Connected devices have become an integral part of modern homes and household devices, such as vacuum cleaners and refrigerators, are now often connected to networks. This connectivity introduces an entry point for cyber attackers. The plethora of successful cyber attacks against household IoT indicates that the security of these devices, or the security of applications related to these devices, is often lacking. Existing penetration testing studies usually focus on individual devices, and recent studies often mention the need for more extensive vulnerability assessments. Therefore, this study investigates the cyber security of devices commonly located in connected homes. Systematic penetration tests were conducted on 22 devices in five categories related to connected homes: smart door locks, smart cameras, smart car adapters/garages, smart appliances, and miscellaneous smart home devices. In total, 17 vulnerabilities were discovered and published as new CVEs. Some CVEs received critical severity rankings from the National Vulnerability Database (NVD), reaching 9.8/10. The devices are already being sold and used worldwide, and the discovered vulnerabilities could lead to severe consequences for residents, such as an attacker gaining physical access to the house. In addition to the published CVEs, 52 weaknesses were discovered that could potentially lead to new CVEs in the future. To our knowledge, this is the most comprehensive study on penetration testing of connected household products.

Nowadays, IT infrastructures are involved in making innumerable aspects of our lives convenient, starting with water or energy distribution systems, and ending with e-commerce solutions and online banking services. In the worst case, cyberattacks on such infrastructures can paralyze whole states and lead to losses in terms of both human lives and money. One of the approaches to increase security of IT infrastructures relies on modeling possible ways of compromising them by potential attackers. To facilitate creation and reusability of such models, domain specific languages (DSLs) can be created. Ideally, a user will employ a DSL for modeling their infrastructure of interest, with the domain-specific threats and attack logic being already encoded in the DSL by the domain experts. The Meta Attack Language (MAL) has been introduced previously as a meta-DSL for development of security-oriented DSLs. In this work, we define formally the syntax and a semantics of MAL to ease a common understanding of MAL’s functionalities and enable reference implementations on different technical platforms. It’s applicability for modeling and analysis of security of IT infrastructures is illustrated with an example.

Migrating enterprises and business capabilities to cloud platforms like Amazon Web Services (AWS) has become increasingly common. However, securing cloud operations, especially at large scales, can quickly become intractable. Customer-side issues such as service misconfigurations, data breaches, and insecure changes are prevalent. Furthermore, cloud-specific tactics and techniques paired with application vulnerabilities create a large and complex search space. Various solutions and modeling languages for cloud security assessments exist. However, no single one appeared sufficiently cloud-centered and holistic. Many also did not account for tactical security dimensions. This article, therefore, presents a domain-specific modeling language for AWS environments. When used to model AWS environments, manually or automatically, the language automatically constructs and traverses attack graphs to assess security. Assessments, therefore, require minimal security expertise from the user. The modeling language was primarily tested on four third-party AWS environments through securiCAD Vanguard, a commercial tool built around the AWS modeling language. The language was validated further by measuring performance on models provided by anonymous end users and a comparison with a similar open source assessment tool. As of March 2020, the modeling language could represent essential AWS structures, cloud tactics, and threats. However, the tests highlighted certain shortcomings. Data collection steps, such as planted credentials, and some missing tactics were obvious. Nevertheless, the issues covered by the DSL were already reminiscent of common issues with real-world precedents. Future additions to attacker tactics and addressing data collection should yield considerable improvements.

This paper investigates methods to secure Remote Terminal Units (RTUs) which are the building blocks of a smart grid systems - the next generation version to replace the power grid systems that are being used today. RTUs are identified as the heart of automation and control (SCADA) systems by the systems engineers. As such, security and maintaining nominal operability of such devices has prime importance, especially for the industrial automation networks such as the smart grid. A way of measuring the security of systems and networks is executing a series of cybersecurity weakness assessment tests called penetration testing. Another way of such an assessment is called vulnerability analysis by threat modelling which involves careful investigation and modelling of each and every component of a network/system under investigation. This article, aims at marrying these two methodologies for the vulnerability assessment of the RTUs in a methodological and scientific way.

