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2020-12-07
Allig, C., Leinmüller, T., Mittal, P., Wanielik, G..  2019.  Trustworthiness Estimation of Entities within Collective Perception. 2019 IEEE Vehicular Networking Conference (VNC). :1–8.
The idea behind collective perception is to improve vehicles' awareness about their surroundings. Every vehicle shares information describing its perceived environment by means of V2X communication. Similar to other information shared using V2X communication, collective perception information is potentially safety relevant, which means there is a need to assess the reliability and quality of received information before further processing. Transmitted information may have been forged by attackers or contain inconsistencies e.g. caused by malfunctions. This paper introduces a novel approach for estimating a belief that a pair of entities, e.g. two remote vehicles or the host vehicle and a remote vehicle, within a Vehicular ad hoc Network (VANET) are both trustworthy. The method updates the belief based on the consistency of the data that both entities provide. The evaluation shows that the proposed method is able to identify forged information.
Xu, M., Huber, M., Sun, Z., England, P., Peinado, M., Lee, S., Marochko, A., Mattoon, D., Spiger, R., Thom, S..  2019.  Dominance as a New Trusted Computing Primitive for the Internet of Things. 2019 IEEE Symposium on Security and Privacy (SP). :1415–1430.
The Internet of Things (IoT) is rapidly emerging as one of the dominant computing paradigms of this decade. Applications range from in-home entertainment to large-scale industrial deployments such as controlling assembly lines and monitoring traffic. While IoT devices are in many respects similar to traditional computers, user expectations and deployment scenarios as well as cost and hardware constraints are sufficiently different to create new security challenges as well as new opportunities. This is especially true for large-scale IoT deployments in which a central entity deploys and controls a large number of IoT devices with minimal human interaction. Like traditional computers, IoT devices are subject to attack and compromise. Large IoT deployments consisting of many nearly identical devices are especially attractive targets. At the same time, recovery from root compromise by conventional means becomes costly and slow, even more so if the devices are dispersed over a large geographical area. In the worst case, technicians have to travel to all devices and manually recover them. Data center solutions such as the Intelligent Platform Management Interface (IPMI) which rely on separate service processors and network connections are not only not supported by existing IoT hardware, but are unlikely to be in the foreseeable future due to the cost constraints of mainstream IoT devices. This paper presents CIDER, a system that can recover IoT devices within a short amount of time, even if attackers have taken root control of every device in a large deployment. The recovery requires minimal manual intervention. After the administrator has identified the compromise and produced an updated firmware image, he/she can instruct CIDER to force the devices to reset and to install the patched firmware on the devices. We demonstrate the universality and practicality of CIDER by implementing it on three popular IoT platforms (HummingBoard Edge, Raspberry Pi Compute Module 3 and Nucleo-L476RG) spanning the range from high to low end. Our evaluation shows that the performance overhead of CIDER is generally negligible.
2020-11-30
Georgakopoulos, D..  2019.  A Global IoT Device Discovery and Integration Vision. 2019 IEEE 5th International Conference on Collaboration and Internet Computing (CIC). :214–221.
This paper presents the vision of establishing a global service for Global IoT Device Discovery and Integration (GIDDI). The establishment of a GIDDI will: (1) make IoT application development more efficient and cost-effective via enabling sharing and reuse of existing IoT devices owned and maintained by different providers, and (2) promote deployment of new IoT devices supported by a revenue generation scheme for their providers. More specifically, this paper proposes a distributed IoT blockchain ledger that is specifically designed for managing the metadata needed to describe IoT devices and the data they produce. This GIDDI Blockchain is Internet-owned (i.e., it is not controlled by any individual or organization) and is Internet-scaled (i.e., it can support the discovery and reuse billions of IoT devices). The paper also proposes a GIDDI Marketplace that provides the functionality needed for IoT device registration, query, integration, payment and security via the proposed GIDDI Blockchain. We outline the GIDDI Blockchain and Marketplace implementation. We also discuss ongoing research for automatically mining the IoT Device metadata needed for IoT Device query and integration from the data produce. This significantly reduces the need for IoT device providers to supply the metadata descriptions the devices and the data they produce during the registration of IoT Devices in the GIDDI Blockchain.
2020-11-20
Semwal, S., Badoni, M., Saxena, N..  2019.  Smart Meters for Domestic Consumers: Innovative Methods for Identifying Appliances using NIALM. 2019 Women Institute of Technology Conference on Electrical and Computer Engineering (WITCON ECE). :81—90.
A country drives by their people and the electricity energy, the availability of the electricity power reflects the strength of that country. All most everything depends on the electricity energy, So it is become very important that we use the available energy very efficiently, and here the energy management come in the picture and Non Intrusive appliance Load monitoring (NIALM) is the part of energy management, in which the energy consumption by the particular load is monitored without any intrusion of wire/circuit. In literature, NIALM has been discussed as a monitoring process for conservation of energy using single point sensing (SPS) for extraction of aggregate signal of the appliances' features, ignoring the second function of demand response (DR) assuming that it would be manual or sensor-based. This assumption is not implementable in developing countries like India, because of requirement of extra cost of sensors, and privacy concerns. Surprisingly, despite decades of research on NIALM, none of the suggested procedures has resulted in commercial application. This paper highlights the causes behind non- commercialization, and proposes a viable and easy solution worthy of commercial exploitation both for monitoring and DR management for outage reduction in respect of Indian domestic consumers. Using a approach of multi point sensing (MPS), combined with Independent Component Analysis (ICA), experiments has been done in laboratory environment and CPWD specification has been followed.
2020-11-17
Abdelzaher, T., Ayanian, N., Basar, T., Diggavi, S., Diesner, J., Ganesan, D., Govindan, R., Jha, S., Lepoint, T., Marlin, B. et al..  2018.  Toward an Internet of Battlefield Things: A Resilience Perspective. Computer. 51:24—36.

