. Molina E, Jacob E (2017) Software-defined networking in cyber-physical systems: A survey. Comput Electr Eng 66: 407419.
  • 15. Ashibani Y, Mahmoud QH (2017) Cyber physical systems security: Analysis, challenges and solutions. Comput Secur 68: 8197.
  • 16. Heath S (2002) Embedded Systems Design. 2nd Edition, Newnes, Oxford, UK.
  • 17. Mascolo C, Hailes S, Lymberopoulos L, et al. (2005) Survey of middleware for networked embedded systems. Project report. Available from: http://erepo.usiu.ac.ke/bitstream/handle/11732/12/IST-RUNES_D5.1.pdf?sequence=1&isAllowed=y.
  • 18. Yick J, Mukherjee B, Ghosal D (2008) Wireless sensor network survey. Comput Netw 52: 22922330.
  • 19. Vasseur J-P, Dunkels A (2010) Interconnecting Smart Objects with IP: The Next Internet. Morgan Kaufmann.
  • 20. Akyildiz IF, Kasimoglu IH (2004) Wireless sensor and actor networks: research challenges. Ad Hoc Netw 2: 351367.
  • 21. Weiser M (1999) Some computer science issues in ubiquitous computing. ACM SIGMOBILEMobile Computing and Communications Review 3: 12.
  • 22. Friedewald M, Raabe O (2011) Ubiquitous computing: An overview of technology impacts. Telematics and Informatics, 28: 5565.
  • 23. Mayer S, Verborgh R, Kovatsch M, et al. (2016) Smart Configuration of Smart Environments. IEEE T Autom Sci Eng 13: 12471255.
  • 24. IERC-European Research Cluster on the Internet of Things, 2014. Available from: http://www.internet-of-things-research.eu/about_iot.htm.
  • 25. ITU-International Telecommunication Union, 2012. Recommendation Y.2069: Terms and definitions for the Internet of things. Available from: https://www.itu.int/rec/T-REC-Y.2069-201207-I/en.
  • 26. Weber RH and Studer E (2016) Cybersecurity in the Internet of Things: Legal aspects. Computer Law & Security Review 32: 715728.
  • 27. Chaouchi H (Ed.) (2013) The Internet of Things Connecting Objects to the Web. John Wiley & Sons.
  • 28. Li H, Dimitrovski A, Song JB, et al. (2014) Communication Infrastructure Design in Cyber Physical Systems with Applications in Smart Grids: A Hybrid System Framework. IEEE Communications Surveys & Tutorials 16: 16891708.
  • 29. Szczodrak M, Yang Y, Cavalcanti D, et al. (2013) An open framework to deploy heterogeneous wireless testbeds for Cyber- Physical Systems. In: 2013 8th IEEE International Symposium on Industrial Embedded Systems (SIES), pp. 215224.
  • 30. Lee J, Bagheri B, Kao HA (2015) A Cyber-Physical Systems architecture for Industry 4.0-based manufacturing systems. Manufacturing Letters 3: 1823.
  • 31. Hu L, Xie N, Kuang Z, et al. (2012) Review of Cyber-Physical System Architecture. In: 2012IEEE15th International Symposium on Object/Component/Service-Oriented Real-Time Distributed Computing Workshops, pp. 2530.
  • 32. Rixner S (2008) Network virtualization: Breaking the performance barrier. Queue 6: 37.
  • 33. Rauchfuss H, Wild T, Herkersdorf A (2010) A network interface card architecture for I/O virtualization in embedded systems. In: Proceedings of the 2nd conference on I/O virtualization, pp. 22. USENIX Association.
  • 34. Ganegedara T, Jiang W, Prasanna V (2011) Multiroot: Towards memory-efficient router virtualization. In: 2011IEEE International Conference on Communications (ICC), pp. 15.
  • 35. Egi N, Greenhalgh A, Handley M, et al. (2007) Evaluating Xen for Router Virtualization. In: 2007 16th International Conference on Computer Communications and Networks (ICCCN), pp. 12561261.
