Biblio

Cyber-Physical Systems(CPS) have been experiencing a fast-growing process in recent decades, and related security issues also have become more important than ever before. To design an efficient defensive policy for operators and controllers is the utmost task to be considered. In this paper, a stochastic game-theoretic model is developed to study a CPS security problem by considering the interdependence between cyber and physical spaces of a CPS. The game model is solved with Minimax Q-learning for finding the mixed strategies equilibria. The numerical simulation revealed that the defensive factors and attack cost can affect the policies adopted by the system. From the perspective of the operator of a CPS, increasing successful defense probability in the phrase of disruption will help to improve the probability of defense strategy when there is a correlation between the cyber layer and the physical layer in a CPS. On the contrary side, the system defense probability will decrease as the total cost of the physical layer increases.

Enabled by the industrial Internet, intelligent transportation has made remarkable achievements such as autonomous vehicles by carnegie mellon university (CMU) Navlab, Google Cars, Tesla, etc. Autonomous vehicles benefit, in various aspects, from the cooperation of the industrial Internet and cyber-physical systems. In this process, users in autonomous vehicles submit query contents, such as service interests or user locations, to service providers. However, privacy concerns arise since the query contents are exposed when the users are enjoying the services queried. Existing works on privacy preservation of query contents rely on location perturbation or k-anonymity, and they suffer from insufficient protection of privacy or low query utility incurred by processing multiple queries for a single query content. To achieve sufficient privacy preservation and satisfactory query utility for autonomous vehicles querying services in cyber-physical systems, this article proposes a novel privacy notion of client-based personalized k-anonymity (CPkA). To measure the performance of CPkA, we present a privacy metric and a utility metric, based on which, we formulate two problems to achieve the optimal CPkA in term of privacy and utility. An approach, including two modules, to establish mechanisms which achieve the optimal CPkA is presented. The first module is to build in-group mechanisms for achieving the optimal privacy within each content group. The second module includes linear programming-based methods to compute the optimal grouping strategies. The in-group mechanisms and the grouping strategies are combined to establish optimal CPkA mechanisms, which achieve the optimal privacy or the optimal utility. We employ real-life datasets and synthetic prior distributions to evaluate the CPkA mechanisms established by our approach. The evaluation results illustrate the effectiveness and efficiency of the established mechanisms.

Consensus-based distributed microgrid energy management system is one of the most used distributed control strategies in the microgrid area. To improve its cybersecurity, the system needs to evaluate the trustworthiness of the participating agents in addition to the conventional cryptography efforts. This paper proposes a novel augmented reputation metric to evaluate the agents' trustworthiness in a distributed fashion. The proposed metric adopts a novel augmentation method to substantially improve the trust evaluation and attack detection performance under three typical difficult-to-detect attack patterns. The proposed metric is implemented and validated on a real-time HIL microgrid testbed.

In modern grid systems which is a typical cyber-physical System (CPS), information space and physical space are closely related. Once the communication link is interrupted, it will make a great damage to the power system. If the service path is too concentrated, the risk will be greatly increased. In order to solve this problem, this paper constructs a route planning algorithm that combines node load pressure, link load balance and service delay risk. At present, the existing intelligent algorithms are easy to fall into the local optimal value, so we chooses the deep reinforcement learning algorithm (DRL). Firstly, we build a risk assessment model. The node risk assessment index is established by using the node load pressure, and then the link risk assessment index is established by using the average service communication delay and link balance degree. The route planning problem is then solved by a route planning algorithm based on DRL. Finally, experiments are carried out in a simulation scenario of a power grid system. The results show that our method can find a lower risk path than the original Dijkstra algorithm and the Constraint-Dijkstra algorithm.

Supervisor synthesis enables the design of supervisory controllers for large cyber-physical systems, with high guarantees for functionality and safety. The complexity of the synthesis problem, however, increases exponentially with the number of system components in the cyber-physical system and the number of models of this system, often resulting in lengthy or even unsolvable synthesis procedures. In this paper, a new method is proposed for reducing the model of the system before synthesis to decrease the required computational time and effort. The method consists of three steps for model reduction, that are mainly based on symmetry in dependency graphs of the system. Dependency graphs visualize the components in the system and the relations between these components. The proposed method is applied in a case study on the design of a supervisory controller for a road tunnel. In this case study, the model reduction steps are described, and results are shown on the effectiveness of model reduction in terms of model size and synthesis time.

