Biblio

Advancements in the AI field unfold tremendous opportunities for society. Simultaneously, it becomes increasingly important to address emerging ramifications. Thereby, the focus is often set on ethical and safe design forestalling unintentional failures. However, cybersecurity-oriented approaches to AI safety additionally consider instantiations of intentional malice – including unethical malevolent AI design. Recently, an analogous emphasis on malicious actors has been expressed regarding security and safety for virtual reality (VR). In this vein, while the intersection of AI and VR (AIVR) offers a wide array of beneficial cross-fertilization possibilities, it is responsible to anticipate future malicious AIVR design from the onset on given the potential socio-psycho-technological impacts. For a simplified illustration, this paper analyzes the conceivable use case of Generative AI (here deepfake techniques) utilized for disinformation in immersive journalism. In our view, defenses against such future AIVR safety risks related to falsehood in immersive settings should be transdisciplinarily conceived from an immersive co-creation stance. As a first step, we motivate a cybersecurity-oriented procedure to generate defenses via immersive design fictions. Overall, there may be no panacea but updatable transdisciplinary tools including AIVR itself could be used to incrementally defend against malicious actors in AIVR.

Cyber-physical systems (CPSs) are implemented in many industrial and embedded control applications. Where these systems are safety-critical, correct and safe behavior is of paramount importance. Malicious attacks on such CPSs can have far-reaching repercussions. For instance, if elements of a power grid behave erratically, physical damage and loss of life could occur. Currently, there is a trend toward increased complexity and connectivity of CPS. However, as this occurs, the potential attack vectors for these systems grow in number, increasing the risk that a given controller might become compromised. In this article, we examine how the dangers of compromised controllers can be mitigated. We propose a novel application of runtime enforcement that can secure the safety of real-world physical systems. Here, we synthesize enforcers to a new hardware architecture within programmable logic controller I/O modules to act as an effective line of defence between the cyber and the physical domains. Our enforcers prevent the physical damage that a compromised control system might be able to perform. To demonstrate the efficacy of our approach, we present several benchmarks, and show that the overhead for each system is extremely minimal.

In response to the increasing awareness of the Ethernet-based threat surface of industrial control systems (ICS), both the research and commercial communities are responding with ICS-specific security solutions. Unfortunately, many of the properties of ICS environments that contribute to the extent of this threat surface (e.g. age of devices, inability or unwillingness to patch, criticality of the system) similarly prevent the proper testing and evaluation of these security solutions. Production environments are often too fragile to introduce unvetted technology and most organizations lack test environments that are sufficiently consistent with production to yield actionable results. Cost and space requirements prevent the creation of mirrored physical environments leading many to look towards simulation or virtualization. Examples in literature provide various approaches to building ICS test beds, though most of these suffer from a lack of realism due to contrived scenarios, synthetic data and other compromises. In this paper, we provide a design methodology for building highly realistic ICS test beds for validating cybersecurity defenses. We then apply that methodology to the design and building of a specific test bed and describe the results and experimental use cases.

Following the same trend of consumer electronics, safety-critical industries are starting to adopt Over-The-Air Software Updates (OTASU) on their embedded systems. The motivation behind this trend is twofold. On the one hand, OTASU offer several benefits to the product makers and users by improving or adding new functionality and services to the product without a complete redesign. On the other hand, the increasing connectivity trend makes OTASU a crucial cyber-security demand to download latest security patches. However, the application of OTASU in the safety-critical domain is not free of challenges, specially when considering the dramatic increase of software complexity and the resulting high computing performance demands. This is the mission of UP2DATE, a recently launched project funded within the European H2020 programme focused on new software update architectures for heterogeneous high-performance mixed-criticality systems. This paper gives an overview of UP2DATE and its foundations, which seeks to improve existing OTASU solutions by considering safety, security and availability from the ground up in an architecture that builds around composability and modularity.

Heterogeneous system-on-chip platforms with multiple processing cores are becoming increasingly common in safety-and security-critical embedded systems. To facilitate a logical isolation of physically connected on-chip components, internal communication links of such platforms are often equipped with dedicated access protection units. When performed manually, however, the configuration of these units can be both time-consuming and error-prone. To resolve this issue, we present a formal model and a corresponding design methodology that allows developers to specify access permissions and information flow requirements for embedded systems in a mostly platform-independent manner. As part of the methodology, the consistency between the permissions and the requirements is automatically verified and an extensible generation framework is used to transform the abstract permission declarations into configuration code for individual access protection units. We present a prototypical implementation of this approach and validate it by generating configuration code for the access protection unit of a commercially available multiprocessor system-on-chip.

