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Alshawish, Ali, Spielvogel, Korbinian, de Meer, Hermann.  2019.  A Model-Based Time-to-Compromise Estimator to Assess the Security Posture of Vulnerable Networks. 2019 International Conference on Networked Systems (NetSys). :1-3.

Several operational and economic factors impact the patching decisions of critical infrastructures. The constraints imposed by such factors could prevent organizations from fully remedying all of the vulnerabilities that expose their (critical) assets to risk. Therefore, an involved decision maker (e.g. security officer) has to strategically decide on the allocation of possible remediation efforts towards minimizing the inherent security risk. This, however, involves the use of comparative judgments to prioritize risks and remediation actions. Throughout this work, the security risk is quantified using the security metric Time-To-Compromise (TTC). Our main contribution is to provide a generic TTC estimator to comparatively assess the security posture of computer networks taking into account interdependencies between the network components, different adversary skill levels, and characteristics of (known and zero-day) vulnerabilities. The presented estimator relies on a stochastic TTC model and Monte Carlo simulation (MCS) techniques to account for the input data variability and inherent prediction uncertainties.

Zieger, Andrej, Freiling, Felix, Kossakowski, Klaus-Peter.  2018.  The $\beta$-Time-to-Compromise Metric for Practical Cyber Security Risk Estimation. 2018 11th International Conference on IT Security Incident Management IT Forensics (IMF). :115-133.

To manage cybersecurity risks in practice, a simple yet effective method to assess suchs risks for individual systems is needed. With time-to-compromise (TTC), McQueen et al. (2005) introduced such a metric that measures the expected time that a system remains uncompromised given a specific threat landscape. Unlike other approaches that require complex system modeling to proceed, TTC combines simplicity with expressiveness and therefore has evolved into one of the most successful cybersecurity metrics in practice. We revisit TTC and identify several mathematical and methodological shortcomings which we address by embedding all aspects of the metric into the continuous domain and the possibility to incorporate information about vulnerability characteristics and other cyber threat intelligence into the model. We propose $\beta$-TTC, a formal extension of TTC which includes information from CVSS vectors as well as a continuous attacker skill based on a $\beta$-distribution. We show that our new metric (1) remains simple enough for practical use and (2) gives more realistic predictions than the original TTC by using data from a modern and productively used vulnerability database of a national CERT.

Hagan, Matthew, Siddiqui, Fahad, Sezer, Sakir.  2018.  Policy-Based Security Modelling and Enforcement Approach for Emerging Embedded Architectures. 2018 31st IEEE International System-on-Chip Conference (SOCC). :84–89.
Complex embedded systems often contain hard to find vulnerabilities which, when exploited, have potential to cause severe damage to the operating environment and the user. Given that threats and vulnerabilities can exist within any layer of the complex eco-system, OEMs face a major challenge to ensure security throughout the device life-cycle To lower the potential risk and damage that vulnerabilities may cause, OEMs typically perform application threat analysis and security modelling. This process typically provides a high level guideline to solving security problems which can then be implemented during design and development. However, this concept presents issues where new threats or unknown vulnerability has been discovered. To address this issue, we propose a policy-based security modelling approach, which utilises a configurable policy engine to apply new policies that counter serious threats. By utilising this approach, the traditional security modelling approaches can be enhanced and the consequences of a new threat greatly reduced. We present a realistic use case of connected car, applying several attack scenarios. By utilising STRIDE threat modelling and DREAD risk assessment model, adequate policies are derived to protect the car assets. This approach poses advantages over the standard approach, allowing a policy update to counter a new threat, which may have otherwise required a product redesign to alleviate the issue under the traditional approach.
Torkura, K. A., Sukmana, M. I. H., Meinig, M., Cheng, F., Meinel, C., Graupner, H..  2018.  A Threat Modeling Approach for Cloud Storage Brokerage and File Sharing Systems. NOMS 2018 - 2018 IEEE/IFIP Network Operations and Management Symposium. :1-5.
Cloud storage brokerage systems abstract cloud storage complexities by mediating technical and business relationships between cloud stakeholders, while providing value-added services. This however raises security challenges pertaining to the integration of disparate components with sometimes conflicting security policies and architectural complexities. Assessing the security risks of these challenges is therefore important for Cloud Storage Brokers (CSBs). In this paper, we present a threat modeling schema to analyze and identify threats and risks in cloud brokerage brokerage systems. Our threat modeling schema works by generating attack trees, attack graphs, and data flow diagrams that represent the interconnections between identified security risks. Our proof-of-concept implementation employs the Common Configuration Scoring System (CCSS) to support the threat modeling schema, since current schemes lack sufficient security metrics which are imperatives for comprehensive risk assessments. We demonstrate the efficiency of our proposal by devising CCSS base scores for two attacks commonly launched against cloud storage systems: Cloud sStorage Enumeration Attack and Cloud Storage Exploitation Attack. These metrics are then combined with CVSS based metrics to assign probabilities in an Attack Tree. Thus, we show the possibility combining CVSS and CCSS for comprehensive threat modeling, and also show that our schemas can be used to improve cloud security.
Mavroeidis, V., Vishi, K., Jøsang, A..  2018.  A Framework for Data-Driven Physical Security and Insider Threat Detection. 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM). :1108–1115.

