Biblio

Engineering a successful conversational AI agent is a tough process, and requires the consideration of achieving an effective communication between its various endpoints. In this paper, we present our perspective for designing an efficient conversational agent according to our belief that the existence of a centralized learning module that is capable of analyzing and understanding humans' behaviour from day one, and acting upon this behaviour is a must.

The advances in natural language processing and the wide use of social networks have boosted the proliferation of chatbots. These are software services typically embedded within a social network, and which can be addressed using conversation through natural language. Many chatbots exist with different purposes, e.g., to book all kind of services, to automate software engineering tasks, or for customer support. In previous work, we proposed the use of chatbots for domain-specific modelling within social networks. In this short paper, we report on the needs for flexible modelling required by modelling using conversation. In particular, we propose a process of meta-model relaxation to make modelling more flexible, followed by correction steps to make the model conforming to its meta-model. The paper shows how this process is integrated within our conversational modelling framework, and illustrates the approach with an example.

The rate at which a secure key can be generated in a quantum key distribution (QKD) protocol is limited by the channel loss and the quantum bit-error rate (QBER). Increases to the QBER can stem from detector noise, channel noise, or the presence of an eavesdropper, Eve. Eve is capable of obtaining information of the unsecure key by performing an attack on the quantum channel or by listening to all discussion performed via a noiseless public channel. Conventionally a QKD protocol will perform the information reconciliation over the authenticated public channel, revealing the parity bits used to correct for any quantum bit errors. In this invited paper, the possibility of limiting the information revealed to Eve during the information reconciliation is considered. Using a covert communication channel for the transmission of the parity bits, secure key rates are possible at much higher QBERs. This is demonstrated through the simulation of a polarization based QKD system implementing the BB84 protocol, showing significant improvement of the SKRs over the conventional QKD protocols.

We propose a coding scheme for covert communication over additive white Gaussian noise channels, which extends a previous construction for discrete memoryless channels. We first show how sparse signaling with On-Off keying fails to achieve the covert capacity but that a modification allowing the use of binary phase-shift keying for "on" symbols recovers the loss. We then construct a modified pulse-position modulation scheme that, combined with multilevel coding, can achieve the covert capacity with low-complexity error-control codes. The main contribution of this work is to reconcile the tension between diffuse and sparse signaling suggested by earlier information-theoretic results.

To be able to meet demanding application performance requirements within a tight power budget, runtime power management must track hardware activity at a very fine granularity in both space and time. This gives rise to sophisticated power management algorithms, which need the underlying system to be both highly observable (to be able to sense changes in instantaneous power demand timely) and controllable (to be able to react to changes in instantaneous power demand timely). The end goal is allocating the power budget, which itself represents a very critical shared resource, in a fair way among active tasks of execution. Fundamentally, if not carefully managed, any system-wide shared resource can give rise to covert communication. Power budget does not represent an exception, particularly as systems are becoming more and more observable and controllable. In this paper, we demonstrate how power management vulnerabilities can enable covert communication over a previously unexplored, novel class of covert channels which we will refer to as POWERT channels. We also provide a comprehensive characterization of the POWERT channel capacity under various sharing and activity scenarios. Our analysis based on experiments on representative commercial systems reveal a peak channel capacity of 121.6 bits per second (bps).

Security issues severely restrict the development and popularization of cloud computing. As a way of data leakage, covert channel greatly threatens the security of cloud platform. This paper introduces the types and research status of covert channels, and discusses the classical detection and interference methods of time-covert channels on cloud platforms for shared memory time covert channels.

In this paper, we outline a novel, forward error correction-based information hiding technique for adaptive rate wireless communication systems. Specifically, we propose leveraging the functionality of wireless local area network modulation and coding schemes (MCS) and link adaptation mechanisms to significantly increase covert channel throughput. After describing our generalized information hiding model, we detail implementation of this technique within the IEEE 802.11ad, directional multi-Gigabit standard. Simulation results demonstrate the potential of the proposed techniques to develop reliable, high-throughput covert channels under multiple MCS rates and embedding techniques. Covert channel performance is evaluated in terms of the observed packet error ratio of the underlying communication system as well as the bit error ratio of the hidden data.