  • 36. Wen H, Tiwary PK, Le-Ngoc T (2013) Network Virtualization: Overview. In: Wireless Virtualization, pp. 510. Springer, Cham.
  • 37. Canonico R, Di Gennaro P, Vittorio M, et al. (2007) Virtualization Techniques in Network Emulation. In: European Conference on Parallel Processing, pp. 144153. Springer, Berlin, Heidelberg.
  • 38. Carapinha J, Jiménez J (2009) Network virtualization: a view from the bottom. In: Proceedings of the 1st ACM workshop on Virtualized infrastructure systems and architectures, pp. 7380. ACM.
  • 39. Martínez NL, Martínez JF, Díaz VH (2014) Virtualization of Event Sources in Wireless Sensor Networks for the Internet of Things. Sensors 14: 2273722753.
  • 40. Taherkordi A, Eliassen F (2014) Towards Independent in-Cloud Evolution of Cyber-Physical Systems. In: 2014 IEEE International Conference on Cyber-Physical Systems, Networks, and Applications, pp. 1924.
  • 41. Kuehnle H (2014) Smart Equipment and Virtual Resources trigger Network Principles in Manufacturing. In: IOP Conference Series: Material Science and Engineering, Vol. 58, p. 012002. IOP Publishing.
  • 42. Karnouskos S (2011) Cyber-physical systems in the smartgrid. In: 2011 9th IEEE International Conference on Industrial Informatics, pp. 2023. IEEE.
  • 43. Gokhale A, McDonald MP, Poff L (2010) Resource Provisioning and Dynamic Resource Management in Intelligent Transportation Systems. In: 11th International Conference on Mobile Data Management, Kansas City, USA.
  • 44. García-Valls M, Cucinotta T, Lu C (2014) Challenges in real-time virtualization and predictable cloud computing. J Syst Architect 60: 726-740.    
  • 45. Al-Fuqaha AI, Guizani M, Mohammadi M, et al. (2015) Internet of Things: A Survey on Enabling Technologies, Protocols, and Applications. IEEE Communications Surveys & Tutorials 17: 23472376.
  • 46. Pham Q, Malik T, Glavic B, et al. (2015) LDV: Light-weight database virtualization. In: 2015 IEEE 31st International Conference on Data Engineering (ICDE), pp. 11791190.c
  • 47. Verdouw CN, Beulens AJM, Reijers HA, et al. (2015) A control model for object virtualization in supply chain management. Comput Ind 68: 116131.
  • 48. Verdouw CN, Wolfert J, Beulens AJM, et al. (2016) Virtualization of food supply chains with the internet of things. J Food Eng 176: 128136.
  • 49. Liu N, Li X, Shen W (2014) Multi-granularity resource virtualization and sharing strategies in cloud manufacturing. J Netw Comput Appl 46: 7282.
  • 50. Kertesz A, Kecskemeti G, Brandic I (2014) An interoperable and self-adaptive approach for SLA-based service virtualization in heterogeneous Cloud environments. Future Gener Comp Sy 32: 5468.
  • 51. Márquez FG, Jimenez M, Ralli C, et al. (2015) Developing your first application using FI-WARE. Available from: http://cattelefonica.webs.upv.es/Fiware/developingyourfirstapplicationusingfiware.pdf.
  • 52. Gonizzi P, Ferrari G, Gay V, et al. (2015) Data dissemination scheme for distributed storage for IoT observation systems at large scale. Inform Fusion 22: 1625.
  • 53. Janak J, Schulzrinne H (2016) Framework for Rapid Prototyping of Distributed IoT Applications Powered by WebRTC, In: 2016Principles, Systems and Applications of IP Telecommunications (IPTComm), pp. 17. IEEE.
  • 54. Girau R, Martis S, Atzori L (2017) Lysis: A Platform for IoT Distributed Applications Over Socially Connected Objects. IEEE Internet Things 4: 4051.
  • 55. McMahan HB, Moore E, Ramage D, et al. (2017) Communication-Efficient Learning of Deep Networks from Decentralized Data. International Conference on Artificial Intelligence and Statistics, 12731282.