This paper presents PSO, an ontological framework and a methodology for improving physical security and insider threat detection. PSO can facilitate forensic data analysis and proactively mitigate insider threats by leveraging rule-based anomaly detection. In all too many cases, rule-based anomaly detection can detect employee deviations from organizational security policies. In addition, PSO can be considered a security provenance solution because of its ability to fully reconstruct attack patterns. Provenance graphs can be further analyzed to identify deceptive actions and overcome analytical mistakes that can result in bad decision-making, such as false attribution. Moreover, the information can be used to enrich the available intelligence (about intrusion attempts) that can form use cases to detect and remediate limitations in the system, such as loosely-coupled provenance graphs that in many cases indicate weaknesses in the physical security architecture. Ultimately, validation of the framework through use cases demonstrates and proves that PS0 can improve an organization's security posture in terms of physical security and insider threat detection.

Zieger, A., Freiling, F., Kossakowski, K..  2018.  The β-Time-to-Compromise Metric for Practical Cyber Security Risk Estimation. 2018 11th International Conference on IT Security Incident Management IT Forensics (IMF). :115–133.

To manage cybersecurity risks in practice, a simple yet effective method to assess suchs risks for individual systems is needed. With time-to-compromise (TTC), McQueen et al. (2005) introduced such a metric that measures the expected time that a system remains uncompromised given a specific threat landscape. Unlike other approaches that require complex system modeling to proceed, TTC combines simplicity with expressiveness and therefore has evolved into one of the most successful cybersecurity metrics in practice. We revisit TTC and identify several mathematical and methodological shortcomings which we address by embedding all aspects of the metric into the continuous domain and the possibility to incorporate information about vulnerability characteristics and other cyber threat intelligence into the model. We propose β-TTC, a formal extension of TTC which includes information from CVSS vectors as well as a continuous attacker skill based on a β-distribution. We show that our new metric (1) remains simple enough for practical use and (2) gives more realistic predictions than the original TTC by using data from a modern and productively used vulnerability database of a national CERT.

Väisänen, Teemu, Noponen, Sami, Latvala, Outi-Marja, Kuusijärvi, Jarkko.  2018.  Combining Real-Time Risk Visualization and Anomaly Detection. Proceedings of the 12th European Conference on Software Architecture: Companion Proceedings. :55:1-55:7.