Cyberattack simulations appear across multiple computer security domains and are interpreted in many different but equally viable ways. However, this makes the topic appear fragmented and inconsistent, making it challenging to identify and communicate relevant research. Therefore, this article contributes to a unified baseline by presenting the results of a systematic literature review. The review targeted attack simulations published between 1999 and 2019, specifically those exploring which specific steps result in successful attacks. The search initially produced 647 articles, later reduced to 11 key contributions. Despite being scattered across application domains, their general aims, contributions, and problem statements were remarkably similar. This was despite them generally not citing each other or a common body of work. However, the attack simulations differed in implementation details, such as modeling techniques, attacker decision-making, and how time is incorporated. How to construct a fully unified view of the entire topic is still somewhat unclear, particularly from the 11 articles. However, the results presented here should help orient practitioners and researchers interested in attack simulations regarding both present and future work. Particularly since, despite the seemingly implausible sample, the cumulative evidence suggests that attack simulations have yet to be pursued as a distinct research topic.

Attack simulations are a feasible means of assessing the cyber security of various systems. Simulations can replicate the steps taken by an attacker to compromise sensitive system assets, and the time required for the acquisition of assets of interests can be calculated. One widely accepted approach to such simulations is the modelling of attack steps and their dependencies in a formal manner using attack graphs. To reduce the effort of creating new attack graphs for each system in a given domain, one can employ domain-specific attack-modeling languages to codify common attack logic. The Meta Attack Language has been proposed as a framework for developing domain-specific attack languages. In this article, we propose vehicleLang as a domain-specific language for modeling vehicles in the context of corresponding information technology infrastructures and analyzing weaknesses related to known attacks. To model domain-specific attributes, we reviewed existing literature to develop a comprehensive language, which was then verified through a series of interviews with domain experts from the automotive industry. Specifically, a systematic literature review was performed to identify possible attacks against vehicles. The identified attacks served as a blueprint for the evaluation of vehicleLang’s simulation capabilities. Finally, the language was validated using the Feigenbaum test methodology.

Abstract Enterprise systems are growing in complexity, and the adoption of cloud and mobile services has greatly increased the attack surface. To proactively address these security issues in enterprise systems, this paper proposes a threat modeling language for enterprise security based on the MITRE Enterprise ATT&CK Matrix. It is designed using the Meta Attack Language framework and focuses on describing system assets, attack steps, defenses, and asset associations. The attack steps in the language represent adversary techniques as listed and described by MITRE. This entity-relationship model describes enterprise IT systems as a whole; by using available tools, the proposed language enables attack simulations on its system model instances. These simulations can be used to investigate security settings and architectural changes that might be implemented to secure the system more effectively. Our proposed language is tested with a number of unit and integration tests. This is visualized in the paper with two real cyber attacks modeled and simulated.

The increase of cyber-attacks raised security concerns for critical assets worldwide in the last decade. Leading to more efforts spent towards increasing the cyber security among companies and countries. For the sake of enhancing cyber security, representation and testing of attacks have prime importance in understanding system vulnerabilities. One of the available tools for simulating attacks on systems is the Meta Attack Language (MAL), which allows representing the effects of certain cyber-attacks. However, only understanding the component vulnerabilities is not enough in securing enterprise systems. Another important factor is the ‘human‘, which constitutes the biggest ‘insider threat‘. For this, Security Behavior Analysis (SBA) helps understanding which system components that might be directly affected by the ‘human‘. As such, in this work, the authors present an approach for integrating user actions, so called “security behavior”, by mapping SBA to a MAL-based language through MITRE ATT&CK techniques.

