2021
I. Siniosoglou; V. Argyriou; S. Bibi; T. Lagkas; P. Sarigiannidis
Unsupervised Ethical Equity Evaluation of Adversarial Federated Networks Conference
The 16th International Conference on Availability, Reliability and Security, 2021.
Abstract | BibTeX | Tags: adverserial federated networks, machine learning, security | Links:
@conference{Siniosoglou2021c,
title = {Unsupervised Ethical Equity Evaluation of Adversarial Federated Networks},
author = {I. Siniosoglou and V. Argyriou and S. Bibi and T. Lagkas and P. Sarigiannidis},
url = {https://www.researchgate.net/publication/353936098_Unsupervised_Ethical_Equity_Evaluation_of_Adversarial_Federated_Networks},
doi = {10.1145/3465481.3470478},
year = {2021},
date = {2021-08-17},
booktitle = {The 16th International Conference on Availability, Reliability and Security},
pages = {1-6},
abstract = {While the technology of Deep Learning (DL) is a powerful tool when properly trained for image analysis and classification applications, some factors for its optimization rely solely on the training data and their environment. In an effort to tackle the problem of knowledge bias created during the training process of a Deep Neural Network (DNN) and specifically Adversarial Networks for image augmentation, this work presents an entirely unsupervised methodology for discovering the unfairness level of Deep Learning (DL) models and in extend, its wrongly accumulated or biased classes. Fdi, the proposed evaluation metric for quantizing the level of unfairness of a model is introduced, along with the method of weighting the model’s knowledge and producing its weakest aspects in a data-agnostic way.},
keywords = {adverserial federated networks, machine learning, security},
pubstate = {published},
tppubtype = {conference}
}
While the technology of Deep Learning (DL) is a powerful tool when properly trained for image analysis and classification applications, some factors for its optimization rely solely on the training data and their environment. In an effort to tackle the problem of knowledge bias created during the training process of a Deep Neural Network (DNN) and specifically Adversarial Networks for image augmentation, this work presents an entirely unsupervised methodology for discovering the unfairness level of Deep Learning (DL) models and in extend, its wrongly accumulated or biased classes. Fdi, the proposed evaluation metric for quantizing the level of unfairness of a model is introduced, along with the method of weighting the model’s knowledge and producing its weakest aspects in a data-agnostic way.
D. Pliatsios; P. Sarigiannidis; G. Fragulis; A. Tsiakalos; D. Margounakis
A Dynamic Recommendation-based Trust Scheme for the Smart Grid Conference
3rd International Workshop on Cyber-Security Threats, Trust and Privacy management in Software-defined and Virtualized Infrastructures (SecSoft 2021), 2021.
Abstract | BibTeX | Tags: cyberattacks, security, Smart Grid, smart meters, trust management | Links:
@conference{Pliatsios2021,
title = {A Dynamic Recommendation-based Trust Scheme for the Smart Grid},
author = {D. Pliatsios and P. Sarigiannidis and G. Fragulis and A. Tsiakalos and D. Margounakis},
url = {https://www.researchgate.net/publication/353484865_A_Dynamic_Recommendation-based_Trust_Scheme_for_the_Smart_Grid},
doi = {10.1109/NetSoft51509.2021.9492542 +Date: 26 July 2021},
year = {2021},
date = {2021-07-26},
booktitle = {3rd International Workshop on Cyber-Security Threats, Trust and Privacy management in Software-defined and Virtualized Infrastructures (SecSoft 2021)},
abstract = {The integration of the internet of things (IoT) concept into the traditional electricity grid introduces several critical vulnerabilities. Intrusion detection systems (IDSs) can be effective countermeasures against cyberattacks, however, they require considerable computational and storage resources. As IoT-enabled metering devices have limited resources, IDSs cannot efficiently ensure security. To this end, trust evaluation schemes have emerged as promising solutions toward protecting resource-constrained metering devices. In this work, we proposed a trust evaluation scheme for the smart grid, that is based on direct trust evaluation and recommendation. The proposed hierarchical scheme is able to evaluate the trustiness of each metering device without requiring any significant modifications to the already deployed infrastructure. Additionally, the proposed scheme features is dynamic, meaning that it is robust against nonadversarial events that negatively impact the device’s trustiness. To validate the performance of the proposed scheme, we carry out network-level simulations and investigate how the various network parameters impact the trust evaluation performance.},