Traditional risk management produces a rather static listing of weaknesses, probabilities and mitigations. Large share of cyber security risks realize through computer networks. These attacks or attack attempts produce events that are detected by various monitoring techniques such as Intrusion Detection Systems (IDS). Often the link between detecting these potentially dangerous real-time events and risk management process is lacking, or completely missing. This paper presents means for transferring and visualizing the network events in the risk management instantly with a tool called Metrics Visualization System (MVS). The tool is used to dynamically visualize network security events of a Terrestrial Trunked Radio (TETRA) network running in Software Defined Networking (SDN) context as a case study. Visualizations are presented with a treelike graph, that gives a quick easily understandable overview of the cyber security situation. This paper also discusses what network security events are monitored and how they affect the more general risk levels. The major benefit of this approach is that the risk analyst is able to map the designed risk tree/security metrics into actual real-time events and view the system's security posture with the help of a runtime visualization view.

Joo, M., Seo, J., Oh, J., Park, M., Lee, K..  2018.  Situational Awareness Framework for Cyber Crime Prevention Model in Cyber Physical System. 2018 Tenth International Conference on Ubiquitous and Future Networks (ICUFN). :837-842.
Recently, IoT, 5G mobile, big data, and artificial intelligence are increasingly used in the real world. These technologies are based on convergenced in Cyber Physical System(Cps). Cps technology requires core technologies to ensure reliability, real-time, safety, autonomy, and security. CPS is the system that can connect between cyberspace and physical space. Cyberspace attacks are confused in the real world and have a lot of damage. The personal information that dealing in CPS has high confidentiality, so the policies and technique will needed to protect the attack in advance. If there is an attack on the CPS, not only personal information but also national confidential data can be leaked. In order to prevent this, the risk is measured using the Factor Analysis of Information Risk (FAIR) Model, which can measure risk by element for situational awareness in CPS environment. To reduce risk by preventing attacks in CPS, this paper measures risk after using the concept of Crime Prevention Through Environmental Design(CPTED).
McDermott, C. D., Petrovski, A. V., Majdani, F..  2018.  Towards Situational Awareness of Botnet Activity in the Internet of Things. 2018 International Conference On Cyber Situational Awareness, Data Analytics And Assessment (Cyber SA). :1-8.
The following topics are dealt with: security of data; risk management; decision making; computer crime; invasive software; critical infrastructures; data privacy; insurance; Internet of Things; learning (artificial intelligence).
Kawanishi, Y., Nishihara, H., Souma, D., Yoshida, H., Hata, Y..  2018.  A Study on Quantitative Risk Assessment Methods in Security Design for Industrial Control Systems. 2018 IEEE 16th Intl Conf on Dependable, Autonomic and Secure Computing, 16th Intl Conf on Pervasive Intelligence and Computing, 4th Intl Conf on Big Data Intelligence and Computing and Cyber Science and Technology Congress(DASC/PiCom/DataCom/CyberSciTech). :62-69.

In recent years, there has been progress in applying information technology to industrial control systems (ICS), which is expected to make the development cost of control devices and systems lower. On the other hand, the security threats are becoming important problems. In 2017, a command injection issue on a data logger was reported. In this paper, we focus on the risk assessment in security design for data loggers used in industrial control systems. Our aim is to provide a risk assessment method optimized for control devices and systems in such a way that one can prioritize threats more preciously, that would lead work resource (time and budget) can be assigned for more important threats than others. We discuss problems with application of the automotive-security guideline of JASO TP15002 to ICS risk assessment. Consequently, we propose a three-phase risk assessment method with a novel Risk Scoring Systems (RSS) for quantitative risk assessment, RSS-CWSS. The idea behind this method is to apply CWSS scoring systems to RSS by fixing values for some of CWSS metrics, considering what the designers can evaluate during the concept phase. Our case study with ICS employing a data logger clarifies that RSS-CWSS can offer an interesting property that it has better risk-score dispersion than the TP15002-specified RSS.

Rubio-Medrano, Carlos E., Zhao, Ziming, Ahn, Gail-Joon.  2018.  RiskPol : A Risk Assessment Framework for Preventing Attribute-Forgery Attacks to ABAC Policies. Proceedings of the Third ACM Workshop on Attribute-Based Access Control. :54–60.