Securing web servers and proxies is critical for enterprise networks. Such Internet-facing systems make up a significant portion of the remote attack surface and, thus, serve as prime targets. HTTP Request Smuggling (HRS) is a vulnerability that arises when web servers and proxies interpret the length of a single HTTP request differently. In this study, empirical testing was used to find parsing behaviors that could lead to HRS in six popular proxies and six servers. A literature study was conducted to compile a corpus containing requests adopting all known HRS techniques and different variations. A test harness was built to enable the automatic sending of requests and recording of responses. The responses were then manually analyzed to identify behaviors vulnerable to HRS. In total, 19 vulnerable behaviors were found, and by combining the proxies with the servers, two almost full and four full attacks could be performed. At least one behavior that went against the HTTP specification was found in every system tested. However, not all of these behaviors enabled HRS. In conclusion, most proxies had strict parsing and did not accept requests that could lead to HRS. The servers, however, were not so strict.

Process digitization and integration is an increasing need for enterprises, while cyber-attacks denote a growing threat. Using the Business Process Model and Notation (BPMN) is common to handle the digital and integration focus within and across organizations. In other parts of the same companies, threat modeling and attack graphs are used for analyzing the security posture and resilience.In this paper, we propose a novel approach to use attack graph simulations on processes represented in BPMN. Our contributions are the identification of BPMN’s attack surface, a mapping of BPMN elements to concepts in a Meta Attack Language (MAL)-based Domain-Specific Language (DSL), called coreLang, and a prototype to demonstrate our approach in a case study using a real-world invoice integration process. The study shows that non-invasively enriching BPMN instances with cybersecurity analysis through attack graphs is possible without much human expert input. The resulting insights into potential vulnerabilities could be beneficial for the process modelers.

Abstract Power systems are one of the critical infrastructures that has seen an increase in cyber security threats due to digitalization. The digitalization also affects the size and complexity of the infrastructure and therefore makes it more difficult to gain an overview in order to secure the entire power system from attackers. One method of how to gain an overview of possible vulnerabilities and security threats is to use threat modeling. In threat modeling, information regarding the vulnerabilities and possible attacks of power systems is required to create an accurate and useful model. There are several different sources for this information. In this paper we conduct a systematic literature review to find which information sources that have been used in power system threat modeling research. Six different information sources were found: expert knowledge, logs & alerts, previous research, system’s state, vulnerability scoring & databases, and vulnerability scanners.

IoT (Internet of Things) devices have grown exponentially in the last years, both in the sheer number of devices and concerning areas of applications being introduced. Together with this rapid development we are faced with an increased need for IoT Security. Devices that have previously been analogue, such as refrigerators, door locks, and cars are now turning digital and are exposed to the threats posed by an Internet connection. This paper investigates how two existing security features (geographic IP Blocking with GeoIP and rate-limited connections with fail2ban) can be used to enhance the security of IoT devices. We analyze the success of each method by comparing units with and without the security features, collecting and comparing data about the received attacks for both kinds. The result shows that the GeoIP security feature can reduce attacks by roughly 93% and fail2ban by up to 99%. Further work in the field is encouraged to validate our findings, create better GeoIP tools, and to better understand the potential of the security techniques at a larger scale. The security features are implemented in aws instances made to simulate IoT devices, and measured with honeypots and IDSs (Intrusion Detection Systems) that collect data from the received attacks. The research is made as a fundamental work to later be extended by implementing the security features in more devices, such as single board computers that will simulate IoT devies even more accurately.

Threat Modeling and Attack Simulations of Smart Cities : A literature review and explorative study

Abstract Threat modeling is of increasing importance to IT security, and it is a complex and resource demanding task. The aim of automating threat modeling is to simplify model creation by using data that are already available. However, the collected data often lack context; this can make the automated models less precise in terms of domain knowledge than those created by an expert human modeler. The lack of domain knowledge in modeling automation can be addressed with ontologies. In this paper, we introduce an ontology framework to improve automatic threat modeling. The framework is developed with conceptual modeling and validated using three different datasets: a small scale utility lab, water utility control network, and university IT environment. The framework produced successful results such as standardizing input sources, removing duplicate name entries, and grouping application software more logically.