keywords = {cyberattacks, security, Smart Grid, smart meters, trust management},
pubstate = {published},
tppubtype = {conference}
}
The integration of the internet of things (IoT) concept into the traditional electricity grid introduces several critical vulnerabilities. Intrusion detection systems (IDSs) can be effective countermeasures against cyberattacks, however, they require considerable computational and storage resources. As IoT-enabled metering devices have limited resources, IDSs cannot efficiently ensure security. To this end, trust evaluation schemes have emerged as promising solutions toward protecting resource-constrained metering devices. In this work, we proposed a trust evaluation scheme for the smart grid, that is based on direct trust evaluation and recommendation. The proposed hierarchical scheme is able to evaluate the trustiness of each metering device without requiring any significant modifications to the already deployed infrastructure. Additionally, the proposed scheme features is dynamic, meaning that it is robust against nonadversarial events that negatively impact the device’s trustiness. To validate the performance of the proposed scheme, we carry out network-level simulations and investigate how the various network parameters impact the trust evaluation performance.
2020
D. Pliatsios; P. Sarigiannidis; T. Lagkas; A.G. Sarigiannidis
A Survey on SCADA Systems: Secure Protocols, Incidents, Threats and Tactics Journal Article
In: IEEE Communications Surveys and Tutorials, vol. 22, no. 3, pp. 1942-1976, 2020.
Abstract | BibTeX | Tags: Cybersecurity, protocols, SCADA, security, Smart Grid, trends | Links:
@article{Pliatsios20201942,
title = {A Survey on SCADA Systems: Secure Protocols, Incidents, Threats and Tactics},
author = { D. Pliatsios and P. Sarigiannidis and T. Lagkas and A.G. Sarigiannidis},
url = {https://www.researchgate.net/publication/340453361_A_Survey_on_SCADA_Systems_Secure_Protocols_Incidents_Threats_and_Tactics},
doi = {10.1109/COMST.2020.2987688},
year = {2020},
date = {2020-01-01},
journal = {IEEE Communications Surveys and Tutorials},
volume = {22},
number = {3},
pages = {1942-1976},
abstract = {Supervisory Control and Data Acquisition (SCADA) systems are the underlying monitoring and control components of critical infrastructures, such as power, telecommunication, transportation, pipelines, chemicals and manufacturing plants. Legacy SCADA systems operated on isolated networks, that made them less exposed to Internet threats. However, the increasing connection of SCADA systems to the Internet, as well as corporate networks, introduces severe security issues. Security considerations for SCADA systems are gaining higher attention, as the number of security incidents against these critical infrastructures is increasing. In this survey, we provide an overview of the general SCADA architecture, along with a detailed description of the SCADA communication protocols. Additionally, we discuss certain high-impact security incidents, objectives, and threats. Furthermore, we carry out an extensive review of the security proposals and tactics that aim to secure SCADA systems. We also discuss the state of SCADA system security. Finally, we present the current research trends and future advancements of SCADA security. © 1998-2012 IEEE.},
keywords = {Cybersecurity, protocols, SCADA, security, Smart Grid, trends},
pubstate = {published},
tppubtype = {article}
}
Supervisory Control and Data Acquisition (SCADA) systems are the underlying monitoring and control components of critical infrastructures, such as power, telecommunication, transportation, pipelines, chemicals and manufacturing plants. Legacy SCADA systems operated on isolated networks, that made them less exposed to Internet threats. However, the increasing connection of SCADA systems to the Internet, as well as corporate networks, introduces severe security issues. Security considerations for SCADA systems are gaining higher attention, as the number of security incidents against these critical infrastructures is increasing. In this survey, we provide an overview of the general SCADA architecture, along with a detailed description of the SCADA communication protocols. Additionally, we discuss certain high-impact security incidents, objectives, and threats. Furthermore, we carry out an extensive review of the security proposals and tactics that aim to secure SCADA systems. We also discuss the state of SCADA system security. Finally, we present the current research trends and future advancements of SCADA security. © 1998-2012 IEEE.