Nowadays energy systems in many countries improve and develop being based on the concept of deep integration of energy as well as infocomm grids. Thus, energy grids find the possibility to analyze the state of the whole system in real time, to predict the processes in it, to have interactive cooperation with the clients and to run the appliance. Such concept has been named Smart Grid. This work highlights the concept of Smart Grid, possible vectors of attacks and identification of attack of false data injection (FDI) into the flow of measuring received from the sensors. Identification is based on the use of spatial and temporal correlations in Smart Grids.

As any other infrastructure relying on cyber-physical systems (CPS), naval CPS are highly interconnected and collect considerable data streams, on which depend multiple command and navigation decisions. Being a data-driven decision system requiring optimized supervisory control on a permanent basis, it is critical to examine the CPS vulnerability to anomalies and their propagation. This paper presents an approach to detect CPS anomalies and estimate their propagation applying a quality assessed graph, which represents the CPS physical and digital subsystems, combined with system variables dependencies and a set of data and information quality measures vectors. Following the identification of variables dependencies and high-risk nodes in the CPS, data and information quality measures reveal how system variables are modified when an anomaly is detected, also indicating its propagation path. Taking as reference the normal state of a naval propulsion management system, four anomalies in the form of cyber-attacks - port scan, programmable logical controller stop, and man in the middle to change the motor speed and operation of a tank valve - were produced. Three anomalies were properly detected and their propagation path identified. These results suggest the feasibility of anomaly detection and estimation of propagation estimation in CPS, applying data and information quality analysis to a system graph.

Energy Internet is a typical cyber-physical system (CPS), in which the disturbance on cyber part may result in the operation risks on the physical part. In order to perform CPS assessment and research the interactive influence between cyber part and physical part, an integrated energy internet CPS model which adopts information flow matrix, energy control flow matrix and information energy hybrid flow matrix is proposed in this paper. The proposed model has a higher computational efficacy compared with simulation based approaches. Then, based on the proposed model, the influence of cyber disturbances such as data dislocation, data delay and data error on the physical part are studied. Finally, a 3 MW PET based energy internet CPS is built using PSCAD/EMTDC software. The simulation results prove the validity of the proposed model and the correctness of the interactive influence analysis.

The Classification of devices involved in authentication and classification of authentication systems by type and combination of protocols used are proposed. The system architecture for soft multi-factor authentication designed and simulated.

Trusted Platform Modules (TPMs) are specialized chips that store RSA keys specific to the host system for hardware authentication. The RSA keys refer to an encryption technology developed by RSA Data Security. The RSA algorithm accounts for the fact that there is no efficient way to factor extremely large numbers. Each TPM chip contains an RSA Key pair known as the Endorsement Key that cannot be accessed by software. The TPM contains an additional key, called the Attestation Identity Key that protects the device itself against unauthorized firmware and software modification by implementing hash functions on critical sections of the software and firmware before execution. As a result, the TPM can be used as a chip for handling encryption for a larger system to offer an additional layer of security. Furthermore, the TPM can also be used for managing encryption keys, as a Storage Root Key is created when a user or administrator takes ownership of the system. However, merging the TPM into a system does come with additional costs along with potential benefits. This paper focuses on integrating a TPM into a system implemented on an ARM processor that engages with power electronics, and then presents the security benefits associated with a TPM.

The ability to advance the state of the art in automated cybersecurity protections for industrial control systems (ICS) has as a prerequisite of understanding the trade-off space. That is, to enable a cyber feedback loop in a control system environment you must first consider both the security mitigation available, the benefits and the impacts to the control system functionality when the mitigation is used. More damaging impacts could be precipitated that the mitigation was intended to rectify. This paper details networked ICS that controls a simulation of the frequency response represented with the swing equation. The microgrid loads and base generation can be balanced through the control of an emulated battery and power inverter. The simulated plant, which is implemented in Raspberry Pi computers, provides an inexpensive platform to realize the physical effects of cyber attacks to show the trade-offs of available mitigating actions. This network design can include a commercial ICS controller and simple plant or emulated plant to introduce real world implementation of feedback controls, and provides a scalable, physical effects measurable microgrid for cyber resilience analysis (SPEMMCRA).

Paper proposed an approach to estimating the sustainability of cyber-physical systems based on system state analysis. Authors suggested that sustainability is the system ability to reconfigure for recovering from attacking influences. Proposed a new criterion for cyber-physical systems sustainability assessment based on spectral graph theory. Numerical calculation of the criterion is based on distribution properties of the graph spectrum - the set of eigenvalues of the adjacency matrix corresponding to the graph. Experimental results have shown dependency of change in Δσ, difference between initial value of σstart and final σstop, on working route length, and on graph connectivity was revealed. This parameter is proposed to use as a criterion for CPS sustainability.