Recently, attribute-based access control (ABAC) has emerged as a convenient paradigm for specifying, enforcing and maintaining rich and flexible authorization policies, leveraging attributes originated from multiple sources, e.g., operative systems, software modules, remote services, etc. However, attackers may try to bypass ABAC policies by compromising such sources to forge the attributes they provide, e.g., by deliberately manipulating the data contained within those attributes at will, in an effort to gain unintended access to sensitive resources as a result. In such a context, performing a proper risk assessment of ABAC policies, taking into account their enlisted attributes as well as their corresponding sources, becomes highly convenient to overcome zero-day security incidents or vulnerabilities, before they can be later exploited by attackers. With this in mind, we introduce RiskPol, an automated risk assessment framework for ABAC policies based on dynamically combining previously-assigned trust scores for each attribute source, such that overall scores at the policy level can be later obtained and used as a reference for performing a risk assessment on each policy. In this paper, we detail the general intuition behind our approach, its current status, as well as our plans for future work.

Hassan, M. H., Mostafa, S. A., Mustapha, A., Wahab, M. H. Abd, Nor, D. Md.  2018.  A Survey of Multi-Agent System Approach in Risk Assessment. 2018 International Symposium on Agent, Multi-Agent Systems and Robotics (ISAMSR). :1–6.
Risk Assessment is a foundation of decision-making about a future project behaviour or action. The related decision made might entail further analyzes to perform risk- reduction. The risk is a general phenomenon that takes different depicts and types. Static risk and its circumstances do not significantly change over time while dynamic risk arises out of the changes in interrelated circumstances. A Multi-Agent System (MAS) approach has become a popular tool to tackle different problems that relate to risk. The MAS helps in the decision aid processes and when responding to the consequences of the risk. This paper surveys some of the existing methods and techniques of risk assessment in different application domains. The survey focuses on the employment of MAS approach in risk assessment. The survey outcomes an illustration of the roles and contributions of the MAS in the Dynamic Risk Assessment (DRA) field.
Lesisa, T. G., Marnewick, A., Nel, H..  2018.  The Identification of Supplier Selection Criteria Within a Risk Management Framework Towards Consistent Supplier Selection. 2018 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM). :913–917.
The aim of the study is to evaluate the consistency of supplier risk assessment performed during the supplier selection process. Existing literature indicates that current supplier selection processes yield inconsistent results. Consistent supplier selection cannot be accomplished without stable risk assessment performed during the process. A case study was conducted in a train manufacturer in South Africa, and document analysis, interviews and questionnaires were employed to source information and data. Triangulation and pattern matching enabled a comparative study between literature and practice from which findings were derived. The study suggests selection criteria that may be considered when performing supplier risk assessment during the selection process. The findings indicate that structured supplier risk assessment with predefined supplier selection criteria may eliminate inconsistencies in supplier assessment and selection.
Winter, A., Deniaud, I., Marmier, F., Caillaud, E..  2018.  A risk assessment model for supply chain design. Implementation at Kuehne amp;\#x002B; Nagel Luxembourg. 2018 4th International Conference on Logistics Operations Management (GOL). :1–8.
Every company may be located at the junction of several Supply Chains (SCs) to meet the requirements of many different end customers. To achieve a sustainable competitive advantage over its business rivals, a company needs to continuously improve its relations to its different stakeholders as well as its performance in terms of integrating its decision processes and hence, its communication and information systems. Furthermore, customers' growing awareness of green and sustainable matters and new national and international regulations force enterprises to rethink their whole system. In this paper we propose a model to quantify the identified potential risks to assist in designing or re-designing a supply chain. So that managers may take adequate decisions to have the continuing ability of satisfying customers' requirements. A case study, developed at kuehne + nagel Luxembourg is provided.
Yu, R., Xue, G., Kilari, V. T., Zhang, X..  2018.  Deploying Robust Security in Internet of Things. 2018 IEEE Conference on Communications and Network Security (CNS). :1-9.