  • 56. Larsen RB, Carron A, Zeilinger MN (2017) Safe Learning for Distributed Systems with Bounded Uncertainties. IFAC-PapersOnLine 50: 25362542.
  • 57. Vincent H, Wells L, Tarazaga P, et al. (2015) Trojan Detection and Side-Channel Analyses for Cyber-Security in Cyber- Physical Manufacturing Systems. Procedia Manufacturing 1: 7785.
  • 58. Friedberg I, McLaughlin K, Smith P, et al. (2017) STPA-SafeSec: Safety and security analysis for cyber-physical systems. Journal of information security and applications 34: 183196.
  • 59. Govindarasu M, Hann A, Sauer P (2012) Cyber-Physical Systems Security for Smart Grid. Future Grid InitiativeWhite Paper, PSERC.
  • 60. Alcaraz C, Lopez J, Wolthusen SD (2016) Policy enforcement system for secure interoperable control in distributed Smart Grid systems. J Netw Comput Appl 59: 301314.
  • 61. Di Sarno C, Garofalo A, Matteucci I, et al. (2016) A novel security information and event management system for enhancing cyber security in a hydroelectric dam. Int J Crit Infr Prot 13: 3951.
  • 62. Lenzini G, Mauw S, Ouchani S (2015) Security analysis of socio-technical physical systems. Comput Electr Eng 47: 258274.
  • 63. Perkins C, Muller G (2015) Using Discrete Event Simulation to Model Attacker Interactions with Cyber and Physical Security Systems. Procedia Computer Science 61: 221226.
  • 64. Cherdantseva Y, Burnap P, Blyth A, et al. (2016) A review of cyber security risk assessment methods for SCADA system. Comput Secur 56: 127.
  • 65. Cardenas AA, Amin S, Sinopoli B, et al. (2009) Challenges for Securing Cyber Physical Systems. Workshop on future directions in cyber-physical systems security 5.
  • 66. Mo Y, Kim THJ, Brancik K, et al. (2011) CyberPhysical Security of a Smart Grid Infrastructure. P IEEE 100: 195209.
  • 67. Ozturk M, Aubin P (2011) SCADA Security: Challenges and Solutions. White Paper, Telemetry & Remote SCADA Solutions, Schneider Electric.
  • 68. Alcaraz C, Zeadally S (2013) Critical Control System Protection in the 21st Century. Computer 46: 7483.
  • 69. Creery A, Byres EJ (2005) Industrial cybersecurity for power system and SCADA networks. In: Record of Conference Papers Industry Applications Society52nd Annual Petroleum and Chemical Industry Conference, pp. 303309. IEEE.
  • 70. Humayed A, Lin J, Li F, et al. (2017) Cyber-Physical Systems Security-A Survey. IEEE Internet Things 4: 18021831.
  • 71. Papp D, Ma Z, Buttyan L (2015) Embedded Systems Security: Threats, Vulnerabilities, and Attack Taxonomy. In: 2015 13th Annual Conference on Privacy, Security and Trust (PST), pp. 145152.
  • 72. Nur AY, Tozal ME (2016) Defending Cyber-Physical Systems against DoS Attacks. In: 2016 IEEE International Conference on Smart Computing (SMARTCOMP), pp. 13. IEEE.
  • 73. Neumann PG (2006) Risks to the Public. ACM SIGSOFT Software Engineering Notes 30.
  • 74. Jokar P, Arianpoo N, Leung VCM (2013) Spoofing detection in IEEE 802.15.4 networks based on received signal strength. Ad Hoc Netw 11: 26482660.
  • 75. Su Z, Wassermann G (2006) The Essence of Command Injection Attacks in Web Applications. In: Acm Sigplan Notices 41: 372382.
  • 76. Shoukry Y, Martin P, Tabuada P, et al. (2013) Non-invasive Spoofing Attacks for Anti-lock Braking Systems. In: International Workshop on Cryptographic Hardware and Embedded Systems, pp. 5572. Springer, Berlin, Heidelberg.