The Internet of Battlefield Things (IoBT) might be one of the most expensive cyber-physical systems of the next decade, yet much research remains to develop its fundamental enablers. A challenge that distinguishes the IoBT from its civilian counterparts is resilience to a much larger spectrum of threats.

Tosh, D. K., Shetty, S., Foytik, P., Njilla, L., Kamhoua, C. A..  2018.  Blockchain-Empowered Secure Internet -of- Battlefield Things (IoBT) Architecture. MILCOM 2018 - 2018 IEEE Military Communications Conference (MILCOM). :593—598.

Internet of Things (IoT) technology is emerging to advance the modern defense and warfare applications because the battlefield things, such as combat equipment, warfighters, and vehicles, can sense and disseminate information from the battlefield to enable real-time decision making on military operations and enhance autonomy in the battlefield. Since this Internet-of-Battlefield Things (IoBT) environment is highly heterogeneous in terms of devices, network standards, platforms, connectivity, and so on, it introduces trust, security, and privacy challenges when battlefield entities exchange information with each other. To address these issues, we propose a Blockchain-empowered auditable platform for IoBT and describe its architectural components, such as battlefield-sensing layer, network layer, and consensus and service layer, in depth. In addition to the proposed layered architecture, this paper also presents several open research challenges involved in each layer to realize the Blockchain-enabled IoBT platform.

Poltronieri, F., Sadler, L., Benincasa, G., Gregory, T., Harrell, J. M., Metu, S., Moulton, C..  2018.  Enabling Efficient and Interoperable Control of IoBT Devices in a Multi-Force Environment. MILCOM 2018 - 2018 IEEE Military Communications Conference (MILCOM). :757—762.

Efficient application of Internet of Battlefield Things (IoBT) technology on the battlefield calls for innovative solutions to control and manage the deluge of heterogeneous IoBT devices. This paper presents an innovative paradigm to address heterogeneity in controlling IoBT and IoT devices, enabling multi-force cooperation in challenging battlefield scenarios.

Russell, S., Abdelzaher, T., Suri, N..  2019.  Multi-Domain Effects and the Internet of Battlefield Things. MILCOM 2019 - 2019 IEEE Military Communications Conference (MILCOM). :724—730.