2019
P.I. Radoglou-Grammatikis; P.G. Sarigiannidis
Securing the Smart Grid: A Comprehensive Compilation of Intrusion Detection and Prevention Systems Journal Article
In: IEEE Access, vol. 7, pp. 46595-46620, 2019.
Abstract | BibTeX | Tags: Advanced Metering Infrastructure, cyberattacks, intrusion detection system, Intrusion prevention system, SCADA, security, Smart Grid, substation, Synchrophasor | Links:
@article{Radoglou-Grammatikis201946595,
title = {Securing the Smart Grid: A Comprehensive Compilation of Intrusion Detection and Prevention Systems},
author = { P.I. Radoglou-Grammatikis and P.G. Sarigiannidis},
url = {https://www.researchgate.net/publication/332188706_Securing_the_Smart_Grid_A_Comprehensive_Compilation_of_Intrusion_Detection_and_Prevention_Systems},
doi = {10.1109/ACCESS.2019.2909807},
year = {2019},
date = {2019-01-01},
journal = {IEEE Access},
volume = {7},
pages = {46595-46620},
abstract = {The smart grid (SG) paradigm is the next technological leap of the conventional electrical grid, contributing to the protection of the physical environment and providing multiple advantages such as increased reliability, better service quality, and the efficient utilization of the existing infrastructure and the renewable energy resources. However, despite the fact that it brings beneficial environmental, economic, and social changes, the existence of such a system possesses important security and privacy challenges, since it includes a combination of heterogeneous, co-existing smart, and legacy technologies. Based on the rapid evolution of the cyber-physical systems (CPS), both academia and industry have developed appropriate measures for enhancing the security surface of the SG paradigm using, for example, integrating efficient, lightweight encryption and authorization mechanisms. Nevertheless, these mechanisms may not prevent various security threats, such as denial of service (DoS) attacks that target on the availability of the underlying systems. An efficient countermeasure against several cyberattacks is the intrusion detection and prevention system (IDPS). In this paper, we examine the contribution of the IDPSs in the SG paradigm, providing an analysis of 37 cases. More detailed, these systems can be considered as a secondary defense mechanism, which enhances the cryptographic processes, by timely detecting or/and preventing potential security violations. For instance, if a cyberattack bypasses the essential encryption and authorization mechanisms, then the IDPS systems can act as a secondary protection service, informing the system operator for the presence of the specific attack or enabling appropriate preventive countermeasures. The cases we study focused on the advanced metering infrastructure (AMI), supervisory control and data acquisition (SCADA) systems, substations, and synchrophasors. Based on our comparative analysis, the limitations and the shortcomings of the current IDPS systems are identified, whereas appropriate recommendations are provided for future research efforts. © 2013 IEEE.},
keywords = {Advanced Metering Infrastructure, cyberattacks, intrusion detection system, Intrusion prevention system, SCADA, security, Smart Grid, substation, Synchrophasor},
pubstate = {published},
tppubtype = {article}
}
The smart grid (SG) paradigm is the next technological leap of the conventional electrical grid, contributing to the protection of the physical environment and providing multiple advantages such as increased reliability, better service quality, and the efficient utilization of the existing infrastructure and the renewable energy resources. However, despite the fact that it brings beneficial environmental, economic, and social changes, the existence of such a system possesses important security and privacy challenges, since it includes a combination of heterogeneous, co-existing smart, and legacy technologies. Based on the rapid evolution of the cyber-physical systems (CPS), both academia and industry have developed appropriate measures for enhancing the security surface of the SG paradigm using, for example, integrating efficient, lightweight encryption and authorization mechanisms. Nevertheless, these mechanisms may not prevent various security threats, such as denial of service (DoS) attacks that target on the availability of the underlying systems. An efficient countermeasure against several cyberattacks is the intrusion detection and prevention system (IDPS). In this paper, we examine the contribution of the IDPSs in the SG paradigm, providing an analysis of 37 cases. More detailed, these systems can be considered as a secondary defense mechanism, which enhances the cryptographic processes, by timely detecting or/and preventing potential security violations. For instance, if a cyberattack bypasses the essential encryption and authorization mechanisms, then the IDPS systems can act as a secondary protection service, informing the system operator for the presence of the specific attack or enabling appropriate preventive countermeasures. The cases we study focused on the advanced metering infrastructure (AMI), supervisory control and data acquisition (SCADA) systems, substations, and synchrophasors. Based on our comparative analysis, the limitations and the shortcomings of the current IDPS systems are identified, whereas appropriate recommendations are provided for future research efforts. © 2013 IEEE.