  • 77. Chen Y, Kar S, Moura JMF (2016) Cyber Physical Attacks with Control Objectives. In: 2016 IEEE 55th Conference on Decision and Control (CDC), pp. 11251130. IEEE.
  • 78. Cazorla L, Alcaraz C, Lopez J (2018) Cyber Stealth Attacks in Critical Information Infrastructures. IEEE Syst J 12: 17781792.
  • 79. Wurm J, Jin Y, Liu Y, et al. (2017) Introduction to Cyber-Physical System Security: A Cross-Layer Perspective. IEEE Transactions on Multi-Scale Computing Systems 3: 215227.
  • 80. Puttonen J, Afolaranmi SO, Moctezuma LG (2015) Security in Cloud-based Cyber-physical Systems. In: 201510th International Conference on P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC), pp. 671676.
  • 81. Ntalampiras S (2016) Automatic identification of integrity attacks in cyber-physical systems. Expert Syst Appl 58: 164173.
  • 82. Altawy R, Youssef AM (2016) Security Tradeoffs in Cyber Physical Systems: A Case Study Survey on Implantable Medical Devices. IEEE Access 4: 959979.
  • 83. Konstantinou C, Maniatakos M, Saqib F, et al. (2015) Cyber-Physical Systems: A Security Perspective. In: 2015 20th IEEE European Test Symposium (ETS), pp. 18. IEEE.
  • 84. Teixeira A, Pérez D, Sandberg H (2012) Attack Models and Scenarios for Networked Control Systems. In: Proceedings of the 1st international conference on High Confidence Networked Systems, pp. 5564. ACM.
  • 85. Gollmann D, Gurikov P, Isakov A, et al. (2016) Cyber-Physical Systems Security Experimental Analysis of a Vinyl Acetate Monomer Plant. In: Proceedings of the1st ACM Workshop on Cyber-Physical System Security, pp. 112. ACM.
  • 86. DeSmit Z, Elhabashy AE, Wells LJ, et al. (2016) Cyber-Physical Vulnerability Assessment in Manufacturing Systems. Procedia Manufacturing 5: 10601074.
  • 87. Rahman MS, Mahmud MA, Oo AMT, et al. (2016) Multi-Agent Approach for Enhancing Security of Protection Schemes in Cyber-Physical Energy Systems. IEEE Transactions on Industrial Informatics 13: 436447.
  • 88. Steger M, Karner M, Hillebrand J, et al. (2016) A Security Metric for Structured Security Analysis of Cyber-Physical Systems Supporting SAE J3061. In: 2016 2nd International Workshop on Modelling, Analysis, and Control of Complex CPS (CPS Data), pp. 16.
  • 89. Burton J, Dubrawsky I, Osipov V, et al. (2003) Secure Intrusion Detection Systems. Syngress Publishing, Inc., Rockland, USA.
  • 90. Rehman RU (2003) Intrusion Detection Systems with Snort Advanced IDS Techniques Using Snort, Apache, MySQL, PHP, and ACID. Prentice Hall Professional.
  • 91. Mitchell R, Chen IR (2014) A Survey of Intrusion Detection Techniques for Cyber-Physical Systems. ACM Computing Surveys (CSUR) 46: 55.
  • 92. Scarfone K, Mell P (2007) Guide to Intrusion Detection and Prevention Systems (IDPS): Recommendations of the National Institute of Standards and Technology. NIST No. Special Publication (NIST SP)-800-94.
  • 93. Alcaraz C, Cazorla L, Fernandez G (2014) Context-Awareness Using Anomaly-Based Detectors for Smart Grid Domains. In: International Conference on Risks and Security of Internet and Systems, pp. 1734. Springer, Cham.
  • 94. Abbas W, Laszka A, Vorobeychik Y, et al. (2015) Scheduling Intrusion Detection Systems in Resource-Bounded Cyber- Physical Systems. In: Proceedings of the 1st ACM Workshop on Cyber-Physical Systems-Security and/or Privacy, pp. 5566. ACM.