This paper reviews the definitions and characteristics of military effects, the Internet of Battlefield Things (IoBT), and their impact on decision processes in a Multi-Domain Operating environment (MDO). The aspects of contemporary military decision-processes are illustrated and an MDO Effect Loop decision process is introduced. We examine the concept of IoBT effects and their implications in MDO. These implications suggest that when considering the concept of MDO, as a doctrine, the technological advances of IoBTs empower enhancements in decision frameworks and increase the viability of novel operational approaches and options for military effects.

Agadakos, I., Ciocarlie, G. F., Copos, B., George, J., Leslie, N., Michaelis, J..  2019.  Security for Resilient IoBT Systems: Emerging Research Directions. IEEE INFOCOM 2019 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS). :1—6.

Continued advances in IoT technology have prompted new investigation into its usage for military operations, both to augment and complement existing military sensing assets and support next-generation artificial intelligence and machine learning systems. Under the emerging Internet of Battlefield Things (IoBT) paradigm, a multitude of operational conditions (e.g., diverse asset ownership, degraded networking infrastructure, adversary activities) necessitate the development of novel security techniques, centered on establishment of trust for individual assets and supporting resilience of broader systems. To advance current IoBT efforts, a set of research directions are proposed that aim to fundamentally address the issues of trust and trustworthiness in contested battlefield environments, building on prior research in the cybersecurity domain. These research directions focus on two themes: (1) Supporting trust assessment for known/unknown IoT assets; (2) Ensuring continued trust of known IoBT assets and systems.

Agadakos, I., Ciocarlie, G. F., Copos, B., Emmi, M., George, J., Leslie, N., Michaelis, J..  2019.  Application of Trust Assessment Techniques to IoBT Systems. MILCOM 2019 - 2019 IEEE Military Communications Conference (MILCOM). :833—840.

Continued advances in IoT technology have prompted new investigation into its usage for military operations, both to augment and complement existing military sensing assets and support next-generation artificial intelligence and machine learning systems. Under the emerging Internet of Battlefield Things (IoBT) paradigm, current operational conditions necessitate the development of novel security techniques, centered on establishment of trust for individual assets and supporting resilience of broader systems. To advance current IoBT efforts, a collection of prior-developed cybersecurity techniques is reviewed for applicability to conditions presented by IoBT operational environments (e.g., diverse asset ownership, degraded networking infrastructure, adversary activities) through use of supporting case study examples. The research techniques covered focus on two themes: (1) Supporting trust assessment for known/unknown IoT assets; (2) ensuring continued trust of known IoT assets and IoBT systems.

2020-11-16
Januário, F., Cardoso, A., Gil, P..  2019.  A Multi-Agent Middleware for Resilience Enhancement in Heterogeneous Control Systems. 2019 IEEE International Conference on Industrial Technology (ICIT). :988–993.
Modern computing networks that enable distributed computing are comprised of a wide range of heterogeneous devices with different levels of resources, which are interconnected by different networking technologies and communication protocols. This integration, together with the state of the art technologies, has brought into play new uncertainties, associated with physical world and the cyber space. In heterogeneous networked control systems environments, awareness and resilience are two important properties that these systems should bear and comply with. In this work the problem of resilience enhancement in heterogeneous networked control systems is addressed based on a distributed middleware, which is propped up on a hierarchical multi-agent framework, where each of the constituent agents is devoted to a specific task. The proposed architecture takes into account physical and cyber vulnerabilities and ensures state and context awareness, and a minimum level of acceptable operational performance, in response to physical and cyber disturbances. Experiments on a IPv6-based test-bed proved the relevance and benefits offered by the proposed architecture.
2020-11-02
Fraiji, Yosra, Ben Azzouz, Lamia, Trojet, Wassim, Saidane, Leila Azouz.  2018.  Cyber security issues of Internet of electric vehicles. 2018 IEEE Wireless Communications and Networking Conference (WCNC). :1—6.

