Biblio

Technologies such as Industry 4.0 or assisted/autonomous driving are relying on highly customized cyber-physical realtime systems. Those systems are designed to match functional safety regulations and requirements such as EN ISO 13849, EN IEC 62061 or ISO 26262. However, as systems - especially vehicles - are becoming more connected and autonomous, they become more likely to suffer from new attack vectors. New features may meet the corresponding safety requirements but they do not consider adversaries intruding through security holes with the purpose of bringing vehicles into unsafe states. As research goal, we want to bridge the gap between security and safety in cyber-physical real-time systems by investigating real-time-aware intrusion-tolerant architectures for automotive use-cases.

Traditional web security assessments are evaluated using a single data source, and the results of the calculations from different data sources are different. Based on multi-source data, this paper uses Analytic Hierarchy Process to construct an evaluation model, calculates the weight of each level of indicators in the web security evaluation model, analyzes and processes the data, calculates the host security threat assessment values at various levels, and visualizes the evaluation results through ECharts+WebGL technology.

This paper presents CapeVM, a sensor node virtual machine aimed at delivering both high performance and a sandboxed execution environment that ensures malicious code cannot corrupt the VM's internal state or perform actions not allowed by the VM. CapeVM uses Ahead-of-Time compilation and introduces a range of optimisations to eliminate most of the overhead present in previous work on sensor node AOT compilers. A sandboxed execution environment is guaranteed by a set of checks. The structured nature of the VM's instruction set allows the VM to perform most checks at load time, reducing the need for expensive run-time checks compared to native code approaches. While some overhead from using a VM and adding sandbox checks cannot be avoided, CapeVM's optimisations reduce this overhead dramatically. We evaluate CapeVM using a set of IoT applications and show this results in a performance just 2.1x slower than unsandboxed native code. Thus, CapeVM combines the desirable properties ofexisting work on both sandboxed execution and virtual machines for sensor nodes, with significantly improved performance.

This paper presents Checked C, an extension to C designed to support spatial safety, implemented in Clang and LLVM. Checked C's design is distinguished by its focus on backward-compatibility, incremental conversion, developer control, and enabling highly performant code. Like past approaches to a safer C, Checked C employs a form of checked pointer whose accesses can be statically or dynamically verified. Performance evaluation on a set of standard benchmark programs shows overheads to be relatively low. More interestingly, Checked C introduces the notions of a checked region and bounds-safe interfaces.

Formal verification of infinite-state systems, and distributed systems in particular, is a long standing research goal. In the deductive verification approach, the programmer provides inductive invariants and pre/post specifications of procedures, reducing the verification problem to checking validity of logical verification conditions. This check is often performed by automated theorem provers and SMT solvers, substantially increasing productivity in the verification of complex systems. However, the unpredictability of automated provers presents a major hurdle to usability of these tools. This problem is particularly acute in case of provers that handle undecidable logics, for example, first-order logic with quantifiers and theories such as arithmetic. The resulting extreme sensitivity to minor changes has a strong negative impact on the convergence of the overall proof effort.

Over the past decade, the reliance on Unmanned Aerial Systems (UAS) to carry out critical missions has grown drastically. With an increased reliance on UAS as mission assets and the dependency of UAS on cyber resources, cyber security of UAS must be improved by adopting sound security principles and relevant technologies from the computing community. On the other hand, the traditional avionics community, being aware of the importance of cyber security, is looking at new architecture and designs that can accommodate both the traditional safety oriented principles as well as the cyber security principles and techniques. It is with the effective and timely convergence of these domains that a holistic approach and co-design can meet the unique requirements of modern systems and operations. In this paper, authors from both the cyber security and avionics domains describe our joint effort and insights obtained during the course of designing secure and resilient embedded avionics systems.

Software Defined Network (SDN) is getting popularity both from academic and industry. Lot of researches have been made to combine SDN with future Internet paradigms to manage and control networks efficiently. SDN provides better management and control in a network through decoupling of data and control plane. Named Data Networking (NDN) is a future Internet technique with aim to replace IPv4 addressing problems. In NDN, communication between different nodes done on the basis of content names rather than IP addresses. Vehicular Ad-hoc Network (VANET) is a subtype of MANET which is also considered as a hot area for future applications. Different vehicles communicate with each other to form a network known as VANET. Communication between VANET can be done in two ways (i) Vehicle to Vehicle (V2V) (ii) Vehicle to Infrastructure (V2I). Combination of SDN and NDN techniques in future Internet can solve lot of problems which were hard to answer by considering a single technique. Security in VANET is always challenging due to unstable topology of VANET. In this paper, we merge future Internet techniques and propose a new scheme to answer timing attack problem in VANETs named as Timing Attack Prevention (TAP) protocol. Proposed scheme is evaluated through simulations which shows the superiority of proposed protocol regarding detection and mitigation of attacker vehicles as compared to normal timing attack scenario in NDN based VANET.