  • 95. Naghnaeian M, Hirzallah N, Voulgaris PG (2015) Dual Rate Control for Security in Cyber-physical Systems. In: 2015 54th IEEE Conference on Decision and Control (CDC), pp. 141451420.
  • 96. Ivanov R, Pajic M, Lee I (2016) Attack-Resilient Sensor Fusion for Safety-Critical Cyber-Physical Systems. ACM Transactions on Embedded Computing Systems (TECS) 15: 21.
  • 97. Zimmer C, Bhat B, Mueller F, et al. (2010) Time-Based Intrusion Detection in Cyber-Physical Systems. In: Proceedings of the1st ACM/IEEE International Conference on Cyber-Physical Systems, pp. 109118. ACM.
  • 98. Joseph AD, Laskov P, Roli F, et al. (2013) Machine Learning Methods for Computer Security (Dagstuhl Perspectives Workshop 12371), In: Dagstuhl Manifestos, Vol. 3. Schloss Dagstuhl-Leibniz-Zentrum fuer Informatik.
  • 99. Nguyen TTT, Armitage GJ (2008) A survey of techniques for internet traffic classification using machine learning. IEEE Commun Surv Tut 10: 5676.
  • 100. Paridari K, Mady AE-D, La Porta S, et al. (2016) Cyber-Physical-Security Framework for Building Energy Management System. In: 2016 ACM/IEEE 7th International Conference on Cyber-Physical Systems (ICCPS), p. 18. IEEE.
  • 101. Udd R, Asplund M, Nadjm-Tehrani S, et al. (2016) Exploiting Bro for Intrusion Detection in a SCADA System. In: Proceedings of the2nd ACM International Workshop on Cyber-Physical System Security, pp. 4451.
  • 102. Chinchore A, Xu G, Jiang F (2016) Classifying Sybil in MSNs using C4.5. In: 2016International Conference on Behavioral, Economic and Socio-cultural Computing (BESC), pp. 16.
  • 103. Palenzuela F, Shaffer M, Ennis M, et al. (2016) Multilayer Perceptron Algorithms for Cyberattack Detection. In: 2016IEEE National Aerospace and Electronics Conference (NAECON) and Ohio Innovation Summit (OIS), pp. 248252.
  • 104. Livadas C, Walsh R, Lapsley DE (2006) Using Machine Learning Techniques to Identify Botnet Traffic. In: LCN, pp. 967974.
  • 105. DeLoach J, Caragea D, Ou X (2016) Android Malware Detection with Weak Ground Truth Data. In: 2016IEEE International Conference on Big Data (Big Data), pp. 34573464.
  • 106. Yerima SY, Sezer S, Muttik I (2015) High accuracy android malware detection using ensemble learning. IET Information Security 9: 313320.
  • 107. Song C, Perez-Pons A, Yen KK (2016) Building a Platform for Software-Defined Networking Cybersecurity Applications. In: 2016 15th IEEE International Conference on Machine Learning and Applications, pp. 482487.
  • 108. Jianguo J, Qi B, Zhixin S, et al. (2016) Botnet Detection Method Analysis on the Effect of Feature Extraction. In: 2016IEEE Trustcom/BigDataSE/ISPA, pp. 18821888.
  • 109. Cohena A, Nissima N, Rokacha L, et al (2016) SFEM: Structural feature extraction methodology for the detection of malicious office documents using machine learning methods. Expert Syst Appl 63: 324343.
  • 110. Goh KL, Singh AK (2015) Comprehensive Literature Review on Machine Learning Structures for Web Spam Classification. Procedia Computer Science 70: 434441.
  • 111. Buczak AL, Guven E (2016) A Survey of Data Mining and Machine Learning Methods for Cyber Security Intrusion Detection. IEEE Commun Surv Tut 18: 11531176.
  • 112. Huda S, Miah S, Hassan MM, et al. (2017) Defending unknown attacks on cyber-physical systems by semi-supervised approach and available unlabeled data. Inform Sciences 379: 211228.