In order to solve the defense problem of wireless network security threats in new energy stations, a new wireless network security risk assessment model which proposes a wireless access security evaluation method for power monitoring system based on fuzzy theory, was established based on the study of security risk assessment methods in this paper. The security evaluation method first divides the security evaluation factor set, then determines the security evaluation weight coefficient, then calculates the network security level membership matrix, and finally combines specific examples to analyze the resulting data. this paper provided new ideas and methods for the wireless access security evaluation of new energy stations.

This research provides security and safety extensions to a blockchain based solution whose target is e-health. The Advanced Blockchain platform is extended with intelligent monitoring for security and machine learning for detecting patient treatment medication safety issues. For the reasons of stringent HIPAA, HITECH, EU-GDPR and other regional regulations dictating security, safety and privacy requirements, the e-Health blockchains have to cover mandatory disclosure of violations or enforcements of policies during transaction flows involving healthcare. Our service solution further provides the benefits of resolving the abnormal flows of a medical treatment process, providing accountability of the service providers, enabling a trust health information environment for institutions to handle medication safely, giving patients a better safety guarantee, and enabling the authorities to supervise the security and safety of e-Health blockchains. The capabilities can be generalized to support a uniform smart solution across industry in a variety of blockchain applications.

Attack detection and recovery are fundamental elements for the operation of safe and resilient cyber-physical systems. Most of the literature focuses on attack-detection, while leaving attack-recovery as an open problem. In this paper, we propose novel attack-recovery control for securing cyber-physical systems. Our recovery control consists of new concepts required for a safe response to attacks, which includes the removal of poisoned data, the estimation of the current state, a prediction of the reachable states, and the online design of a new controller to recover the system. The synthesis of such recovery controllers for cyber-physical systems has barely investigated so far. To fill this void, we present a formal method-based approach to online compute a recovery control sequence that steers a system under an ongoing sensor attack from the current state to a target state such that no unsafe state is reachable on the way. The method solves a reach-avoid problem on a Linear Time-Invariant (LTI) model with the consideration of an error bound $ε$ $\geq$ 0. The obtained recovery control is guaranteed to work on the original system if the behavioral difference between the LTI model and the system's plant dynamics is not larger than $ε$. Since a recovery control should be obtained and applied at the runtime of the system, in order to keep its computational time cost as low as possible, our approach firstly builds a linear programming restriction with the accordingly constrained safety and target specifications for the given reach-avoid problem, and then uses a linear programming solver to find a solution. To demonstrate the effectiveness of our method, we provide (a) the comparison to the previous work over 5 system models under 3 sensor attack scenarios: modification, delay, and reply; (b) a scalability analysis based on a scalable model to evaluate the performance of our method on large-scale systems.

The proliferation of artificial intelligence based systems in all walks of life raises concerns about their safety and robustness, especially for cyber-physical systems including multiple machine learning components. In this paper, we introduce robustness contracts as a framework for compositional specification and reasoning about the robustness of cyber-physical systems based on neural network (NN) components. Robustness contracts can encompass and generalize a variety of notions of robustness which were previously proposed in the literature. They can seamlessly apply to NN-based perception as well as deep reinforcement learning (RL)-enabled control applications. We present a sound and complete algorithm that can efficiently verify the satisfaction of a class of robustness contracts on NNs by leveraging notions from Lagrangian duality to identify system configurations that violate the contracts. We illustrate the effectiveness of our approach on the verification of NN-based perception systems and deep RL-based control systems.

Security has become the vital component of today's technology. People wish to safeguard their valuable items in bank lockers. With growing technology most of the banks have replaced the manual lockers by digital lockers. Even though there are numerous biometric approaches, these are not robust. In this work we propose a new approach for personal biometric identification based on features extracted from ECG.

Safety and security of complex critical infrastructures is very important for economic, environmental and social reasons. The interdisciplinary and inter-system dependencies within these infrastructures introduce difficulties in the safety and security design. Late discovery of safety and security design weaknesses can lead to increased costs, additional system complexity, ineffective mitigation measures and delays to the deployment of the systems. Traditionally, safety and security assessments are handled using different methods and tools, although some concepts are very similar, by specialized experts in different disciplines and are performed at different system design life-cycle phases.The methodology proposed in this paper supports a concurrent safety and security Defense in Depth (DiD) assessment at an early design phase and it is designed to handle safety and security at a high level and not focus on specific practical technologies. It is assumed that regardless of the perceived level of security defenses in place, a determined (motivated, capable and/or well-funded) attacker can find a way to penetrate a layer of defense. While traditional security research focuses on removing vulnerabilities and increasing the difficulty to exploit weaknesses, our higher-level approach focuses on how the attacker's reach can be limited and to increase the system's capability for detection, identification, mitigation and tracking. The proposed method can assess basic safety and security DiD design principles like Redundancy, Physical separation, Functional isolation, Facility functions, Diversity, Defense lines/Facility and Computer Security zones, Safety classes/Security Levels, Safety divisions and physical gates/conduits (as defined by the International Atomic Energy Agency (IAEA) and international standards) concurrently and provide early feedback to the system engineer. A prototype tool is developed that can parse the exported project file of the interdisciplinary model. Based on a set of safety and security attributes, the tool is able to assess aspects of the safety and security DiD capabilities of the design. Its results can be used to identify errors, improve the design and cut costs before a formal human expert inspection. The tool is demonstrated on a case study of an early conceptual design of a complex system of a nuclear power plant.