Software verification has been well applied in safety critical areas and has shown the ability to provide better quality assurance for modern software. However, as lines of code and complexity of software systems increase, the scalability of verification becomes a challenge. In this paper, we present an automatic software verification framework TSV to address the scalability issues: (i) the extended structural abstraction and property-guided program slicing to solve large-scale program verification problem, saving time and memory without losing accuracy; (ii) automatically select different verification methods according to the program and property context to improve the verification efficiency. For evaluation, we compare TSV's different configurations with existing C program verifiers based on open benchmarks. We found that TSV with auto-selection performs better than with bounded model checking only or with extended structural abstraction only. Compared to existing tools such as CMBC and CPAChecker, it acquires 10%-20% improvement of accuracy and 50%-90% improvement of memory consumption.

Automotive systems have always been designed with safety in mind. In this regard, the functional safety standard, ISO 26262, was drafted with the intention of minimizing risk due to random hardware faults or systematic failure in design of electrical and electronic components of an automobile. However, growing complexity of a modern car has added another potential point of failure in the form of cyber or sensor attacks. Recently, researchers have demonstrated that vulnerability in vehicle's software or sensing units could enable them to remotely alter the intended operation of the vehicle. As such, in addition to safety, security should be considered as an important design goal. However, designing security solutions without the consideration of safety objectives could result in potential hazards. Consequently, in this paper we propose the notion of security for safety and show that by integrating safety conditions with our system-level security solution, which comprises of a modified Kalman filter and a Chi-squared detector, we can prevent potential hazards that could occur due to violation of safety objectives during an attack. Furthermore, with the help of a car-following case study, where the follower car is equipped with an adaptive-cruise control unit, we show that our proposed system-level security solution preserves the safety constraints and prevent collision between vehicle while under sensor attack.

Peer-to-peer computing (P2P) refers to the famous technology that provides peers an equal spontaneous collaboration in the network by using appropriate information and communication systems without the need for a central server coordination. Today, the interconnection of several P2P networks has become a genuine solution for increasing system reliability, fault tolerance and resource availability. However, the existence of security threats in such networks, allows us to investigate the safety of users from P2P threats by studying the effects of competition between these interconnected networks. In this paper, we present an e-epidemic model to characterize the worm propagation in an interconnected peer-to-peer network. Here, we address this issue by introducing a model of network competition where an unprotected network is willing to partially weaken its own safety in order to more severely damage a more protected network. The unprotected network can infect all peers in the competitive networks after their non react against the passive worm propagation. Our model also evaluated the effect of an immunization strategies adopted by the protected network to resist against attacking networks. The launch time of immunization strategies in the protected network, the number of peers synapse connected to the both networks, and other effective parameters have also been investigated in this paper.

Immersive augmented reality (AR) technologies are becoming a reality. Prior works have identified security and privacy risks raised by these technologies, primarily considering individual users or AR devices. However, we make two key observations: (1) users will not always use AR in isolation, but also in ecosystems of other users, and (2) since immersive AR devices have only recently become available, the risks of AR have been largely hypothetical to date. To provide a foundation for understanding and addressing the security and privacy challenges of emerging AR technologies, grounded in the experiences of real users, we conduct a qualitative lab study with an immersive AR headset, the Microsoft HoloLens. We conduct our study in pairs - 22 participants across 11 pairs - wherein participants engage in paired and individual (but physically co-located) HoloLens activities. Through semi-structured interviews, we explore participants' security, privacy, and other concerns, raising key findings. For example, we find that despite the HoloLens's limitations, participants were easily immersed, treating virtual objects as real (e.g., stepping around them for fear of tripping). We also uncover numerous security, privacy, and safety concerns unique to AR (e.g., deceptive virtual objects misleading users about the real world), and a need for access control among users to manage shared physical spaces and virtual content embedded in those spaces. Our findings give us the opportunity to identify broader lessons and key challenges to inform the design of emerging single-and multi-user AR technologies.