  • 113. Seiger R, Keller C, Niebling F, et al. (2015) Modelling complex and flexible processes for smart cyber-physical environments. Journal of Computational Science 10: 137148.
  • 114. Kroiß C, Bureš T (2016) Logic-based modeling of information transfer in cyberphysical multi-agent systems. Future Gener Comp Sy 56: 124139.
  • 115. Khaitan SK, McCalley JD (2015) Design Techniques and Applications of Cyberphysical Systems: A Survey. IEEE SYST J 9: 350365.
  • 116. Petnga L, Austin M (2016) An ontological framework for knowledge modeling and decision support in cyber-physical systems. Adv Eng Inform 30: 7794.
  • 117. Kelly RA, Jakeman AJ, Barreteau O, et al. (2013) Selecting among five common modelling approaches for integrated environmental assessment and management. Environ Modell Softw 47: 159181.
  • 118. Strasser U, Vilsmaier U, Prettenhaler F, et al. (2014) Coupled component modelling for inter- and transdisciplinary climate change impact research: Dimensions of integration and examples of interface design. Environ Modell Softw 60: 180187.
  • 119. Burmester M, Magkos E, Chrissikopoulos V (2012) Modeling security in cyberphysical systems. Int J Crit Infr Prot 5: 118126.
  • 120. Marrone S, Rodríguez RJ, Nardone R, et al. (2015) On synergies of cyber and physical security modelling in vulnerability assessment of railway systems. Comput Electr Eng 47: 275285.
  • 121. Akella R, Tang H, McMillin BM (2010) Analysis of information flow security in cyberphysical systems. Int J Cri Infr Prot 3: 157173.
  • 122. Wan J, Canedo A, Al Faruque MA (2015) Security-Aware Functional Modeling of Cyber-Physical Systems. In: 2015 IEEE 20th Conference on Emerging Technologies & Factory Automation (ETFA), pp. 14. IEEE.
  • 123. Amullen EM, Shetty S, Keel LH (2016) Model-based resilient control for a multi-agent system against Denial of Service attacks. In: 2016 World Automation Congress (WAC), pp. 16.
  • 124. Tsigkanos C, Pasquale L, Ghezzi C, et al. (2015) Ariadne: Topology Aware Adaptive Security for Cyber-Physical Systems. In: Proceedings of the 37th IEEE International Conference on Software Engineering, pp. 729732. IEEE Press.
  • 125. Kriaa S, Pietre-Cambacedes L, Bouissou M, et al. (2015) A survey of approaches combining safety and security for industrial control systems. Reliab Eng Syst Safe 139: 156178.
  • 126. Kornecki AJ, Subramanian N, Zalewski J (2013) Studying Interrelationships of Safety and Security for Software Assurance in Cyber-Physical Systems: Approach Based on Bayesian Belief Networks. In: 2013 Federated Conference on Computer Science and Information Systems, pp. 13931399.
  • 127. Bak S, Abad FAT, Huang Z, et al. (2013) Using Run-Time Checking to Provide Safety and Progress for Distributed Cyber-Physical Systems. In: 2013IEEE 19th International Conference on Embedded and Real-Time Computing Systems and Applications, pp. 287296.
  • 128. Kuschnerus D, Bilgic A, Bruns F, et al. (2015) A Hierarchical Domain Model for Safety-Critical Cyber-Physical Systems in Process Automation. In: 2015 IEEE 13th International Conference on Industrial Informatics (INDIN), pp. 430436.
  • 129. Knight JC (2002) Safety critical systems: challenges and directions. In: Proceedings of the24th International Conference on Software Engineering, pp. 547550.
  • 130. Neuman C (2009) Challenges in Security for Cyber-Physical Systems. In: DHS Workshop on Future Directions in Cyber- Physical Systems Security, pp. 2224.
  • 131. Sun H, Liu J, Chen X, et al. (2015) Specifying Cyber-Physical System Safety Properties with Metric Temporal-Spatial Logic. In: 2015 Asia-PacificSoftware Engineering Conference (APSEC), pp. 254260.