2018
P. I. Radoglou-Grammatikis; P. G. Sarigiannidis
An Anomaly-Based Intrusion Detection System for the Smart Grid Based on CART Decision Tree Conference
2018 Global Information Infrastructure and Networking Symposium (GIIS), IEEE, 2018.
Abstract | BibTeX | Tags: Advanced Metering Infrastructure, intrusion detection system, security, Smart Grid | Links:
@conference{Radoglou-Grammatikis2019b,
title = {An Anomaly-Based Intrusion Detection System for the Smart Grid Based on CART Decision Tree},
author = { P. I. Radoglou-Grammatikis and P. G. Sarigiannidis},
url = {An Anomaly-Based Intrusion Detection System for the Smart Grid Based on CART Decision Tree},
doi = {10.1109/GIIS.2018.8635743},
year = {2018},
date = {2018-10-01},
booktitle = {2018 Global Information Infrastructure and Networking Symposium (GIIS)},
journal = {2018 Global Information Infrastructure and Networking Symposium, GIIS 2018},
publisher = {IEEE},
abstract = {The Smart Grid (SG) paradigm constitutes the new technological evolution of the traditional electrical grid, providing remote monitoring and controlling capabilities among all its operations through computing services. These new capabilities offer a lot of benefits, such as better energy management, increased reliability and security, as well as more economical pricing. However, despite these advantages, it introduces significant security challenges, as the computing systems and the corresponding communications are characterized by several cybersecurity threats. An efficient solution against cyberattacks is the Intrusion Detection Systems (IDS). These systems usually operate as a second line of defence and have the ability to detect or even prevent cyberattacks in near real-Time. In this paper, we present a new IDS for the Advanced Metering Infrastructure (AMI) utilizing machine learning capabilities based on a decision tree. Decision trees have been used for multiple classification problems like the distinguishment between the normal and malicious activities. The experimental evaluation demonstrates the efficiency of the proposed IDS, as the Accuracy and the True Positive Rate of our IDS reach 0.996 and 0.993 respectively. © 2018 IEEE.},
keywords = {Advanced Metering Infrastructure, intrusion detection system, security, Smart Grid},
pubstate = {published},
tppubtype = {conference}
}
The Smart Grid (SG) paradigm constitutes the new technological evolution of the traditional electrical grid, providing remote monitoring and controlling capabilities among all its operations through computing services. These new capabilities offer a lot of benefits, such as better energy management, increased reliability and security, as well as more economical pricing. However, despite these advantages, it introduces significant security challenges, as the computing systems and the corresponding communications are characterized by several cybersecurity threats. An efficient solution against cyberattacks is the Intrusion Detection Systems (IDS). These systems usually operate as a second line of defence and have the ability to detect or even prevent cyberattacks in near real-Time. In this paper, we present a new IDS for the Advanced Metering Infrastructure (AMI) utilizing machine learning capabilities based on a decision tree. Decision trees have been used for multiple classification problems like the distinguishment between the normal and malicious activities. The experimental evaluation demonstrates the efficiency of the proposed IDS, as the Accuracy and the True Positive Rate of our IDS reach 0.996 and 0.993 respectively. © 2018 IEEE.