VANET plays a vital role to optimize the journey between source and destination in the growth of smart cities worldwide. The crucial information shared between vehicles is concerned primarily with safety. VANET is a MANET sub-class network that provides a free movement and communication between the RSU and vehicles. The self organized with high mobility in VANET makes any vehicle can transmit malicious messages to some other vehicle in the network. In the defense horizon of VANETs this is a matter of concern. It is the duty of RSU to ensure the safe transmission of sensitive information across the Network to each node. For this, network access exists as the key safety prerequisite, and several risks or attacks can be experienced. The VANETs is vulnerable to a range of security attacks including masquerading, selfish node attack, Sybil attack etc. One of the main threats to network access is this Denial of Service attack. The most important research in the literature on the prevention of Denial of Service Attack in VANETs was explored in this paper. The limitations of each reviewed paper are also presented and Game theory based security model is defined in this paper.

New technologies, such as augmented reality (AR) are used to enhance human capabilities and extend human functioning; nevertheless they may cause distraction and incorrect human functioning. Systems including socio entities (such as human) and technical entities (such as augmented reality) are called socio-technical systems. In order to do risk assessment in such systems, considering new dependability threats caused by augmented reality is essential, for example failure of an extended human function is a new type of dependability threat introduced to the system because of new technologies. In particular, it is required to identify these new dependability threats and extend modeling and analyzing techniques to be able to uncover their potential impacts. This research aims at providing a framework for risk assessment in AR-equipped socio-technical systems by identifying AR-extended human failures and AR-caused faults leading to human failures. Our work also extends modeling elements in an existing metamodel for modeling socio-technical systems, to enable AR-relevant dependability threats modeling. This extended metamodel is expected to be used for extending analysis techniques to analyze AR-equipped socio-technical systems.

Vehicular Adhoc Networks (VANETs) ensures road safety by communicating with a set of smart vehicles. VANET is a subset of Mobile Adhoc Networks (MANETs). VANET enabled vehicles helps in establishing communication services among one another or with the Road Side Unit (RSU). Information transmitted in VANET is distributed in an open access environment and hence security is one of the most critical issues related to VANET. Although each vehicle is not a source of all communications, most contact depends on the information that other vehicles receive from it. That vehicle must be able to assess, determine and respond locally on the information obtained from other vehicles to protect VANET from malicious act. Of this reason, message verification in VANET is more difficult due to the protection and privacy issues of the participating vehicles. To overcome security threats, we propose Monitoring Algorithm that detects malicious nodes based on the pre-selected threshold value. The threshold value is compared with the distrust value which is inherently tagged with each vehicle. The proposed Monitoring Algorithm not only detects malicious vehicles, but also isolates the malicious vehicles from the network. The proposed technique is simulated using Network Simulator2 (NS2) tool. The simulation result illustrated that the proposed Monitoring Algorithm outperforms the existing algorithms in terms of malicious node detection, network delay, packet delivery ratio and throughput, thereby uplifting the overall performance of the network.

Remote patient monitoring is a system that focuses on patients care and attention with the advent of the Internet of Things (IoT). The technology makes it easier to track distance, but also to diagnose and provide critical attention and service on demand so that billions of people are safer and more safe. Skincare monitoring is one of the growing fields of medical care which requires IoT monitoring, because there is an increasing number of patients, but cures are restricted to the number of available dermatologists. The IoT-based skin monitoring system produces and store volumes of private medical data at the cloud from which the skin experts can access it at remote locations. Such large-scale data are highly vulnerable and otherwise have catastrophic results for privacy and security mechanisms. Medical organizations currently do not concentrate much on maintaining safety and privacy, which are of major importance in the field. This paper provides an IoT based skin surveillance system based on a blockchain data protection and safety mechanism. A secure data transmission mechanism for IoT devices used in a distributed architecture is proposed. Privacy is assured through a unique key to identify each user when he registers. The principle of blockchain also addresses security issues through the generation of hash functions on every transaction variable. We use blockchain consortiums that meet our criteria in a decentralized environment for controlled access. The solutions proposed allow IoT based skin surveillance systems to privately and securely store and share medical data over the network without disturbance.