In Vehicle-to-Vehicle (V2V) communications, malicious actors may spread false information to undermine the safety and efficiency of the vehicular traffic stream. Thus, vehicles must determine how to respond to the contents of messages which maybe false even though they are authenticated in the sense that receivers can verify contents were not tampered with and originated from a verifiable transmitter. Existing solutions to find appropriate actions are inadequate since they separately address trust and decision, require the honest majority (more honest ones than malicious), and do not incorporate driver preferences in the decision-making process. In this work, we propose a novel trust-aware decision-making framework without requiring an honest majority. It securely determines the likelihood of reported road events despite the presence of false data, and consequently provides the optimal decision for the vehicles. The basic idea of our framework is to leverage the implied effect of the road event to verify the consistency between each vehicle's reported data and actual behavior, and determine the data trustworthiness and event belief by integrating the Bayes' rule and Dempster Shafer Theory. The resulting belief serves as inputs to a utility maximization framework focusing on both safety and efficiency. This framework considers the two basic necessities of the Intelligent Transportation System and also incorporates drivers' preferences to decide the optimal action. Simulation results show the robustness of our framework under the multiple-vehicle attack, and different balances between safety and efficiency can be achieved via selecting appropriate human preference factors based on the driver's risk-taking willingness.

The intelligent power grid is composed of a large number of industrial control equipment, and most of the industrial control equipment has security holes, which are vulnerable to malicious attacks and affect the normal operation of the power grid. By analyzing the security vulnerability of the firmware of industrial control equipment, the vulnerability can be detected in advance and the power grid's ability to resist attack can be improved. In this paper, a kind of industrial control device firmware protocol vulnerabilities associated technology, through the technology of information extraction from the mass grid device firmware device attributes and extract the industrial control system, the characteristics of the construction of industrial control system device firmware and published vulnerability information correlation, faster in the industrial control equipment safety inspection found vulnerabilities.

Stealth malware, a representative tool of advanced persistent threat (APT) attacks, in particular poses an increased threat to cyber-physical systems (CPS). Due to the use of stealthy and evasive techniques (e.g., zero-day exploits, obfuscation techniques), stealth malwares usually render conventional heavyweight countermeasures (e.g., exploits patching, specialized ant-malware program) inapplicable. Light-weight countermeasures (e.g., containment techniques), on the other hand, can help retard the spread of stealth malwares, but the ensuing side effects might violate the primary safety requirement of CPS. Hence, defenders need to find a balance between the gain and loss of deploying light-weight countermeasures. To address this challenge, we model the persistent anti-malware process as a shortest-path tree interdiction (SPTI) Stackelberg game, and safety requirements of CPS are introduced as constraints in the defender's decision model. Specifically, we first propose a static game (SSPTI), and then extend it to a multi-stage dynamic game (DSPTI) to meet the need of real-time decision making. Both games are modelled as bi-level integer programs, and proved to be NP-hard. We then develop a Benders decomposition algorithm to achieve the Stackelberg Equilibrium of SSPTI. Finally, we design a model predictive control strategy to solve DSPTI approximately by sequentially solving an approximation of SSPTI. The extensive simulation results demonstrate that the proposed dynamic defense strategy can achieve a balance between fail-secure ability and fail-safe ability while retarding the stealth malware propagation in CPS.

Cyber physical systems are the key innovation driver for many domains such as automotive, avionics, industrial process control, and factory automation. However, their interconnection potentially provides adversaries easy access to sensitive data, code, and configurations. If attackers gain control, material damage or even harm to people must be expected. To counteract data theft, system manipulation and cyber-attacks, security mechanisms must be embedded in the cyber physical system. Adding hardware security in the form of the standardized Trusted Platform Module (TPM) is a promising approach. At the same time, traditional dependability features such as safety, availability, and reliability have to be maintained. To determine the right balance between security and dependability it is essential to understand their interferences. This paper supports developers in identifying the implications of using TPMs on the dependability of their system.We highlight potential consequences of adding TPMs to cyber-physical systems by considering the resulting safety, reliability, and availability. Furthermore, we discuss the potential of enhancing the dependability of TPM services by applying traditional redundancy techniques.

As safety-critical systems become increasingly interconnected, a system's operations depend on the reliability and security of the computing components and the interconnections among them. Therefore, a growing body of research seeks to tie safety analysis to security analysis. Specifically, it is important to analyze system safety under different attacker models. In this paper, we develop generic parameterizable state automaton templates to model the effects of an attack. Then, given an attacker model, we generate a state automaton that represents the system operation under the threat of the attacker model. We use a railway signaling system as our case study and consider threats to the communication protocol and the commands issued to physical devices. Our results show that while less skilled attackers are not able to violate system safety, more dedicated and skilled attackers can affect system safety. We also consider several countermeasures and show how well they can deter attacks.