Network covert channels are used in various cyberattacks, including disclosure of sensitive information and enabling stealth tunnels for botnet commands. With time and technology, covert channels are becoming more prevalent, complex, and difficult to detect. The current methods for detection are protocol and pattern specific. This requires the investment of significant time and resources into application of various techniques to catch the different types of covert channels. This paper reviews several patterns of network storage covert channels, describes generation of network traffic dataset with covert channels, and proposes a generic, protocol-independent approach for the detection of network storage covert channels using a supervised machine learning technique. The implementation of the proposed generic detection model can lead to a reduction of necessary techniques to prevent covert channel communication in network traffic. The datasets we have generated for experimentation represent storage covert channels in the IP, TCP, and DNS protocols and are available upon request for future research in this area.

Covert communications, where a transmitter Alice wishes to hide the presence of her transmitted signal from a watchful adversary Willie, has been considered extensively in recent years. Those investigations have generally considered physical-layer models, where the adversary has access to a sophisticated (often optimal) receiver to determine whether a transmission has taken place, and have addressed the question of what rate can information be communicated covertly. More recent investigations have begun to consider the change in covert rate when Willie has uncertainty about the physical layer environment. Here, we move up the protocol stack to consider the covert rate when Willie is watching the medium-access control (MAC) layer in a network employing a random access MAC such as slotted ALOHA. Based on the rate of collisions and potentially the number of users involved in those collisions, Willie attempts to determine whether unauthorized (covert) users are accessing the channel. In particular, we assume different levels of sophistication in Willie's receiver, ranging from a receiver that only can detect whether there was a collision or not, to one that can always tell exactly how many packets were on the channel in the random access system. In each case, we derive closed-form expressions for the achievable covert rates in the system. The achievable rates exhibit significantly different behavior than that observed in the study of covert systems at the physical layer.

In this study, delays between data packets were read by using different window sizes to detect data transmitted from covert timing channel in computer networks, and feature vectors were extracted from them and detection of hidden data by some classification algorithms was achieved with high performance rate.

As the Internet of Things (IoT) continues to expand into every facet of our daily lives, security researchers have warned of its myriad security risks. While denial-of-service attacks and privacy violations have been at the forefront of research, covert channel communications remain an important concern. Utilizing a Bluetooth controlled light bulb, we demonstrate three separate covert channels, consisting of current utilization, luminosity and hue. To study the effectiveness of these channels, we implement exfiltration attacks using standard off-the-shelf smart bulbs and RGB LEDs at ranges of up to 160 feet. We analyze the identified channels for throughput, generality and stealthiness, and report transmission speeds of up to 832 bps.

Securing Cyber-Physical Systems (CPS) against cyber-attacks is challenging due to the wide range of possible attacks - from stealthy ones that seek to manipulate/drop/delay control and measurement signals to malware that infects host machines that control the physical process. This has prompted the research community to address this problem through developing targeted methods that protect and check the run-time operation of the CPS. Since protecting signals and checking for errors result in performance penalties, they must be performed within the delay bounds dictated by the control loop. Due to the large number of potential checks that can be performed, coupled with various degrees of their effectiveness to detect a wide range of attacks, strategic assignment of these checks in the control loop is a critical endeavor. To that end, this paper presents a coherent runtime framework - which we coin BLOC - for orchestrating the CPS with check blocks to secure them against cyber attacks. BLOC capitalizes on game theoretical techniques to enable the defender to find an optimal randomized use of check blocks to secure the CPS while respecting the control-loop constraints. We develop a Stackelberg game model for stateless blocks and a Markov game model for stateful ones and derive optimal policies that minimize the worst-case damage from rational adversaries. We validate our models through extensive simulations as well as a real implementation for a HVAC system.

Smart buildings are controlled by multiple cyber-physical systems that provide critical services such as heating, ventilation, lighting and access control. These building systems are becoming increasingly vulnerable to both cyber and physical attacks. We introduce a multi-model methodology for assessing the security of these systems, which utilises INTO-CPS, a suite of modelling, simulation, and analysis tools for designing cyber-physical systems. Using a fan coil unit case study we show how its security can be systematically assessed when subjected to Man-in-the-Middle attacks on the data connections between system components. We suggest our methodology would enable building managers and security engineers to design attack countermeasures and refine their effectiveness.