Cyber-physical systems (CPSs) encompass a network of sensors and actuators that are monitored, controlled and integrated by a computing and communication core. As autonomous underwater vehicles (AUVs) become more intelligent and connected, new use cases in ocean production, security and environmental monitoring become feasible. Swarms of small, affordable and hydrobatic AUVs can be beneficial in substance cloud tracking and algae farming, and a CPS linking the AUVs with multi-fidelity simulations can improve performance while reducing risks and costs. In this paper, we present a CPS concept tightly linking the AUV network in ROS to virtual validation using Simulink and Gazebo. A robust hardware-software interface using the open-source UAVCAN-ROS bridge is described for enabling hardware-in-the-loop validation. Hardware features of the hydrobatic SAM AUV are described, with a focus on subsystem integration. Results presented include pre-tuning of controllers, validation of mission plans in simulation and real time subsystem performance in tank tests. These first results demonstrate the interconnection between different system elements and offer a proof of concept.

The network attack graph is a powerful tool for analyzing network security, but the generation of a large-scale graph is non-trivial. The main challenge is from the explosion of network state space, which greatly increases time and storage costs. In this paper, three parallel algorithms are proposed to generate scalable attack graphs. An OpenMP-based programming implementation is used to test their performance. Compared with the serial algorithm, the best performance from the proposed algorithms provides a 10X speedup.

To promote InGaP solar cell efficiency toward the theoretical limit, one promising approach is to incorporate multiple quantum wells (MQWs) into the InGaP host and improve its open-circuit voltage by facilitating radiative carrier recombination owing to carrier confinement. In this research, we demonstrate numerically that a strain-balanced (SB) In1-xGaxP/In1-yGayP MQW enhances confined carrier density while degrades the effective carrier mobility. However, a smart design of the MQW structure is possible by considering quantitatively the trade-off between carrier confinement effect and carrier transport, and MQW can be advantageous over the InGaP bulk material for boosting photovoltaic efficiency.

The effects of quantum confinement on the charge distribution in planar Double-Gate (DG) SOI (Siliconon-Insulator) MOSFETs were examined, for sub-10 nm SOI film thicknesses (tsi $łeq$ 10 nm), by modeling the potential experienced by the charge carriers as that of an an-harmonic oscillator potential, consistent with the inherent structural symmetry of nanoscale symmetric DGSOI MOSFETs. By solving the 1-D Poisson's equation using this potential, the results obtained were validated through comparisons with TCAD simulations. The present model satisfactorily predicted the electron density and channel charge density for a wide range of SOI channel thicknesses and gate voltages.

The smart grid is a complex cyber-physical system (CPS) that poses challenges related to scale, integration, interoperability, processes, governance, and human elements. The US National Institute of Standards and Technology (NIST) and its government, university and industry collaborators, developed an approach, called CPS Framework, to reasoning about CPS across multiple levels of concern and competency, including trustworthiness, privacy, reliability, and regulatory. The approach uses ontology and reasoning techniques to achieve a greater understanding of the interdependencies among the elements of the CPS Framework model applied to use cases. This paper demonstrates that the approach extends naturally to automated and manual decision-making for smart grids: we apply it to smart grid use cases, and illustrate how it can be used to analyze grid topologies and address concerns about the smart grid. Smart grid stakeholders, whose decision making may be assisted by this approach, include planners, designers and operators.

The new generation ship integrated power system (IPS) realizes high level informatization for various physical equipments, and gradually develops to a cyber-physical system (CPS). The future trend is collecting ship big data to achieve data-driven intelligence for IPS. However, traditional relational data management framework becomes inefficient to handle the real-time data processing in ship integrated power cyber-physics system. In order to process the large-scale real-time data that collected from numerous sensors by field bus of IPS devices within acceptable latency, especially for handling the semi-structured and non-structured data. This paper proposes a novel key-value data model based real-time data management framework, which enables batch processing and distributed deployment to acquire time-efficiency as well as system scalable. We implement a real-time data management prototype system based on an open source in-memory key-value store. Finally, the evaluation results from the prototype verify the advantages of novel framework compared with traditional solution.

Cyber-Physical System (CPS) and Cloud Computing are emerging and important research fields in recent years. It is a current trend that CPS combines with Cloud Computing. Compared with traditional CPS, Cloud can improve its performance, but Cloud failures occur occasionally. The existing cloud-based CPS architectures rely too much on the Cloud, ignoring the risk and problems caused by Cloud failures, thus making the reliability of CPS not guaranteed. In order to solve the risk and problems above, spare parts are involved based on the research of cloud-based CPS. An architecture of cloud-based CPS with spare parts is proposed and two solutions for spare parts are designed. Agricultural intelligent temperature control system is used as an example to model and simulate the proposed architecture and solutions using Simulink. The simulation results prove the effectiveness of the proposed architecture and solutions, which enhance the reliability of cloud-based CPS.