P. Radoglou-Grammatikis; P. Sarigiannidis; T. Liatifis; T. Apostolakos; S. Oikonomou
An Overview of the Firewall Systems in the Smart Grid Paradigm Conference
2018 Global Information Infrastructure and Networking Symposium (GIIS), IEEE, 2018.
Abstract | BibTeX | Tags: Advanced Metering Infrastructure, cyberattacks, firewall, SCADA, security, Smart Grid, substation | Links:
@conference{Radoglou-Grammatikis2019c,
title = {An Overview of the Firewall Systems in the Smart Grid Paradigm},
author = { P. Radoglou-Grammatikis and P. Sarigiannidis and T. Liatifis and T. Apostolakos and S. Oikonomou},
url = {https://www.researchgate.net/publication/328998034_An_Overview_of_the_Firewall_Systems_in_the_Smart_Grid_Paradigm?_sg=CEd52g3u0I4mXf4THuYQzeTDbKNpbsG1qpl5tTT-9PASC4E8XbQbzl9YIlg_icl-irrtxOICHyYWGaQ},
doi = {10.1109/giis.2018.8635747},
year = {2018},
date = {2018-10-01},
booktitle = {2018 Global Information Infrastructure and Networking Symposium (GIIS)},
journal = {2018 Global Information Infrastructure and Networking Symposium, GIIS 2018},
publisher = {IEEE},
abstract = {The multiple interconnections and the heterogeneity of the devices and technologies into the Smart Grid (SG) generate possible cyber-physical security vulnerabilities that can be exploited by various cyberattackers. The cyberattacks in SG, usually target the availability and the information integrity of the systems. Replay attacks, Denial of Service (DoS), Distributed DoS (DDoS) and botnets are typical examples. Furthermore, the hacking tools have been largely automated, so even a novice can execute destructive cyberattacks. These situations make it necessary to develop efficient firewall systems that can prevent possible cyberattacks. In this paper, we present an overview of the various firewall systems in the SG paradigm and also we provide new research directions in this field. © 2018 IEEE.},
keywords = {Advanced Metering Infrastructure, cyberattacks, firewall, SCADA, security, Smart Grid, substation},
pubstate = {published},
tppubtype = {conference}
}
The multiple interconnections and the heterogeneity of the devices and technologies into the Smart Grid (SG) generate possible cyber-physical security vulnerabilities that can be exploited by various cyberattackers. The cyberattacks in SG, usually target the availability and the information integrity of the systems. Replay attacks, Denial of Service (DoS), Distributed DoS (DDoS) and botnets are typical examples. Furthermore, the hacking tools have been largely automated, so even a novice can execute destructive cyberattacks. These situations make it necessary to develop efficient firewall systems that can prevent possible cyberattacks. In this paper, we present an overview of the various firewall systems in the SG paradigm and also we provide new research directions in this field. © 2018 IEEE.
T. Lagkas; V. Argyriou; S. Bibi; P. Sarigiannidis
UAV IoT framework views and challenges: Towards protecting drones as “things” Journal Article
In: Sensors (Switzerland), vol. 18, no. 11, 2018.