The next generation of dependable embedded systems feature autonomy and higher levels of interconnection. Autonomy is commonly achieved with the support of artificial intelligence algorithms that pose high computing demands on the hardware platform, reaching a high performance scale. This involves a dramatic increase in software and hardware complexity, fact that together with the novelty of the technology, raises serious concerns regarding system dependability. Traditional approaches for certification require to demonstrate that the system will be acceptably safe to operate before it is deployed into service. The nature of autonomous systems, with potentially infinite scenarios, configurations and unanticipated interactions, makes it increasingly difficult to support such claim at design time. In this context, the extended networking technologies can be exploited to collect post-deployment evidence that serve to oversee whether safety assumptions are preserved during operation and to continuously improve the system through regular software updates. These software updates are not only convenient for critical bug fixing but also necessary for keeping the interconnected system resilient against security threats. However, such approach requires a recondition of the traditional certification practices.

Improved safety, high mobility and environmental concerns in transportation systems across the world and the corresponding developments in information and communication technologies continue to drive attention towards Intelligent Transportation Systems (ITS). This is evident in advanced driver-assistance systems such as lane departure warning, adaptive cruise control and collision avoidance. However, in connected and autonomous vehicles, the efficient functionality of these applications depends largely on the ability of a vehicle to accurately predict it operating parameters such as location and speed. The ability to predict the immediate future/next location (or speed) of a vehicle or its ability to predict neighbors help in guaranteeing integrity, availability and accountability, thus boosting safety and resiliency of the Vehicular Network for Mobile Cyber Physical Systems (VCPS). In this paper, we proposed a secure movement-prediction for connected vehicles by using Kalman filter. Specifically, Kalman filter predicts the locations and speeds of individual vehicles with reference to already observed and known information such posted legal speed limit, geographic/road location, direction etc. The aim is to achieve resilience through the predicted and exchanged information between connected moving vehicles in an adaptive manner. By being able to predict their future locations, the following vehicle is able to adjust its position more accurately to avoid collision and to ensure optimal information exchange among vehicles.

The autonomy of intelligent systems and their safety rely on their ability for local decision making based on collected environmental information. This is even more for cyber-physical systems running safety critical activities. While this intelligence is partial and fragmented, and cognitive techniques are of limited maturity, the decision function must produce results whose validity and scope must be weighted in light of the underlying assumptions, unavoidable uncertainty and hypothetical safety limitation. Besides the cognitive techniques dependability, it is about the assurance level of the decision self-making. Beyond the pure decision-making capabilities of the autonomous intelligent system, we need techniques that guarantee the system assurance required for the intended use. Security mechanisms for cognitive systems may be consequently tightly intricated. We propose a trustworthiness module which is part of the system and its resulting safety. In this paper, we briefly review the state of the art regarding the dependability of cognitive techniques, the assurance level definition in this context, and related engineering practices. We elaborate regarding the design of autonomous intelligent systems safety, then we discuss its security design and approaches for the mitigation of safety violations by the cognitive functions.

Blockchain is developing rapidly in various domains for its security. Nowadays, one of the most crucial fundamental concerns is internet security. Blockchain is a novel solution to enhance the security of network applications. However, there are no precise frameworks to secure the Internet of Vehicle (IoV) using Blockchain technology. In this paper, a blockchain-based smart internet of vehicle (BSIoV) framework has been proposed due to the cooperative, collaborative, transparent, and secure characteristics of Blockchain. The main contribution of the proposed work is to connect vehicle-related authorities together to fix a secure and transparent vehicle-to-everything (V2X) communication through the peer-to-peer network connection and provide secure services to the intelligent transport systems. A key management strategy has been included to identify a vehicle in this proposed system. The proposed framework can also provide a significant solution for the data security and safety of the connected vehicles in blockchain network.

Digital signal processor (DSP) intellectual property (IP) cores are the underlying hardware responsible for high performance data intensive applications. However an unauthorized IP vendor may counterfeit the DSP IPs and infuse them into the design-chain. Thus fake IPs or integrated circuits (ICs) are unknowingly integrated into consumer electronics (CE) systems, leading to reliability and safety issues for users. The latent solution to this threat is hardware steganography wherein vendor's secret information is covertly inserted into the design to enable detection of counterfeiting. A key-regulated hash-modules chaining based IP steganography is presented in our paper to secure against counterfeiting threat. The proposed approach yielded a robust steganography achieving very high security with regard to stego-key length than previous approaches.