With rapid advances in the fields of the Internet of Things and autonomous systems, the network security of cyber-physical systems(CPS) becomes more and more important. This paper focuses on the real-time security evaluation for unmanned aircraft systems which are cyber-physical systems relying on information communication and control system to achieve autonomous decision making. Our problem formulation is motivated by scenarios involving autonomous unmanned aerial vehicles(UAVs) working continuously under data-driven attacks when in an open, uncertain, and even hostile environment. Firstly, we investigated the state estimation method in CPS integrated with data-driven attacks model, and then proposed a real-time security scoring algorithm to evaluate the security condition of unmanned aircraft systems under different threat patterns, considering the vulnerability of the systems and consequences brought by data attacks. Our simulation in a UAV illustrated the efficiency and reliability of the algorithm.

The massive integration of Renewable Energy Sources (RES) into power systems is a major challenge but it also provides new opportunities for network operation. For example, with a large amount of RES available at HV subtransmission level, it is possible to exploit them as controlling resources in islanding conditions. Thus, a procedure for off-line evaluation of islanded operation feasibility in the presence of RES is proposed. The method finds which generators and loads remain connected after islanding to balance the island's real power maximizing the amount of supplied load and assuring the network's long-term security. For each possible islanding event, the set of optimal control actions (load/generation shedding) to apply in case of actual islanding, is found. The procedure is formulated as a Mixed Integer Non-Linear Problem (MINLP) and is solved using Genetic Algorithms (GAs). Results, including dynamic simulations, are shown for a representative HV subtransmission grid.

The dependability of Cyber Physical Systems (CPS) solely lies in the secure and reliable functionality of their backbone, the computing platform. Security of this platform is not only threatened by the vulnerabilities in the software peripherals, but also by the vulnerabilities in the hardware internals. Such threats can arise from malicious modifications to the integrated circuits (IC) based computing hardware, which can disable the system, leak information or produce malfunctions. Such modifications to computing hardware are made possible by the globalization of the IC industry, where a computing chip can be manufactured anywhere in the world. In the complex computing environment of CPS such modifications can be stealthier and undetectable. Under such circumstances, design of these malicious modifications, and eventually their detection, will be tied to the functionality and operation of the CPS. So it is imperative to address such threats by incorporating security awareness in the computing hardware design in a comprehensive manner taking the entire system into consideration. In this paper, we present a study in the influence of hardware Trojans on closed-loop systems, which form the basis of CPS, and establish threat models. Using these models, we perform a case study on a critical CPS application, gas pipeline based SCADA system. Through this process, we establish a completely virtual simulation platform along with a hardware-in-the-loop based simulation platform for implementation and testing.

With the tighter integration of power system and Information and Communication Technology (ICT), power grid is becoming a typical cyber physical system (CPS). It is important to analyze the impact of the cyber event on power system, so that it is necessary to build a co-simulation system for studying the interaction between power system and ICT. In this paper, a cyber physical power system (CPPS) co-simulation platform is proposed, which includes the hardware-in-the-loop (HIL) simulation function. By using flexible interface, various simulation software for power system and ICT can be interconnected into the platform to build co-simulation tools for various simulation purposes. To demonstrate it as a proof, one simulation framework for real life cyber-attack on power system control is introduced. In this case, the real life denial-of-service attack on a router in automatic voltage control (AVC) is simulated to demonstrate impact of cyber-attack on power system.

The CPS standard can be more objective to evaluate the effect of control behavior in each control area on the interconnected power grid. The CPS standard is derived from statistical methods emphasizing the long-term control performance of AGC, which is beneficial to the frequency control of the power grid by mutual support between the various power grids in the case of an accident. Moreover, CPS standard reduces the wear of the equipment caused by the frequent adjustment of the AGC unit. The key is to adjust the AGC control strategy to meet the performance of CPS standard. This paper proposed a dynamic optimal CPS control methodology for interconnected power systems based on model predictive control which can achieve optimal control under the premise of meeting the CPS standard. The effectiveness of the control strategy is verified by simulation examples.

Cyber physical system (CPS) is often deployed at safety-critical key infrastructures and fields, fault tolerance policies are extensively applied in CPS systems to improve its credibility; the same physical backup of hardware redundancy (SPB) technology is frequently used for its simple and reliable implementation. To resolve challenges faced with in simulation test of SPB-CPS, this paper dynamically determines the test resources matched with the CPS scale by using the adaptive allocation policies, establishes the hierarchical models and inter-layer message transmission mechanism. Meanwhile, the collaborative simulation time sequence push strategy and the node activity test mechanism based on the sliding window are designed in this paper to improve execution efficiency of the simulation test. In order to validate effectiveness of the method proposed in this paper, we successfully built up a fault-tolerant CPS simulation platform. Experiments showed that it can improve the SPB-CPS simulation test efficiency.