The use of Electric Vehicle (EV) is growing rapidly due to its environmental benefits. However, the major problem of these vehicles is their limited battery, the lack of charging stations and the re-charge time. Introducing Information and Communication Technologies, in the field of EV, will improve energy efficiency, energy consumption predictions, availability of charging stations, etc. The Internet of Vehicles based only on Electric Vehicles (IoEV) is a complex system. It is composed of vehicles, humans, sensors, road infrastructure and charging stations. All these entities communicate using several communication technologies (ZigBee, 802.11p, cellular networks, etc). IoEV is therefore vulnerable to significant attacks such as DoS, false data injection, modification. Hence, security is a crucial factor for the development and the wide deployment of Internet of Electric Vehicles (IoEV). In this paper, we present an overview of security issues of the IoEV architecture and we highlight open issues that make the IoEV security a challenging research area in the future.

Anzer, Ayesha, Elhadef, Mourad.  2018.  A Multilayer Perceptron-Based Distributed Intrusion Detection System for Internet of Vehicles. 2018 IEEE 4th International Conference on Collaboration and Internet Computing (CIC). :438—445.

Security of Internet of vehicles (IoV) is critical as it promises to provide with safer and secure driving. IoV relies on VANETs which is based on V2V (Vehicle to Vehicle) communication. The vehicles are integrated with various sensors and embedded systems allowing them to gather data related to the situation on the road. The collected data can be information associated with a car accident, the congested highway ahead, parked car, etc. This information exchanged with other neighboring vehicles on the road to promote safe driving. IoV networks are vulnerable to various security attacks. The V2V communication comprises specific vulnerabilities which can be manipulated by attackers to compromise the whole network. In this paper, we concentrate on intrusion detection in IoV and propose a multilayer perceptron (MLP) neural network to detect intruders or attackers on an IoV network. Results are in the form of prediction, classification reports, and confusion matrix. A thorough simulation study demonstrates the effectiveness of the new MLP-based intrusion detection system.