  • 132. Baldoni R, Montanari L, Rizzuto M (2015) On-line failure prediction in safety-critical systems. Future Gener Comp Sy 45: 123132.
  • 133. Masrur A, Kit M, Matena V, et al. (2016) Component-based design of cyber-physical applications with safety-critical requirements. Microprocess Microsy 42: 7086.
  • 134. Nguyen HH, Tan R, Yau DKY (2014) Safety-Assured Collaborative Load Management in Smart Grids. In: 2014 ACM/IEEE International Conference on Cyber-Physical Systems (ICCPS), pp. 151162.
  • 135. Weissnegger R, Schuss M, Kreiner C, et al. (2016) Simulation-based Verification of Automotive Safety-CriticalSystems based on EAST-ADL. Procedia computer science 8: 245252.
  • 136. Ishigooka T, Saissi H, Piper T, et al. (2014) Practical Use of Formal Verification for Safety Critical Cyber-Physical Systems: A Case Study. In: 2014 IEEE International Conference on Cyber-Physical Systems, Networks, and Applications, pp. 712.
  • 137. Piesik E, Śliwiński M, Barnert T (2016) Determining and verifying the safety integrity level of the safety instrumented systems with the uncertainty and security aspects. Reliab Eng Syst Safe 152: 259272.
  • 138. Zheng X, Julien C, Kim M, et al. (2015) Perceptions on the State of the Art in Verification and Validation in Cyber- Physical Systems. IEEE Syst J 11: 26142627.
  • 139. Fallah YP, Huang CL, Sengupta R, et al. (2010) Design of Cooperative Vehicle Safety Systems Based on Tight Coupling of Communication, Computing and Physical Vehicle Dynamics. In: Proceedings of the 1st ACM/IEEE International Conference on Cyber-Physical Systems, pp. 159167.
  • 140. Schmittner C, Ma Z, Schoitsch E, et al. (2015) A Case Study of FMVEA and CHASSIS as Safety and Security Co- Analysis Method for Automotive Cyber-physical Systems. In: Proceedings of the 1st ACM Workshop on Cyber-Physical System Security, pp. 6980.
  • 141. Adhikari U, Morris TH, Pan S (2014) A Causal Event Graph for Cyber-Power System Events Using Synchrophasor. In: 2014 IEEE PES General Meeting|Conference & Exposition, pp. 15. IEEE.
  • 142. Al-Hammadi Y, Aickelin U (2010) Behavioural Correlation for Detecting P2P Bots. In: 2010 2nd International Conference on Future Networks (ICFN), pp. 323327.
  • 143. Petrovski A, Rattadilok P, Petrovski S (2015) Designing a Context-Aware Cyber Physical System for Detecting Security Threats in Motor Vehicles. In: Proceedings of the 8th International Conference on Security of Information and Networks, pp. 267270.
  • 144. Skormin V, Dolgikh A, Birnbaum Z (2014) The Behavioral Approach to Diagnostics of Cyber-Physical Systems. In: 2014 IEEE AUTOTEST, pp. 2630. IEEE.
  • 145. Wang A, Iyer M, Dutta R, et al. (2013) Network Virtualization: Technologies, Perspectives, and Frontiers. J Lightwave Technol 31: 523537.
  • 146. Wardell DC, Mills RF, Peterson GL, et al. (2016) A Method for Revealing and Addressing Security Vulnerabilities in Cyber-Physical Systems by Modeling Malicious Agent Interactions with Formal Verification. Procedia Computer Science 95: 2431.
  • 147. McAfee Special report: How Collaboration Can Optimize Security Operations. The new secret weapon against advanced threats, 2016. Available from: https://abyteofcyber.com/DOCS/rp-soc-collaboration-advanced-threats.pdf.
  • 148. Mrabet ZE, Kaabouch N, Ghazi HE, et al. (2018) Cyber-security in smart grid: Survey and challenges. Comput Electr Eng 67: 469482.