Cyber-physical systems (CPS) research leverages the expertise of researchers from multiple domains to engineer complex systems of interacting physical and computational components. An approach called co-simulation is often used in CPS conceptual design to integrate the specialized tools and simulators from each of these domains into a joint simulation for the evaluation of design decisions. Many co-simulation platforms are being developed to expedite CPS conceptualization and realization, but most use intrusive modeling and communication libraries that require researchers to either abandon their existing models or spend considerable effort to integrate them into the platform. A significant number of these co-simulation platforms use the High Level Architecture (HLA) standard that provides a rich set of services to facilitate distributed simulation. This paper introduces a simple gateway that can be readily implemented without co-simulation expertise to adapt existing models and research infrastructure for use in HLA. An open-source implementation of the gateway has been developed for the National Institute of Standards and Technology (NIST) co-simulation platform called the Universal CPS Environment for Federation (UCEF).

Secure logging is essential for the integrity and accountability of cyber-physical systems (CPS). To prevent modification of log files the integrity of data must be ensured. In this work, we propose a solution for secure event in cyberphysical systems logging based on the blockchain technology, by encapsulating event data in blocks. The proposed solution considers the real-time application constraints that are inherent in CPS monitoring and control functions by optimizing the heterogeneous resources governing blockchain computations. In doing so, the proposed blockchain mechanism manages to deliver events in hard-to-tamper ledger blocks that can be accessed and utilized by the various functions and components of the system. Performance analysis of the proposed solution is conducted through extensive simulation, demonstrating the effectiveness of the proposed approach in delivering blocks of events on time using the minimum computational resources.

Cyber-Physical Systems (CPS) are playing important roles in the critical infrastructure now. A prominent family of CPSs are networked control systems in which the control and feedback signals are carried over computer networks like the Internet. Communication over insecure networks make system vulnerable to cyber attacks. In this article, we design an intrusion detection and compensation framework based on system/plant identification to fight covert attacks. We collect error statistics of the output estimation during the learning phase of system operation and after that, monitor the system behavior to see if it significantly deviates from the expected outputs. A compensating controller is further designed to intervene and replace the classic controller once the attack is detected. The proposed model is tested on a DC motor as the plant and is put against a deception signal amplification attack over the forward link. Simulation results show that the detection algorithm well detects the intrusion and the compensator is also successful in alleviating the attack effects.

In order to be more environmentally friendly, a lot of parts and aspects of life become electrified to reduce the usage of fossil fuels. This can be seen in the increased number of electrical vehicles in everyday life. This of course only makes a positive impact on the environment, if the electricity is produced environmentally friendly and comes from renewable sources. But when the green electrical power is produced, it still needs to be transported to where it's needed, which is not necessarily near the production site. In China, one of the ways to do this transport is to use High Voltage Direct Current (HVDC) technology. This of course means, that the current has to be converted to DC before being transported to the end user. That implies that the converter stations are of great importance for the grid security. Therefore, a precise monitoring of the stations is necessary. Ideally, this could be accomplished with wireless sensor nodes with an autarkic energy supply. A role in this energy supply could be played by a thermoelectrical generator (TEG). But to assess the power generated in the specific environment, a simulation would be highly desirable, to evaluate the power gained from the temperature difference in the converter station. This paper proposes a method to simulate the generated power by combining a model for the generator with a Computational Fluid Dynamics (CFD) model converter.

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.

The intelligent production line is a complex application with a large number of independent equipment network integration. In view of the characteristics of CPS, the existing modeling methods cannot well meet the application requirements of large scale high-performance system. a formal simulation verification framework and verification method are designed for the performance constraints such as the real-time and security of the intelligent production line based on soft bus. A model-based service-oriented integration approach is employed, which adopts a model-centric way to automate the development course of the entire software life cycle. Developing experience indicate that the proposed approach based on the formal modeling and verification framework in this paper can improve the performance of the system, which is also helpful to achieve the balance of the production line and maintain the reasonable use rate of the processing equipment.