Cyber-attacks on power assets can have disastrous consequences for individuals, regions, and whole nations. In order to respond to these threats, the assessment of power grids' and plants' cyber security can foster a higher degree of safety for the whole infrastructure dependent on power. Hitherto, we propose the use of attack simulations based on system architecture models. To reduce the effort of creating new attack graphs for each system of a given type, domain-specific attack languages may be employed. They codify common attack logics of the considered domain. Previously, MAL (the Meta Attack Language) was proposed, which serves as a framework to develop domain specific attack languages. We extend the tool set of MAL by developing an approach to model security domains in ArchiMate notation. Next, those models are used to create a MAL instance, which reflects the concepts modeled in ArchiMate. These instances serve as input to simulate attacks on certain systems. To show the applicability of our approach, we conduct two case studies in the power domain. On the one hand, we model a thermal power plant and possible attacks on it. On the other hand, we use the attack on the Ukrainian power grid for our case study.

Attack simulations are a feasible means to assess the cyber security of systems. The simulations trace the steps taken by an attacker to compromise sensitive system assets. Moreover, they allow to ...

Modern vehicles are dependent on software, and are often connected to the Internet or other external services, which makes them vulnerable to various attacks. To improve security for Internet facing systems, holistic threat modeling is becoming a common way to proactively make decisions and design for security. One approach that has not been commonly implemented is to enhance the threat models with probabilistic attack simulations. That is, incorporating security intelligence, attack types, vulnerabilities, and countermeasures to get objective security metrics and risk assessments. This combination has been shown efficient in other disciplines, e.g. energy and banking. However, it has so far been fairly unexplored in the vehicle domain. This position paper reviews previous research in the field, and implements a vehicle threat model using a tool called securiCAD, based on which future research requirements for connected vehicle attack simulations are also derived. The main findings are: 1) not much work has been done in the combined area of connected vehicles and threat modeling with attack simulations, 2) initial tests show that the approach is useful, 3) more research in vehicle specific attacks and countermeasures is needed in order to provide more accurate simulation results, and 4) a more tailored metamodel is needed for the vehicle domain.

Attack simulations may be used to assess the cyber security of systems. In such simulations, the steps taken by an attacker in order to compromise sensitive system assets are traced, and a time estimate may be computed from the initial step to the compromise of assets of interest. Attack graphs constitute a suitable formalism for the modeling of attack steps and their dependencies, allowing the subsequent simulation.

The Common Vulnerability Scoring System (CVSS) is the state-of-the art system for assessing software vulnerabilities. However, it has been criticized for lack of validity and practitioner relevance. In this paper, the credibility of the CVSS scoring data found in five leading databases-NVD, X-Force, OSVDB, CERT-VN, and Cisco-is assessed. A Bayesian method is used to infer the most probable true values underlying the imperfect assessments of the databases, thus circumventing the problem that ground truth is not known. It is concluded that with the exception of a few dimensions, the CVSS is quite trustworthy. The databases are relatively consistent, but some are better than others. The expected accuracy of each database for a given dimension can be found by marginalizing confusion matrices. By this measure, NVD is the best and OSVDB is the worst of the assessed databases.

Business transactions executed between organizations and individuals are largely operated on digital environments, conducting to an industrial interoperability challenge demanding secure environmen ...

In this paper we introduce pwnPr3d, a probabilistic threat modeling approach for automatic attack graph generation based on network modeling. The aim is to provide stakeholders in organizations with a holistic approach that both provides high-level overview and technical details. Unlike many other threat modeling and attack graph approaches that rely heavily on manual work and security expertise, our language comes with built-in security analysis capabilities. pwnPr3d generates probability distributions over the time to compromise assets.