Bloom, Gedare, Alsulami, Bassma, Nwafor, Ebelechukwu, Bertolotti, Ivan Cibrario.  2018.  Design patterns for the industrial Internet of Things. 2018 14th IEEE International Workshop on Factory Communication Systems (WFCS). :1—10.
The Internet of Things (IoT) is a vast collection of interconnected sensors, devices, and services that share data and information over the Internet with the objective of leveraging multiple information sources to optimize related systems. The technologies associated with the IoT have significantly improved the quality of many existing applications by reducing costs, improving functionality, increasing access to resources, and enhancing automation. The adoption of IoT by industries has led to the next industrial revolution: Industry 4.0. The rise of the Industrial IoT (IIoT) promises to enhance factory management, process optimization, worker safety, and more. However, the rollout of the IIoT is not without significant issues, and many of these act as major barriers that prevent fully achieving the vision of Industry 4.0. One major area of concern is the security and privacy of the massive datasets that are captured and stored, which may leak information about intellectual property, trade secrets, and other competitive knowledge. As a way forward toward solving security and privacy concerns, we aim in this paper to identify common input-output (I/O) design patterns that exist in applications of the IIoT. These design patterns enable constructing an abstract model representation of data flow semantics used by such applications, and therefore better understand how to secure the information related to IIoT operations. In this paper, we describe communication protocols and identify common I/O design patterns for IIoT applications with an emphasis on data flow in edge devices, which, in the industrial control system (ICS) setting, are most often involved in process control or monitoring.
2020-10-29
Sajyth, RB, Sujatha, G.  2018.  Design of Data Confidential and Reliable Bee Clustering Routing Protocol in MANET. 2018 International Conference on Computer Communication and Informatics (ICCCI). :1—7.
Mobile ad hoc network (MANET) requires extraneous energy effectualness and legion intelligence for which a best clustered based approach is pertained called the “Bee-Ad Hoc-C”. In MANET the mechanism of multi-hop routing is imperative but may leads to a challenging issue like lack of data privacy during communication. ECC (Elliptical Curve Cryptography) is integrated with the Bee clustering approach to provide an energy efficient and secure data delivery system. Even though it ensures data confidentiality, data reliability is still disputable such as data dropping attack, Black hole attack (Attacker router drops the data without forwarding to destination). In such cases the technique of overhearing is utilized by the neighbor routers and the packet forwarding statistics are measured based on the ratio between the received and forwarded packets. The presence of attack is detected if the packet forwarding ratio is poor in the network which paves a way to the alternate path identification for a reliable data transmission. The proposed work is an integration of SC-AODV along with ECC in Bee clustering approach with an extra added overhearing technique which n on the whole ensures data confidentiality, data reliability and energy efficiency.
2020-10-26
George, Chinnu Mary, Luke Babu, Sharon.  2019.  A Scalable Correlation Clustering strategy in Location Privacy for Wireless Sensor Networks against a Universal Adversary. 2019 International Conference on Computational Intelligence and Knowledge Economy (ICCIKE). :1–3.
Wireless network sensors are outsized number of pocket sized sensors deployed in the area under surveillance. The sensor network is very sensitive to unattended and remote Environment with a wide variety of applications in the agriculture, health, industry there a lot of challenges being faced with respect to the energy, mobility, security. The paper presents with regard to the context based surrounding information which has location privacy to the source node against an adversary who sees the network at a whole so a correlation strategy is proposed for providing the privacy.
Zhang, Kewang, Zahng, Qiong.  2018.  Preserve Location Privacy for Cyber-Physical Systems with Addresses Hashing at Data Link Layer. 2018 IEEE 20th International Conference on High Performance Computing and Communications; IEEE 16th International Conference on Smart City; IEEE 4th International Conference on Data Science and Systems (HPCC/SmartCity/DSS). :1028–1032.
Due to their low complexity and robustness in nature, wireless sensor networks are a key component in cyber-physical system. The integration of wireless sensor network in cyber-physical system provides immense benefits in distributed controlled environment. However, the open nature of the wireless medium makes resource-constrained WSN vulnerable to unauthorized interception and detection. Privacy is becoming one of the major issues that jeopardize the successful deployment of WSN. In this paper, we propose a scheme named HASHA to provide location privacy. Different from previous approaches, HASHA protect nodes' location privacy at data link layer. It is well known that payload at data link layer frame is well protected through cryptosystem, but addresses at data link layer leaves unprotected. The adversaries can identify nodes in the network easily by capturing frames and check the source and destination addresses. If both addresses are well protected and unknown to the adversaries, they cannot identify nodes of the targeted networks, rendering it very difficult to launch traffic analysis and locate subjects. Simulation and analytical results demonstrate that our scheme provides stronger privacy protection and requires much less energy.
Rimjhim, Roy, Pradeep Kumar, Prakash Singh, Jyoti.  2018.  Encircling the Base Station for Source Location Privacy in Wireless Sensor Networks. 2018 3rd International Conference on Computational Systems and Information Technology for Sustainable Solutions (CSITSS). :307–312.
Location Privacy breach in Wireless Sensor Networks (WSNs) cannot be controlled by encryption techniques as all the communications are signal based. Signal strength can be analyzed to reveal many routing information. Adversary takes advantage of this and tracks the incoming packet to know the direction of the packet. With the information of location of origin of packets, the Source is also exposed which is generating packets on sensing any object. Thus, the location of subject is exposed. For protecting such privacy breaches, routing schemes are used which create anonymization or diverts the adversary. In this paper, we are using `Dummy' packets that will be inserted into real traffic to confuse the adversary. The dummy packets are such inserted that they encircle the Sink or Base Station. These Dummy packets are send with a value of TTL (Time To Live) field such that they travel only a few hops. Since adversary starts backtracking from the Sink, it will be trapped in the dummy traffic. In our protocol, we are confusing adversary without introducing any delay in packet delivery. Adversary uses two common methods for knowing the source i.e. Traffic Analysis and Back-tracing. Mathematically and experimentally, our proposal is sound for both type of methods. Overhead is also balanced as packets will not live long.
2020-10-19
Hasan, Khondokar Fida, Kaur, Tarandeep, Hasan, Md. Mhedi, Feng, Yanming.  2019.  Cognitive Internet of Vehicles: Motivation, Layered Architecture and Security Issues. 2019 International Conference on Sustainable Technologies for Industry 4.0 (STI). :1–6.
Over the past few years, we have experienced great technological advancements in the information and communication field, which has significantly contributed to reshaping the Intelligent Transportation System (ITS) concept. Evolving from the platform of a collection of sensors aiming to collect data, the data exchanged paradigm among vehicles is shifted from the local network to the cloud. With the introduction of cloud and edge computing along with ubiquitous 5G mobile network, it is expected to see the role of Artificial Intelligence (AI) in data processing and smart decision imminent. So as to fully understand the future automobile scenario in this verge of industrial revolution 4.0, it is necessary first of all to get a clear understanding of the cutting-edge technologies that going to take place in the automotive ecosystem so that the cyber-physical impact on transportation system can be measured. CIoV, which is abbreviated from Cognitive Internet of Vehicle, is one of the recently proposed architectures of the technological evolution in transportation, and it has amassed great attention. It introduces cloud-based artificial intelligence and machine learning into transportation system. What are the future expectations of CIoV? To fully contemplate this architecture's future potentials, and milestones set to achieve, it is crucial to understand all the technologies that leaned into it. Also, the security issues to meet the security requirements of its practical implementation. Aiming to that, this paper presents the evolution of CIoV along with the layer abstractions to outline the distinctive functional parts of the proposed architecture. It also gives an investigation of the prime security and privacy issues associated with technological evolution to take measures.
2020-10-14
Xie, Kun, Li, Xiaocan, Wang, Xin, Xie, Gaogang, Xie, Dongliang, Li, Zhenyu, Wen, Jigang, Diao, Zulong.  2019.  Quick and Accurate False Data Detection in Mobile Crowd Sensing. IEEE INFOCOM 2019 - IEEE Conference on Computer Communications. :2215—2223.