Abstract | BibTeX | Tags: Drones, IoT, Privacy, security, UAV | Links:
@article{Lagkas2018b,
title = {UAV IoT framework views and challenges: Towards protecting drones as “things”},
author = { T. Lagkas and V. Argyriou and S. Bibi and P. Sarigiannidis},
url = {https://www.researchgate.net/publication/328968155_UAV_IoT_Framework_Views_and_Challenges_Towards_Protecting_Drones_as_Things},
doi = {10.3390/s18114015},
year = {2018},
date = {2018-01-01},
journal = {Sensors (Switzerland)},
volume = {18},
number = {11},
abstract = {Unmanned aerial vehicles (UAVs) have enormous potential in enabling new applications in various areas, ranging from military, security, medicine, and surveillance to traffic-monitoring applications. Lately, there has been heavy investment in the development of UAVs and multi-UAVs systems that can collaborate and complete missions more efficiently and economically. Emerging technologies such as 4G/5G networks have significant potential on UAVs equipped with cameras, sensors, and GPS receivers in delivering Internet of Things (IoT) services from great heights, creating an airborne domain of the IoT. However, there are many issues to be resolved before the effective use of UAVs can be made, including security, privacy, and management. As such, in this paper we review new UAV application areas enabled by the IoT and 5G technologies, analyze the sensor requirements, and overview solutions for fleet management over aerial-networking, privacy, and security challenges. Finally, we propose a framework that supports and enables these technologies on UAVs. The introduced framework provisions a holistic IoT architecture that enables the protection of UAVs as “flying” things in a collaborative networked environment. © 2018 by the authors. Licensee MDPI, Basel, Switzerland.},
keywords = {Drones, IoT, Privacy, security, UAV},
pubstate = {published},
tppubtype = {article}
}
Unmanned aerial vehicles (UAVs) have enormous potential in enabling new applications in various areas, ranging from military, security, medicine, and surveillance to traffic-monitoring applications. Lately, there has been heavy investment in the development of UAVs and multi-UAVs systems that can collaborate and complete missions more efficiently and economically. Emerging technologies such as 4G/5G networks have significant potential on UAVs equipped with cameras, sensors, and GPS receivers in delivering Internet of Things (IoT) services from great heights, creating an airborne domain of the IoT. However, there are many issues to be resolved before the effective use of UAVs can be made, including security, privacy, and management. As such, in this paper we review new UAV application areas enabled by the IoT and 5G technologies, analyze the sensor requirements, and overview solutions for fleet management over aerial-networking, privacy, and security challenges. Finally, we propose a framework that supports and enables these technologies on UAVs. The introduced framework provisions a holistic IoT architecture that enables the protection of UAVs as “flying” things in a collaborative networked environment. © 2018 by the authors. Licensee MDPI, Basel, Switzerland.
2017
P.I. Radoglou-Grammatikis; P.G. Sarigiannidis
Flow anomaly based intrusion detection system for Android mobile devices Conference
2017.
Abstract | BibTeX | Tags: Android, Artificial Neural Networks, intrusion detection system, Mobile, NetFlows, security | Links:
@conference{Radoglou-Grammatikis2017,
title = {Flow anomaly based intrusion detection system for Android mobile devices},
author = { P.I. Radoglou-Grammatikis and P.G. Sarigiannidis},
url = {https://www.researchgate.net/publication/316691657_Flow_Anomaly_Based_Intrusion_Detection_System_for_Android_Mobile_Devices},
doi = {10.1109/MOCAST.2017.7937625},
year = {2017},
date = {2017-01-01},
journal = {2017 6th International Conference on Modern Circuits and Systems Technologies, MOCAST 2017},
abstract = {The penetration of the modern mobile devices is progressively gaining ground in today's cognitive applications and services. Several applications have become part of the smartphone capabilities such as e-mail monitoring, Internet browsing, social networks activities, etc. However, the increased computation and storage capabilities of smartphones have attracted more and more cyber attacks in terms of writing mobile malware for various purposes. In this paper, we present an intrusion detection system (IDS) for detecting the anomaly behaviors in Android mobile devices. The IDS continuously monitors the network traffic of the mobile device and collects various features of the NetFlows. An artificial neural network (ANN) gathers the data flows and determines whether there is an invasion or not. The proposed IDS is demonstrated in realistic conditions, where the accuracy of the systems reaches 85%. © 2017 IEEE.},
keywords = {Android, Artificial Neural Networks, intrusion detection system, Mobile, NetFlows, security},
pubstate = {published},
tppubtype = {conference}
}
The penetration of the modern mobile devices is progressively gaining ground in today's cognitive applications and services. Several applications have become part of the smartphone capabilities such as e-mail monitoring, Internet browsing, social networks activities, etc. However, the increased computation and storage capabilities of smartphones have attracted more and more cyber attacks in terms of writing mobile malware for various purposes. In this paper, we present an intrusion detection system (IDS) for detecting the anomaly behaviors in Android mobile devices. The IDS continuously monitors the network traffic of the mobile device and collects various features of the NetFlows. An artificial neural network (ANN) gathers the data flows and determines whether there is an invasion or not. The proposed IDS is demonstrated in realistic conditions, where the accuracy of the systems reaches 85%. © 2017 IEEE.