Popularization of the Internet-of-Things (IoT) has brought widespread concerns on IoT security, especially in face of several recent security incidents related to IoT devices. Due to the resource-constrained nature of many IoT devices, security offloading has been proposed to provide good-enough security for IoT with minimum overhead on the devices. In this paper, we investigate the inevitable risk associated with security offloading: the unprotected and unmonitored transmission from IoT devices to the offloaded security mechanisms. An important challenge in modeling the security risk is the dynamic nature of IoT due to demand fluctuations and infrastructure instability. We propose a stochastic model to capture both the expected and worst-case security risks of an IoT system. We then propose a framework to efficiently address the optimal robust deployment of security mechanisms in IoT. We use results from extensive simulations to demonstrate the superb performance and efficiency of our approach compared to several other algorithms.

Zou, Z., Wang, D., Yang, H., Hou, Y., Yang, Y., Xu, W..  2018.  Research on Risk Assessment Technology of Industrial Control System Based on Attack Graph. 2018 IEEE 3rd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC). :2420-2423.

In order to evaluate the network security risks and implement effective defenses in industrial control system, a risk assessment method for industrial control systems based on attack graphs is proposed. Use the concept of network security elements to translate network attacks into network state migration problems and build an industrial control network attack graph model. In view of the current subjective evaluation of expert experience, the atomic attack probability assignment method and the CVSS evaluation system were introduced to evaluate the security status of the industrial control system. Finally, taking the centralized control system of the thermal power plant as the experimental background, the case analysis is performed. The experimental results show that the method can comprehensively analyze the potential safety hazards in the industrial control system and provide basis for the safety management personnel to take effective defense measures.

Zheng, Erkang, Gates-Idem, Phil, Lavin, Matt.  2018.  Building a Virtually Air-Gapped Secure Environment in AWS: With Principles of Devops Security Program and Secure Software Delivery. Proceedings of the 5th Annual Symposium and Bootcamp on Hot Topics in the Science of Security. :11:1–11:8.

This paper presents the development and configuration of a virtually air-gapped cloud environment in AWS, to secure the production software workloads and patient data (ePHI) and to achieve HIPAA compliance.