With the proliferation of smartphones, a novel sensing paradigm called Mobile Crowd Sensing (MCS) has emerged very recently. However, the attacks and faults in MCS cause a serious false data problem. Observing the intrinsic low dimensionality of general monitoring data and the sparsity of false data, false data detection can be performed based on the separation of normal data and anomalies. Although the existing separation algorithm based on Direct Robust Matrix Factorization (DRMF) is proven to be effective, requiring iteratively performing Singular Value Decomposition (SVD) for low-rank matrix approximation would result in a prohibitively high accumulated computation cost when the data matrix is large. In this work, we observe the quick false data location feature from our empirical study of DRMF, based on which we propose an intelligent Light weight Low Rank and False Matrix Separation algorithm (LightLRFMS) that can reuse the previous result of the matrix decomposition to deduce the one for the current iteration step. Our algorithm can largely speed up the whole iteration process. From a theoretical perspective, we validate that LightLRFMS only requires one round of SVD computation and thus has very low computation cost. We have done extensive experiments using a PM 2.5 air condition trace and a road traffic trace. Our results demonstrate that LightLRFMS can achieve very good false data detection performance with the same highest detection accuracy as DRMF but with up to 10 times faster speed thanks to its lower computation cost.

2020-10-12
Khayat, Mohamad, Barka, Ezedin, Sallabi, Farag.  2019.  SDN\_Based Secure Healthcare Monitoring System(SDN-SHMS). 2019 28th International Conference on Computer Communication and Networks (ICCCN). :1–7.
Healthcare experts and researchers have been promoting the need for IoT-based remote health monitoring systems that take care of the health of elderly people. However, such systems may generate large amounts of data, which makes the security and privacy of such data to become imperative. This paper studies the security and privacy concerns of the existing Healthcare Monitoring System (HMS) and proposes a reference architecture (security integration framework) for managing IoT-based healthcare monitoring systems that ensures security, privacy, and reliable service delivery for patients and elderly people to reduce and avoid health related risks. Our proposed framework will be in the form of state-of-the-art Security Platform, for HMS, using the emerging Software Defined Network (SDN) networking paradigm. Our proposed integration framework eliminates the dependency on specific Software or vendor for different security systems, and allows for the benefits from the functional and secure applications, and services provided by the SDN platform.
2020-10-06
Tomić, Ivana, Breza, Michael J., Jackson, Greg, Bhatia, Laksh, McCann, Julie A..  2018.  Design and Evaluation of Jamming Resilient Cyber-Physical Systems. 2018 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData). :687—694.