SUMMARY It is difficult to manage complex software systems. Thus, many research initiatives focus on how to improve software development efficiency and maintainability. However, the trend in the industry is still alarming, software development projects fail, and maintenance is becoming more and more expensive. One problem could be that research has been focusing on the wrong things. Most research publications address either process improvements or architectural improvements. There are few known approaches that consider how architectural changes affect processes and vice versa. One method proposed, called the Business–Architecture–Process method, takes these aspects into consideration. In 2007 the method was tested in one case study. Findings in the 2007 case study show that the method is useful, but in need of improvements and further validation. The present paper employs the method in a second case study. The contribution in this paper is thus a second test and validation of the proposed method, and useful method improvements for future use of the method. Copyright © 2011 John Wiley & Sons, Ltd.

Enterprise Architecture models can be used to support IT/business alignment. However, existing approaches do not distinguish between different IT/business alignment situations. Since companies face diverse challenges in achieving a high degree of IT/business alignment, a universal `one size fits all' approach does not seem appropriate. This paper proposes to decompose the IT/business alignment problem into tangible qualities for business, IT systems, and IT governance. An explorative study among 162 professionals is used to distinguish four IT/business alignment situations, i.e. four clusters of IT/business alignment problems. These situations each represent the current state according to certain qualities and also the priorities for future development. In order to increase IT/business alignment, enterprise architecture meta models are proposed for each identified situation. One core meta model (to reflect common priorities) as well as situation specific extensions are presented.

Creating accurate models of information systems is an important but challenging task. It is generally well understood that such modeling encompasses general scientific issues, but the monetary aspects of the modeling of software systems are not equally well acknowledged. The present paper describes a method using Bayesian networks for optimizing modeling strategies, perceived as a trade-off between these two aspects. Using GeNIe, a graphical tool with the proper Bayesian algorithms implemented, decision support can thus be provided to the modeling process. Specifically, an informed trade-off can be made, based on the modeler's prior knowledge of the predictive power of certain models, combined with his projection of their costs. It is argued that this method might enhance modeling of large and complex software systems in two principal ways: Firstly, by enforcing rigor and making hidden assumptions explicit. Secondly, by enforcing cost awareness even in the early phases of modeling. The method should be used primarily when the choice of modeling can have great economic repercussions.

The goal of IT governance is not only to achieve internal efficiency in an IT organization, but also to support IT’s role as a business enabler. The latter is here denoted IT governance performance. IT management cannot control the IT governance performance directly. Instead, their realm of control includes several IT governance maturity indicators such as the existence of different IT activities, documents, metrics and roles. Current IT governance frameworks are suitable for describing IT governance, IT-systems, and business processes, but lack the ability to predict how changes to the IT governance maturity indicators affect IT governance performance. Bayesian networks are widely used for goal modeling and prediction in several research fields. This paper presents an application of Bayesian networks for IT governance performance prediction. Data from 35 case studies conducted in a variety of organizations has been used to determine the behavior of the network. An assumption on linearity is introduced in order to compensate for the limited amount of data, and the network learns using the proposed Linear Conditional Probability Matrix Generator. The resulting Bayesian network for IT governance performance prediction can be used to support IT governance decision-making.

The discipline of enterprise architecture advocates the use of models to support decision-making on enterprise-wide information system issues. In order to provide such support, enterprise architecture models should be amenable to analyses of various properties, as e.g. the level of enterprise information security. This paper proposes the use of a formal language to support such analysis. Such a language needs to be able to represent causal relations between, and definitions of, various concepts as well as uncertainty with respect to both concepts and relations. To support decision-making properly, the language must also allow the representation of goals and decision alternatives. This paper evaluates a number of languages with respect to these requirements, and selects influence diagrams for further consideration. The influence diagrams are then extended to fully satisfy the requirements. The syntax and semantics of the extended influence diagrams are detailed in the paper, and their use is demonstrated in an example