Feng, S., Xiong, Z., Niyato, D., Wang, P., Leshem, A..  2018.  Evolving Risk Management Against Advanced Persistent Threats in Fog Computing. 2018 IEEE 7th International Conference on Cloud Networking (CloudNet). :1–6.
With the capability of support mobile computing demand with small delay, fog computing has gained tremendous popularity. Nevertheless, its highly virtualized environment is vulnerable to cyber attacks such as emerging Advanced Persistent Threats attack. In this paper, we propose a novel approach of cyber risk management for the fog computing platform. Particularly, we adopt the cyber-insurance as a tool for neutralizing cyber risks from fog computing platform. We consider a fog computing platform containing a group of fog nodes. The platform is composed of three main entities, i.e., the fog computing provider, attacker, and cyber-insurer. The fog computing provider dynamically optimizes the allocation of its defense computing resources to improve the security of the fog computing platform. Meanwhile, the attacker dynamically adjusts the allocation of its attack resources to improve the probability of successful attack. Additionally, to prevent from the potential loss due to attacks, the provider also makes a dynamic decision on the purchases ratio of cyber-insurance from the cyber-insurer for each fog node. Thereafter, the cyber-insurer accordingly determines the premium of cyber-insurance for each fog node. In our formulated dynamic Stackelberg game, the attacker and provider act as the followers, and the cyber-insurer acts as the leader. In the lower level, we formulate an evolutionary subgame to analyze the provider's defense and cyber-insurance subscription strategies as well as the attacker's attack strategy. In the upper level, the cyber-insurer optimizes its premium determination strategy, taking into account the evolutionary equilibrium at the lower-level evolutionary subgame. We analytically prove that the evolutionary equilibrium is unique and stable. Moreover, we provide a series of insightful analytical and numerical results on the equilibrium of the dynamic Stackelberg game.
Shearon, C. E..  2018.  IPC-1782 standard for traceability of critical items based on risk. 2018 Pan Pacific Microelectronics Symposium (Pan Pacific). :1–3.
Traceability has grown from being a specialized need for certain safety critical segments of the industry, to now being a recognized value-add tool for the industry as a whole that can be utilized for manual to automated processes End to End throughout the supply chain. The perception of traceability data collection persists as being a burden that provides value only when the most rare and disastrous of events take place. Disparate standards have evolved in the industry, mainly dictated by large OEM companies in the market create confusion, as a multitude of requirements and definitions proliferate. The intent of the IPC-1782 project is to bring the whole principle of traceability up to date and enable business to move faster, increase revenue, increase productivity, and decrease costs as a result of increased trust. Traceability, as defined in this standard will represent the most effective quality tool available, becoming an intrinsic part of best practice operations, with the encouragement of automated data collection from existing manufacturing systems which works well with Industry 4.0, integrating quality, reliability, product safety, predictive (routine, preventative, and corrective) maintenance, throughput, manufacturing, engineering and supply-chain data, reducing cost of ownership as well as ensuring timeliness and accuracy all the way from a finished product back through to the initial materials and granular attributes about the processes along the way. The goal of this standard is to create a single expandable and extendable data structure that can be adopted for all levels of traceability and enable easily exchanged information, as appropriate, across many industries. The scope includes support for the most demanding instances for detail and integrity such as those required by critical safety systems, all the way through to situations where only basic traceability, such as for simple consumer products, are required. A key driver for the adoption of the standard is the ability to find a relevant and achievable level of traceability that exactly meets the requirement following risk assessment of the business. The wealth of data accessible from traceability for analysis (e.g.; Big Data, etc.) can easily and quickly yield information that can raise expectations of very significant quality and performance improvements, as well as providing the necessary protection against the costs of issues in the market and providing very timely information to regulatory bodies along with consumers/customers as appropriate. This information can also be used to quickly raise yields, drive product innovation that resonates with consumers, and help drive development tests & design requirements that are meaningful to the Marketplace. Leveraging IPC 1782 to create the best value of Component Traceability for your business.
Ma, Y..  2018.  Constructing Supply Chains in Open Source Software. 2018 IEEE/ACM 40th International Conference on Software Engineering: Companion (ICSE-Companion). :458–459.
The supply chain is an extremely successful way to cope with the risk posed by distributed decision making in product sourcing and distribution. While open source software has similarly distributed decision making and involves code and information flows similar to those in ordinary supply chains, the actual networks necessary to quantify and communicate risks in software supply chains have not been constructed on large scale. This work proposes to close this gap by measuring dependency, code reuse, and knowledge flow networks in open source software. We have done preliminary work by developing suitable tools and methods that rely on public version control data to measure and comparing these networks for R language and emberjs packages. We propose ways to calculate the three networks for the entirety of public software, evaluate their accuracy, and to provide public infrastructure to build risk assessment and mitigation tools for various individual and organizational participants in open sources software. We hope that this infrastructure will contribute to more predictable experience with OSS and lead to its even wider adoption.
Palmer, D., Fazzari, S., Wartenberg, S..  2017.  A virtual laboratory approach for risk assessment of aerospace electronics trust techniques. 2017 IEEE Aerospace Conference. :1–8.
This paper describes a novel aerospace electronic component risk assessment methodology and supporting virtual laboratory structure designed to augment existing supply chain management practices and aid in Microelectronics Trust Assurance. This toolkit and methodology applies structure to the unclear and evolving risk assessment problem, allowing quantification of key risks affecting both advanced and obsolete systems that rely on semiconductor technologies. The impacts of logistics & supply chain risk, technology & counterfeit risk, and faulty component risk on trusted and non-trusted procurement options are quantified. The benefits of component testing on part reliability are assessed and incorporated into counterfeit mitigation calculations. This toolkit and methodology seek to assist acquisition staff by providing actionable decision data regarding the increasing threat of counterfeit components by assessing the risks faced by systems, identifying mitigation strategies to reduce this risk, and resolving these risks through the optimal test and procurement path based on the component criticality risk tolerance of the program.
Schlüter, F., Hetterscheid, E..  2017.  A Simulation Based Evaluation Approach for Supply Chain Risk Management Digitalization Scenarios. 2017 International Conference on Industrial Engineering, Management Science and Application (ICIMSA). :1–5.
Supply Chain wide proactive risk management based on real-time risk related information transparency is required to increase the security of modern, volatile supply chains. At this time, none or only limited empirical/objective information about digitalization benefits for supply chain risk management is available. A method is needed, which draws conclusion on the estimation of costs and benefits of digitalization initiatives. The paper presents a flexible simulation based approach for assessing digitalization scenarios prior to realization. The assessment approach is integrated into a framework and its applicability will be shown in a case study of a German steel producer, evaluating digitalization effects on the Mean Lead time-at-risk.
Khayyam, Y. E., Herrou, B..  2017.  Risk assessment of the supply chain: Approach based on analytic hierarchy process and group decision-making. 2017 International Colloquium on Logistics and Supply Chain Management (LOGISTIQUA). :135–141.
Faced with a turbulent economic, political and social environment, Companies need to build effective risk management systems in their supply chains. Risk management can only be effective when the risks identification and analysis are enough accurate. In this perspective, this paper proposes a risk assessment approach based on the analytic hierarchy process and group decision making. In this study, a new method is introduced that will reduce the impact of incoherent judgments on group decision-making, It is, the “reduced weight function” that decreases the weight associated to a member of the expert panel based on the consistency of its judgments.
Halabi, T., Bellaiche, M., Abusitta, A..  2018.  A Cooperative Game for Online Cloud Federation Formation Based on Security Risk Assessment. 2018 5th IEEE International Conference on Cyber Security and Cloud Computing (CSCloud)/2018 4th IEEE International Conference on Edge Computing and Scalable Cloud (EdgeCom). :83–88.

