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2019-06-17
Miedl, Philipp, Thiele, Lothar.  2018.  The Security Risks of Power Measurements in Multicores. Proceedings of the 33rd Annual ACM Symposium on Applied Computing. :1585-1592.
Two of the main goals of power management in modern multicore processors are reducing the average power dissipation and delivering the maximum performance up to the physical limits of the system, when demanded. To achieve these goals, hardware manufacturers and operating system providers include sophisticated power and performance management systems, which require detailed information about the current processor state. For example, Intel processors offer the possibility to measure the power dissipation of the processor. In this work, we are evaluating whether such power measurements can be used to establish a covert channel between two isolated applications on the same system; the power covert channel. We present a detailed theoretical and experimental evaluation of the power covert channel on two platforms based on Intel processors. Our theoretical analysis is based on detailed modelling and allows us to derive a channel capacity bound for each platform. Moreover, we conduct an extensive experimental study under controlled, yet realistic, conditions. Our study shows, that the platform dependent channel capacities are in the order of 2000 bps and that it is possible to achieve throughputs of up to 1000 bps with a bit error probability of less than 15%, using a simple implementation. This illustrates the potential of leaking sensitive information and breaking a systems security framework using a covert channel based on power measurements.
Borgolte, Kevin, Fiebig, Tobias, Hao, Shuang, Kruegel, Christopher, Vigna, Giovanni.  2018.  Cloud Strife: Mitigating the Security Risks of Domain-Validated Certificates. Proceedings of the Applied Networking Research Workshop. :4-4.
Infrastructure-as-a-Service (IaaS), more generally the "cloud," changed the landscape of system operations on the Internet. Clouds' elasticity allow operators to rapidly allocate and use resources as needed, from virtual machines, to storage, to IP addresses, which is what made clouds popular. We show that the dynamic component paired with developments in trust-based ecosystems (e.g., TLS certificates) creates so far unknown attacks. We demonstrate that it is practical to allocate IP addresses to which stale DNS records point. Considering the ubiquity of domain validation in trust ecosystems, like TLS, an attacker can then obtain a valid and trusted certificate. The attacker can then impersonate the service, exploit residual trust for phishing, or might even distribute malicious code. Even worse, an aggressive attacker could succeed in less than 70 seconds, well below common time-to-live (TTL) for DNS. In turn, she could exploit normal service migrations to obtain a valid certificate, and, worse, she might not be bound by DNS records being (temporarily) stale. We introduce a new authentication method for trust-based domain validation, like IETF's automated certificate management environment (ACME), that mitigates staleness issues without incurring additional certificate requester effort by incorporating the existing trust of a name into the validation process. Based on previously published work [1]. [1] Kevin Borgolte, Tobias Fiebig, Shuang Hao, Christopher Kruegel, Giovanni Vigna. February 2018. Cloud Strife: Mitigating the Security Risks of Domain-Validated Certificates. In Proceedings of the 25th Network and Distributed Systems Security Symposium (NDSS '18). Internet Society (ISOC). DOI: 10.14722/ndss.2018.23327. URL: https://doi.org/10.14722/nd
Frey, Sylvain, Rashid, Awais, Anthonysamy, Pauline, Pinto-Albuquerque, Maria, Naqvi, Syed Asad.  2018.  The Good, the Bad and the Ugly: A Study of Security Decisions in a Cyber-Physical Systems Game. Proceedings of the 40th International Conference on Software Engineering. :496-496.