This paper surveys some prior work regarding attack models in a cyber-physical system and discusses the potential benefits. For comparison, the full paper will model a bad data injection attack scenario in power grid using the surveyed prior work.

The timing characteristics of cache, a high-speed storage between the fast CPU and the slow memory, may reveal sensitive information of a program, thus allowing an adversary to conduct side-channel attacks. Existing methods for detecting timing leaks either ignore cache all together or focus only on passive leaks generated by the program itself, without considering leaks that are made possible by concurrently running some other threads. In this work, we show that timing-leak-freedom is not a compositional property: a program that is not leaky when running alone may become leaky when interleaved with other threads. Thus, we develop a new method, named adversarial symbolic execution, to detect such leaks. It systematically explores both the feasible program paths and their interleavings while modeling the cache, and leverages an SMT solver to decide if there are timing leaks. We have implemented our method in LLVM and evaluated it on a set of real-world ciphers with 14,455 lines of C code in total. Our experiments demonstrate both the efficiency of our method and its effectiveness in detecting side-channel leaks.

With the advancement in technology, inclusion of Information and Communication Technology (ICT) in the conventional Electrical Power Grid has become evident. The combination of communication system with physical system makes it cyber-physical system (CPS). Though the advantages of this improvement in technology are numerous, there exist certain issues with the system. Security and privacy concerns of a CPS are a major field and research and the insight of which is content of this paper.

Applications in C/C++ are notoriously prone to memory corruptions. With significant research efforts devoted to this area of study, the security threats posed by previously popular vulnerabilities, such as stack and heap overflows, are not as serious as before. Instead, we have seen the meteoric rise of attacks exploiting use-after-free (UaF) vulnerabilities in recent years, which root in pointers pointing to freed memory (i.e., dangling pointers). Although various approaches have been proposed to harden software against UaF, none of them can achieve robustness and efficiency at the same time. In this paper, we present a novel defense called pSweeper to robustly protect against UaF exploits with low overhead, and pinpoint the root-causes of UaF vulnerabilities with one safe crash. The success of pSweeper lies in its two unique and innovative design ideas, concurrent pointer sweeping (CPW) and object origin tracking (OOT). CPW exploits the increasingly available multi-cores on modern PCs and outsources the heavyweight security checks and enforcement to dedicated threads that can run on spare cores. Specifically, CPW iteratively sweeps all live pointers in a concurrent thread to find dangling pointers. This design is quite different from previous work that requires to track every pointer propagation to maintain accurate point-to relationship between pointers and objects. OOT can help to pinpoint the root-causes of UaF by informing developers of how a dangling pointer is created, i.e., how the problematic object is allocated and freed. We implement a prototype of pSweeper and validate its efficacy in real scenarios. Our experimental results show that pSweeper is effective in defeating real-world UaF exploits and efficient when deployed in production runs.

This paper proposes a game-theoretic approach to analyze the interactions between an attacker and a defender in a cyber-physical system (CPS) and develops effective defense strategies. In a CPS, the attacker launches cyber attacks on a number of nodes in the cyber layer, trying to maximize the potential damage to the underlying physical system while the system operator seeks to defend several nodes in the cyber layer to minimize the physical damage. Given that CPS attacking and defending is often a continual process, a zero-sum Markov game is proposed in this paper to model these interactions subject to underlying uncertainties of real-world events and actions. A novel model is also proposed in this paper to characterize the interdependence between the cyber layer and the physical layer in a CPS and quantify the impact of the cyber attack on the physical damage in the proposed game. To find the Nash equilibrium of the Markov game, we design an efficient algorithm based on value iteration. The proposed general approach is then applied to study the wide-area monitoring and protection issue in smart grid. Extensive simulations are conducted based on real-world data, and results show the effectiveness of the defending strategies derived from the proposed approach.

The growing number of devices we interact with require a convenient yet secure solution for user identification, authorization and authentication. Current approaches are cumbersome, susceptible to eavesdropping and relay attacks, or energy inefficient. In this paper, we propose a body-guided communication mechanism to secure every touch when users interact with a variety of devices and objects. The method is implemented in a hardware token worn on user's body, for example in the form of a wristband, which interacts with a receiver embedded inside the touched device through a body-guided channel established when the user touches the device. Experiments show low-power (uJ/bit) operation while achieving superior resilience to attacks, with the received signal at the intended receiver through the body channel being at least 20dB higher than that of an adversary in cm range.