The exponential growth of information and communication technologies have caused a profound shift in the way humans engineer systems leading to the emergence of closed-loop systems involving strong integration and coordination of physical and cyber components, often referred to as cyber-physical systems (CPSs). Because of these disruptive changes, physical systems can now be attacked through cyberspace and cyberspace can be attacked through physical means. The paper considers security and resilience as system properties emerging from the intersection of system dynamics and the computing architecture. A modeling and simulation integration platform for experimentation and evaluation of resilient CPSs is presented using smart transportation systems as the application domain. Evaluation of resilience is based on attacker-defender games using simulations of sufficient fidelity. The platform integrates 1) realistic models of cyber and physical components and their interactions; 2) cyber attack models that focus on the impact of attacks to CPS behavior and operation; and 3) operational scenarios that can be used for evaluation of cybersecurity risks. Three case studies are presented to demonstrate the advantages of the platform: 1) vulnerability analysis of transportation networks to traffic signal tampering; 2) resilient sensor selection for forecasting traffic flow; and 3) resilient traffic signal control in the presence of denial-of-service attacks.

The exponential growth of information and communication technologies have caused a profound shift in the way humans engineer systems leading to the emergence of closed-loop systems involving strong integration and coordination of physical and cyber components, often referred to as cyber-physical systems (CPSs). Because of these disruptive changes, physical systems can now be attacked through cyberspace and cyberspace can be attacked through physical means. The paper considers security and resilience as system properties emerging from the intersection of system dynamics and the computing architecture. A modeling and simulation integration platform for experimentation and evaluation of resilient CPSs is presented using smart transportation systems as the application domain. Evaluation of resilience is based on attacker-defender games using simulations of sufficient fidelity. The platform integrates 1) realistic models of cyber and physical components and their interactions; 2) cyber attack models that focus on the impact of attacks to CPS behavior and operation; and 3) operational scenarios that can be used for evaluation of cybersecurity risks. Three case studies are presented to demonstrate the advantages of the platform: 1) vulnerability analysis of transportation networks to traffic signal tampering; 2) resilient sensor selection for forecasting traffic flow; and 3) resilient traffic signal control in the presence of denial-of-service attacks.

We develop a contingency planning methodology for how a firm would build a global supply chain network with reserve manufacturing capacity which can be strategically deployed by the firm in the event actual demand exceeds forecast. The contingency planning approach is comprised of: (1) a strategic network design model for finding the profit maximizing plant locations, manufacturing capacity and inventory investments, and production level and product distribution; and (2) a scenario planning and risk assessment scheme to analyze the costs and benefits of alternative levels of manufacturing capacity and inventory investments. We develop an efficient heuristic procedure to solve the model. We show numerically how a firm would use our approach to explore and weigh the potential upside benefits and downside risks of alternative strategies.

Networked control systems improve the efficiency of cyber-physical plants both functionally, by the availability of data generated even in far-flung locations, and operationally, by the adoption of standard protocols. A side-effect, however, is that now the safety and stability of a local process and, in turn, of the entire plant are more vulnerable to malicious agents. Leveraging the communication infrastructure, the authors here present the design of networked control systems with built-in resilience. Specifically, the paper addresses attacks known as false data injections that originate within compromised sensors. In the proposed framework for closed-loop control, the feedback signal is constructed by weighted consensus of estimates of the process state gathered from other interconnected processes. Observers are introduced to generate the state estimates from the local data. Side-channel monitors are attached to each primary sensor in order to assess proper code execution. These monitors provide estimates of the trust assigned to each observer output and, more importantly, independent of it; these estimates serve as weights in the consensus algorithm. The authors tested the concept on a multi-sensor networked physical experiment with six primary sensors. The weighted consensus was demonstrated to yield a feedback signal within specified accuracy even if four of the six primary sensors were injecting false data.

Airports are at the forefront of technological innovation, mainly due to the fact that the number of air travel passengers is exponentially increasing every year. As a result, airports enhance infrastructure's intelligence and evolve as smart facilities to support growth, by offering a pleasurable travel experience, which plays a vital role in increasing revenue of aviation sector. New challenges are coming up, which aviation has to deal and adapt, such as the integration of Industrial IoT in airport facilities and the increased use of Bring Your Own Device from travelers and employees. Cybersecurity is becoming a key enabler for safety, which is paramount in the aviation context. Smart airports strive to provide optimal services in a reliable and sustainable manner, by working around the domains of growth, efficiency, safety andsecurity. This paper researches the implementation rate of cybersecurity measures and best practices to improve airports cyber resilience. With the aim to enhance operational practices anddevelop robust cybersecurity governance in smart airports, we analyze security gaps in different areas including technical, organizational practices and policies.