Motivation: The security of any system is a direct consequence of stakeholders' decisions regarding security requirements. Such decisions are taken with varying degrees of expertise, and little is currently understood about how various demographics - security experts, general computer scientists, managers - approach security decisions and the strategies that underpin those decisions. What are the typical decision patterns, the consequences of such patterns and their impact on the security of the system in question? Nor is there any substantial understanding of how the strategies and decision patterns of these different groups contrast. Is security expertise necessarily an advantage when making security decisions in a given context? Answers to these questions are key to understanding the "how" and "why" behind security decision processes. The Game: In this talk1, we present a tabletop game: Decisions and Disruptions (D-D)2 that tasks a group of players with managing the security of a small utility company while facing a variety of threats. The game is kept short - 2 hours - and simple enough to be played without prior training. A cyber-physical infrastructure, depicted through a Lego\textregistered board, makes the game easy to understand and accessible to players from varying backgrounds and security expertise, without being too trivial a setting for security experts. Key insights: We played D-D with 43 players divided into homogeneous groups: 4 groups of security experts, 4 groups of nontechnical managers and 4 groups of general computer scientists. • Strategies: Security experts had a strong interest in advanced technological solutions and tended to neglect intelligence gathering, to their own detriment. Managers, too, were technology-driven and focused on data protection while neglecting human factors more than other groups. Computer scientists tended to balance human factors and intelligence gathering with technical solutions, and achieved the best results of the three demographics. • Decision Processes: Technical experience significantly changes the way players think. Teams with little technical experience had shallow, intuition-driven discussions with few concrete arguments. Technical teams, and the most experienced in particular, had much richer debates, driven by concrete scenarios, anecdotes from experience, and procedural thinking. Security experts showed a high confidence in their decisions - despite some of them having bad consequences - while the other groups tended to doubt their own skills - even when they were playing good games. • Patterns: A number of characteristic plays were identified, some good (balance between priorities, open-mindedness, and adapting strategies based on inputs that challenge one's pre-conceptions), some bad (excessive focus on particular issues, confidence in charismatic leaders), some ugly ("tunnel vision" syndrome by over-confident players). These patterns are documented in the full paper - showing the virtue of the positive ones, discouraging the negative ones, and inviting the readers to do their own introspection. Conclusion: Beyond the analysis of the security decisions of the three demographics, there is a definite educational and awareness-raising aspect to D-D (as noted consistently by players in all our subject groups). Game boxes will be brought to the conference for demonstration purposes, and the audience will be invited to experiment with D-D themselves, make their own decisions, and reflect on their own perception of security.
Sion, Laurens, Yskout, Koen, Van Landuyt, Dimitri, Joosen, Wouter.  2018.  Risk-Based Design Security Analysis. Proceedings of the 1st International Workshop on Security Awareness from Design to Deployment. :11-18.
Implementing security by design in practice often involves the application of threat modeling to elicit security threats and to aid designers in focusing efforts on the most stringent problems first. Existing threat modeling methodologies are capable of generating lots of threats, yet they lack even basic support to triage these threats, except for relying on the expertise and manual assessment by the threat modeler. Since the essence of creating a secure design is to minimize associated risk (and countermeasure costs), risk analysis approaches offer a very compelling solution to this problem. By combining risk analysis and threat modeling, elicited threats in a design can be enriched with risk analysis information in order to provide support in triaging and prioritizing threats and focusing security efforts on the high-risk threats. It requires the following inputs: the asset values, the strengths of countermeasures, and an attacker model. In his paper, we provide an integrated threat elicitation and risk analysis approach, implemented in a threat modeling tool prototype, and evaluate it using a real-world application, namely the SecureDrop whistleblower submission system. We show that the security measures implemented in SecureDrop indeed correspond to the high-risk threats identified by our approach. Therefore, the risk-based security analysis provides useful guidance on focusing security efforts on the most important problems first.
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.
Marshall, Allen, Jahan, Sharmin, Gamble, Rose.  2018.  Toward Evaluating the Impact of Self-Adaptation on Security Control Certification. Proceedings of the 13th International Conference on Software Engineering for Adaptive and Self-Managing Systems. :149-160.