Shared register emulations on top of message-passing systems provide an illusion of a simpler shared memory system which can make the task of a system designer easier. Numerous shared register applications have a considerably high read-to-write ratio. Thus, having algorithms that make reads more efficient than writes is a fair trade-off.Typically, such algorithms for reads and writes are asymmetric and sacrifice the stringent consistency condition atomicity, as it is impossible to have fast reads for multi-writer atomicity. Safety is a consistency condition that has has gathered interest from both the systems and theory community as it is weaker than atomicity yet provides strong enough guarantees like "strong consistency" or read-my-write consistency. One requirement that is assumed by many researchers is that of the reliable broadcast (RB) primitive, which ensures the "all or none" property during a broadcast. One drawback is that such a primitive takes 1.5 rounds to complete and requires server-to-server communication.This paper implements an efficient multi-writer multi-reader safe register without using a reliable broadcast primitive. Moreover, we provide fast reads or one-shot reads – our read operations can be completed in one round of client-to-server communication. Of course, this comes with the price of requiring more servers when compared to prior solutions assuming reliable broadcast. However, we show that this increased number of servers is indeed necessary as we prove a tight bound on the number of servers required to implement Byzantine-fault tolerant safe registers in a system without reliable broadcast.We extend our results to data stored using erasure coding as well. We present an emulation of single-writer multi-reader safe register based on MDS codes. The usage of MDS codes reduces storage and communication costs. On the negative side, we also show that to use MDS codes and at the same time achieve one-shot reads, we need even more servers.

In article the basic criteria of quality of work of the automated control system of technological process (APCS) are considered, the analysis of critical moments and level of information safety of APCS is spent. The model of maintenance of information safety of APCS on the basis of technology of predictive maintenance with application of intellectual methods of data processing is offered. The model allows to generate the list of actions at detection of new kinds of the threats connected with destructive influences on object, proceeding from acceptability of predicted consequences of work of APCS. In article with use of the system analysis the complex model of the technical object of automation is developed, allowing to estimate consequences from realization of threats of information safety at various system levels of APCS.

Digitalization of production and management as the imperatives of Industry 4.0 stipulated the requirements of state regulators for informing and training personnel of a significant object of critical information infrastructure. However, the attention of industrial enterprises to this problem is assessed as insufficient. This determines the relevance and purpose of this article - to develop a methodology and tool for raising the awareness of workers of an industrial enterprise about information security (IS) of significant objects of critical information infrastructure. The article reveals the features of training at industrial enterprises associated with a high level of development of safety and labor protection systems. Traditional and innovative methods and means of training personnel at the workplace within the framework of these systems and their opportunities for training in the field of information security are shown. The specificity of the content and forms of training employees on the security of critical information infrastructure has been substantiated. The scientific novelty of the study consists in the development of methods and software applications that can perform the functions of identifying personal qualities of employees; testing the input level of their knowledge in the field of IS; testing for knowledge of IS rules (by the example of a response to socio-engineering attacks); planning an individual thematic plan for employee training; automatic creation of a modular program and its content; automatic notification of the employee about the training schedule at the workplace; organization of training according to the schedule; control self-testing and testing the level of knowledge of the employee after training; organizing a survey to determine satisfaction with employee training. The practical significance of the work lies in the possibility of implementing the developed software application in industrial enterprises, which is confirmed by the successful results of its testing.

In this study, our aim is to extend the scope for public key cryptography. We offered a new efficient public key encryption scheme using partial discrete logarithm problem (PDLP). It is known as the Quadratic Exponentiation Randomized Public Key Cryptosystem (QERPKC). Security of the presented scheme is based on the hardness of PDLP. We reflect the safety in contrast to trick of certain elements in the offered structure and demonstrated the prospect of creating an extra safety structure. The presented new efficient QERPKC structure is appropriate for low-bandwidth communication, low-storage and low-computation environments.

To achieve a substantial reliability and safety level, it is imperative to provide electronic computing systems with appropriate mechanisms to tackle soft errors. This paper proposes a low-cost system-level soft error mitigation technique, which allocates the critical application function to a pool of specific general-purpose processor registers. Both the critical function and the register pool are automatically selected by a developed profiling tool. The proposed technique was validated through more than 320K fault injections considering a Linux kernel, different benchmarks and two multicore ARM processors. Results show that our technique significantly reduces the code size and performance overheads while providing reliability improvement, w.r.t. the Triple Modular Redundancy (TMR) technique.