  • 149. Leeds M, Atkison T (2016) Preliminary Results of Applying Machine Learning Algorithms to Android Malware Detection. In: 2016International Conference on Computational Science and Computational Intelligence, pp. 10701073.
  • 150. Suh-Lee C, Jo J-Y, Kim Y (2016) Text Mining for Security Threat Detection Discovering Hidden Information in Unstructured Log Messages. In: 2016 IEEE Conference on Communications and Network Security (CNS), pp. 252260.
  • 151. Morales-Ortega S, Escamilla-Ambrosio PJ, Rodríguez-Mota A, et al. (2016) Native Malware Detection in Smartphones with Android OS Using Static Analysis, Feature Selection and Ensemble Classifiers. In: 2016 11th International Conference on Malicious and Unwanted Software (MALWARE), pp. 18.
  • 152. Hu W, Liao Y, Vemuri VR (2003) Robust Anomaly Detection Using Support Vector Machines. In: Proceedings of the International Conference on Machine Learning, pp. 282289.
  • 153. Gouveia A, Correia M (2016) Feature Set Tuning in Statistical Learning Network Intrusion Detection. In: 2016 IEEE 15th International Symposium on Network Computing and Applications, pp. 6875.
  • 154. Kamarudin MH, Maple C, Watson T, et al. (2015) Packet Header Intrusion Detection with Binary Logistic Regression Approach in Detecting R2L and U2R attacks. In: 20154th International Conference on Cyber Security, Cyber Warfare, and Digital Forensic, pp. 101106.
  • 155. Alshammari R, Zincir-Heywood AN (2015) Identification of VoIP encrypted traffic using a machine learning approach. Journal of King Saud University Computer and Information Sciences 27: 7792.
  • 156. Li Y, Guo L (2007) An Efficient Network Anomaly Detection Scheme Based on TCM-KNN Algorithm and Data Reduction Mechanism. In: 2007IEEE SMC Information Assurance and Security Workshop, pp. 221227.
  • 157. Wang W, Lee XD, Hu AL, et al. (2013) Co-Training based Semi-Supervised Web Spam Detection. In: 2013 10th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), pp. 789793.
  • 158. Baig M, El-Alfy E-SM, Awais MM (2014) Intrusion Detection Using a Cascade of Boosted Classifiers (CBC), In: 2014 International Joint Conference on Neural Networks, pp. 13861392.
  • 159. Farid DM, Harbi N, Rahman MZ (2010) Combining Naïve Bayes and Decision Tree for Adaptive Intrusion Detection. International Journal of Network Security & Its Applications (IJNSA) 2: 1225.
  • 160. Stein G, Chen B, Wu AS, et al. (2005) Decision Tree Classifier For Network Intrusion Detection With GA-based Feature Selection. In: Proceedings of the 43rd annual Southeast regional conference, pp. 136141.
  • 161. Kumar PAR, Selvakumar S (2013) Detection of distributed denial of service attacks using an ensemble of adaptive and hybrid neuro-fuzzy systems. Comput Commun 36: 303319.
  • 162. Hu W, Hu W, Maybank SJ (2008) AdaBoost-Based Algorithm for Network Intrusion Detection. Systems Man and Cybernatics 38: 577583.
  • 163. Laskov P, Schäfer C, Kotenko I, et al. (2004) Intrusion Detection in Unlabeled Data with Quarter-sphere Support Vector Machines. Praxis der Informationsverarbeitung und Kommunikation 27: 228236.
  • 164. Zhang J, Luo X, Perdisci R, et al. (2011) Boosting the Scalability of Botnet Detection Using Adaptive Traffic Sampling. In: Proceedings of the 6th ACM Symposium on Information, Computer and Communications Security, pp. 124134.
  • 165. Syarif I, Zaluska E, Prugel-Bennett A, et al. (2012) Application of Bagging, Boosting and Stacking to Intrusion Detection. In: MLDM'12 Proceedings of the8th international conference on Machine Learning and Data Mining in Pattern Recognition, pp. 593602.


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