P. Sarigiannidis; E. Karapistoli; A.A. Economides
Modeling the Internet of Things under Attack: A G-network Approach Journal Article
In: IEEE Internet of Things Journal, vol. 4, no. 6, pp. 1964-1977, 2017.
Abstract | BibTeX | Tags: G-networks, Internet of Things (IoT), Modeling, queuing theory, security | Links:
@article{Sarigiannidis20171964,
title = {Modeling the Internet of Things under Attack: A G-network Approach},
author = { P. Sarigiannidis and E. Karapistoli and A.A. Economides},
url = {https://www.researchgate.net/publication/317867935_Modelling_the_Internet_of_Things_Under_Attack_A_G-network_Approach?_sg=nQGxFUwlDGkq6bJAkluGr9ICZ80minya34gpJdFzE990HU4AFYuPRV760oFW4FmaMbAYtNSeFztuzGo},
doi = {10.1109/JIOT.2017.2719623},
year = {2017},
date = {2017-01-01},
journal = {IEEE Internet of Things Journal},
volume = {4},
number = {6},
pages = {1964-1977},
abstract = {This paper introduces a novel, analytic framework for modeling security attacks in Internet of Things (IoT) infrastructures. The devised model is quite generic, and as such, it could flexibly be adapted to various IoT architectures. Its flexibility lies in the underlying theory, it is based on a dynamic G-network, where the positive arrivals denote the data streams that originated from the various data collection networks (e.g., sensor networks), while the negative arrivals denote the securit attacks that result in data losses (e.g., jamming attacks). In addition, we take into account the intensity of an attack by considering both light and heavy attacks. The light attack implies simple losses of traffic data, while the heavy attack causes massive data loss. The introduced model is solved subject to the arrival and departure rates in terms of: 1) average number of data packets in the application domain and 2) attack impact (loss rate). A comprehensive verification discussion accompanied by numerous numerical results verify the accuracy of the proposed model. Moreover, the assessment of the presented model highlights notable operation characteristics of the underlying IoT system under light and heavy attacks. © 2017 IEEE.},
keywords = {G-networks, Internet of Things (IoT), Modeling, queuing theory, security},
pubstate = {published},
tppubtype = {article}
}
This paper introduces a novel, analytic framework for modeling security attacks in Internet of Things (IoT) infrastructures. The devised model is quite generic, and as such, it could flexibly be adapted to various IoT architectures. Its flexibility lies in the underlying theory, it is based on a dynamic G-network, where the positive arrivals denote the data streams that originated from the various data collection networks (e.g., sensor networks), while the negative arrivals denote the securit attacks that result in data losses (e.g., jamming attacks). In addition, we take into account the intensity of an attack by considering both light and heavy attacks. The light attack implies simple losses of traffic data, while the heavy attack causes massive data loss. The introduced model is solved subject to the arrival and departure rates in terms of: 1) average number of data packets in the application domain and 2) attack impact (loss rate). A comprehensive verification discussion accompanied by numerous numerical results verify the accuracy of the proposed model. Moreover, the assessment of the presented model highlights notable operation characteristics of the underlying IoT system under light and heavy attacks. © 2017 IEEE.
Address
Internet of Things and Applications Lab
Department of Electrical and Computer Engineering
University of Western Macedonia Campus
ZEP Area, Kozani 50100
Greece
Contact Information
tel: +30 2461 056527
Email: ithaca@uowm.gr