In this paper, we consider the runtime verification problem of safety hyperproperties for deterministic programs. Several security and information-flow policies such as data minimality, non-interference, integrity, and software doping are naturally expressed formally as safety hyperproperties. Although there are monitoring results for hyperproperties, the algorithms are very complex since these are properties over set of traces, and not over single traces. For the deterministic input-output programs that we consider, and the specific safety hyperproperties we are interested in, the problem can be reduced to monitoring of trace properties. In this paper, we present a simpler monitoring approach for safety hyperproperties of deterministic programs. The approach involves transforming the given safety hyperproperty into a trace property, extracting a characteristic predicate for the given hyperproperty, and providing a parametric monitor taking such predicate as parameter. For any hyperproperty in the considered subclass, we show how runtime verification monitors can be synthesised. We have implemented our approach in the form of a parameterised monitor for the given class, and have applied it to a number of hyperproperties including data minimisation, non-interference, integrity and software doping. We show results concerning both offline and online monitoring.

Autonomous systems are gaining momentum in various application domains, such as autonomous vehicles, autonomous transport robotics and self-adaptation in smart homes. Product liability regulations impose high standards on manufacturers of such systems with respect to dependability (safety, security and privacy). Today's conventional engineering methods are not adequate for providing guarantees with respect to dependability requirements in a cost-efficient manner, e.g. road tests in the automotive industry sum up millions of miles before a system can be considered sufficiently safe. System engineers will no longer be able to test and respectively formally verify autonomous systems during development time in order to guarantee the dependability requirements in advance. In this vision paper, we introduce a new holistic software systems engineering approach for autonomous systems, which integrates development time methods as well as operation time techniques. With this approach, we aim to give the users a transparent view of the confidence level of the autonomous system under use with respect to the dependability requirements. We present already obtained results and point out research goals to be addressed in the future.

Many governments organizations in Libya have started transferring traditional government services to e-government. These e-services will benefit a wide range of public. However, deployment of e-government bring many new security issues. Attackers would take advantages of vulnerabilities in these e-services and would conduct cyber attacks that would result in data loss, services interruptions, privacy loss, financial loss, and other significant loss. The number of vulnerabilities in e-services have increase due to the complexity of the e-services system, a lack of secure programming practices, miss-configuration of systems and web applications vulnerabilities, or not staying up-to-date with security patches. Unfortunately, there is a lack of study being done to assess the current security level of Libyan government websites. Therefore, this study aims to assess the current security of 16 Libyan government websites using penetration testing framework. In this assessment, no exploits were committed or tried on the websites. In penetration testing framework (pen test), there are four main phases: Reconnaissance, Scanning, Enumeration, Vulnerability Assessment and, SSL encryption evaluation. The aim of a security assessment is to discover vulnerabilities that could be exploited by attackers. We also conducted a Content Analysis phase for all websites. In this phase, we searched for security and privacy policies implementation information on the government websites. The aim is to determine whether the websites are aware of current accepted standard for security and privacy. From our security assessment results of 16 Libyan government websites, we compared the websites based on the number of vulnerabilities found and the level of security policies. We only found 9 websites with high and medium vulnerabilities. Many of these vulnerabilities are due to outdated software and systems, miss-configuration of systems and not applying the latest security patches. These vulnerabilities could be used by cyber hackers to attack the systems and caused damages to the systems. Also, we found 5 websites didn't implement any SSL encryption for data transactions. Lastly, only 2 websites have published security and privacy policies on their websites. This seems to indicate that these websites were not concerned with current standard in security and privacy. Finally, we classify the 16 websites into 4 safety categories: highly unsafe, unsafe, somewhat unsafe and safe. We found only 1 website with a highly unsafe ranking. Based on our finding, we concluded that the security level of the Libyan government websites are adequate, but can be further improved. However, immediate actions need to be taken to mitigate possible cyber attacks by fixing the vulnerabilities and implementing SSL encryption. Also, the websites need to publish their security and privacy policy so the users could trust their websites.

Wireless Sensor Networks (WSNs) are used in sensitive applications such as in asset monitoring applications. Due to the sensitivity of information in these applications, it is important to ensure that flow of data between sensor nodes is secure and does not expose any information about the source node or the monitored assets. This paper proposes a scheme to preserve the source location privacy based on random routing techniques. To achieve high privacy, the proposed scheme randomly sends packet to sink node through tactically positioned agent nodes. The position of agent nodes is designed to guarantee that successive packets are routed through highly random and perplexing routing paths as compared to other routing schemes. Simulation results demonstrate that proposed scheme provides longer safety period and higher privacy against both, patient and cautious adversaries.