There is a growing movement to retrofit ageing, large scale infrastructures, such as water networks, with wireless sensors and actuators. Next generation Cyber-Physical Systems (CPSs) are a tight integration of sensing, control, communication, computation and physical processes. The failure of any one of these components can cause a failure of the entire CPS. This represents a system design challenge to address these interdependencies. Wireless communication is unreliable and prone to cyber-attacks. An attack upon the wireless communication of CPS would prevent the communication of up-to-date information from the physical process to the controller. A controller without up-to-date information is unable to meet system's stability and performance guarantees. We focus on design approach to make CPSs secure and we evaluate their resilience to jamming attacks aimed at disrupting the system's wireless communication. We consider classic time-triggered control scheme and various resource-aware event-triggered control schemes. We evaluate these on a water network test-bed against three jamming strategies: constant, random, and protocol aware. Our test-bed results show that all schemes are very susceptible to constant and random jamming. We find that time-triggered control schemes are just as susceptible to protocol aware jamming, where some event-triggered control schemes are completely resilient to protocol aware jamming. Finally, we further enhance the resilience of an event-triggered control scheme through the addition of a dynamical estimator that estimates lost or corrupted data.

Januário, Fábio, Cardoso, Alberto, Gil, Paulo.  2018.  Resilience Enhancement through a Multi-agent Approach over Cyber-Physical Systems. 2018 10th International Conference on Information Technology and Electrical Engineering (ICITEE). :231—236.

Cyber-physical systems are an important component of most industrial infrastructures that allow the integration of control systems with state of the art information technologies. These systems aggregate distinct communication platforms and networked devices with different capabilities. This integration, has brought into play new uncertainties, not only from the tangible physical world, but also from a cyber space perspective. In light of this situation, awareness and resilience are invaluable properties of these kind of systems. The present work proposes an architecture based on a distributed middleware that relying on a hierarchical multi-agent framework for resilience enhancement. The proposed architecture takes into account physical and cyber vulnerabilities and guarantee state and context awareness, and a minimum level of acceptable operation, in response to physical disturbances and malicious attacks. This framework was evaluated on an IPv6 test-bed comprising several distributed devices, where performance and communication links health are analysed. Results from tests prove the relevance and benefits of the proposed approach.

Sullivan, Daniel, Colbert, Edward, Cowley, Jennifer.  2018.  Mission Resilience for Future Army Tactical Networks. 2018 Resilience Week (RWS). :11—14.

Cyber-physical systems are an integral component of weapons, sensors and autonomous vehicles, as well as cyber assets directly supporting tactical forces. Mission resilience of tactical networks affects command and control, which is important for successful military operations. Traditional engineering methods for mission assurance will not scale during battlefield operations. Commanders need useful mission resilience metrics to help them evaluate the ability of cyber assets to recover from incidents to fulfill mission essential functions. We develop 6 cyber resilience metrics for tactical network architectures. We also illuminate how psychometric modeling is necessary for future research to identify resilience metrics that are both applicable to the dynamic mission state and meaningful to commanders and planners.

2020-10-05
Mitra, Aritra, Abbas, Waseem, Sundaram, Shreyas.  2018.  On the Impact of Trusted Nodes in Resilient Distributed State Estimation of LTI Systems. 2018 IEEE Conference on Decision and Control (CDC). :4547—4552.

We address the problem of distributed state estimation of a linear dynamical process in an attack-prone environment. A network of sensors, some of which can be compromised by adversaries, aim to estimate the state of the process. In this context, we investigate the impact of making a small subset of the nodes immune to attacks, or “trusted”. Given a set of trusted nodes, we identify separate necessary and sufficient conditions for resilient distributed state estimation. We use such conditions to illustrate how even a small trusted set can achieve a desired degree of robustness (where the robustness metric is specific to the problem under consideration) that could otherwise only be achieved via additional measurement and communication-link augmentation. We then establish that, unfortunately, the problem of selecting trusted nodes is NP-hard. Finally, we develop an attack-resilient, provably-correct distributed state estimation algorithm that appropriately leverages the presence of the trusted nodes.