Cloud federations allow Cloud Service Providers (CSPs) to deliver more efficient service performance by interconnecting their Cloud environments and sharing their resources. However, the security of the federated Cloud service could be compromised if the resources are shared with relatively insecure and unreliable CSPs. In this paper, we propose a Cloud federation formation model that considers the security risk levels of CSPs. We start by quantifying the security risk of CSPs according to well defined evaluation criteria related to security risk avoidance and mitigation, then we model the Cloud federation formation process as a hedonic coalitional game with a preference relation that is based on the security risk levels and reputations of CSPs. We propose a federation formation algorithm that enables CSPs to cooperate while considering the security risk introduced to their infrastructures, and refrain from cooperating with undesirable CSPs. According to the stability-based solution concepts that we use to evaluate the game, the model shows that CSPs will be able to form acceptable federations on the fly to service incoming resource provisioning requests whenever required.

Yousef, K. M. A., AlMajali, A., Hasan, R., Dweik, W., Mohd, B..  2017.  Security risk assessment of the PeopleBot mobile robot research platform. 2017 International Conference on Electrical and Computing Technologies and Applications (ICECTA). :1–5.
Nowadays, robots are widely ubiquitous and integral part in our daily lives, which can be seen almost everywhere in industry, hospitals, military, etc. To provide remote access and control, usually robots are connected to local network or to the Internet through WiFi or Ethernet. As such, it is of great importance and of a critical mission to maintain the safety and the security access of such robots. Security threats may result in completely preventing the access and control of the robot. The consequences of this may be catastrophic and may cause an immediate physical damage to the robot. This paper aims to present a security risk assessment of the well-known PeopleBot; a mobile robot platform from Adept MobileRobots Company. Initially, we thoroughly examined security threats related to remote accessing the PeopleBot robot. We conducted an impact-oriented analysis approach on the wireless communication medium; the main method considered to remotely access the PeopleBot robot. Numerous experiments using SSH and server-client applications were conducted, and they demonstrated that certain attacks result in denying remote access service to the PeopleBot robot. Consequently and dangerously the robot becomes unavailable. Finally, we suggested one possible mitigation and provided useful conclusions to raise awareness of possible security threats on the robotic systems; especially when the robots are involved in critical missions or applications.