Certifying security controls is required for information systems that are either federally maintained or maintained by a US government contractor. As described in the NIST SP800-53, certified and accredited information systems are deployed with an acceptable security threat risk. Self-adaptive information systems that allow functional and decision-making changes to be dynamically configured at runtime may violate security controls increasing the risk of security threat to the system. Methods are needed to formalize the process of certification for security controls by expressing and verifying the functional and non-functional requirements to determine what risks are introduced through self-adaptation. We formally express the existence and behavior requirements of the mechanisms needed to guarantee the security controls' effectiveness using audit controls on program example. To reason over the risk of security control compliance given runtime self-adaptations, we use the KIV theorem prover on the functional requirements, extracting the verification concerns and workflow associated with the proof process. We augment the MAPE-K control loop planner with knowledge of the mechanisms that satisfy the existence criteria expressed by the security controls. We compare self-adaptive plans to assess their risk of security control violation prior to plan deployment.
Goman, Maksim.  2018.  Towards Unambiguous IT Risk Definition. Proceedings of the Central European Cybersecurity Conference 2018. :15:1-15:6.
The paper addresses the fundamental methodological problem of risk analysis and control in information technology (IT) – the definition of risk as a subject of interest. Based on analysis of many risk concepts, we provide a consistent definition that describes the phenomenon. The proposed terminology is sound in terms of system analysis principles and applicable to practical use in risk assessment and control. Implication to risk assessment methods were summarized.
Van Rompay, Cédric, Molva, Refik, Önen, Melek.  2018.  Secure and Scalable Multi-User Searchable Encryption. Proceedings of the 6th International Workshop on Security in Cloud Computing. :15–25.
By allowing a large number of users to behave as readers or writers, Multi-User Searchable Encryption (MUSE) raises new security and performance challenges beyond the typical requirements of Symmetric Searchable Encryption (SSE). In this paper we identify two core mandatory requirements of MUSE protocols being privacy in face of users colluding with the CSP and low complexity for the users, pointing that no existing MUSE protocol satisfies these two requirements at the same time. We then come up with the first MUSE protocol that satisfies both of them. The design of the protocol also includes new constructions for a secure variant of Bloom Filters (BFs) and multi-query Oblivious Transfer (OT).
Yang, Lishan, Cherkasova, Ludmila, Badgujar, Rajeev, Blancaflor, Jack, Konde, Rahul, Mills, Jason, Smirni, Evgenia.  2018.  Evaluating Scalability and Performance of a Security Management Solution in Large Virtualized Environments. Proceedings of the 2018 ACM/SPEC International Conference on Performance Engineering. :168–175.
Virtualized infrastructure is a key capability of modern enterprise data centers and cloud computing, enabling a more agile and dynamic IT infrastructure with fast IT provisioning, simplified, automated management, and flexible resource allocation to handle a broad set of workloads. However, at the same time, virtualization introduces new challenges, since securing virtual servers is more difficult than physical machines. HyTrust Inc. has developed an innovative security solution, called HyTrust Cloud Control (HTCC), to mitigate risks associated with virtualization and cloud technologies. HTCC is a virtual appliance deployed as a transparent proxy in front of a VMware-based virtualized environment. Since HTCC serves as a gateway to a customer virtualized environment, it is important to carefully assess its performance and scalability as well as provide its accurate resource sizing. In this work, we introduce a novel approach for accomplishing this goal. First, we describe a special framework, based on a nested virtualization technique, which enables the creation and deployment of a large scale virtualized environment (with 30,000 VMs) using a limited number of physical servers (4 servers in our experiments). Second, we introduce a design and implementation of a novel, extensible benchmark, called HT-vmbench, that allows to mimic the session-based activities of different system administrators and users in virtualized environments. The benchmark is implemented using VMware Web Service SDK. By executing HT-vmbench in the emulated large-scale virtualized environments, we can support an efficient performance assessment of management and security solutions (such as HTCC), their overhead, and provide capacity planning rules and resource sizing recommendations.
Gu, R., Zhang, X., Yu, L., Zhang, J..  2018.  Enhancing Security and Scalability in Software Defined LTE Core Networks. 2018 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/ 12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE). :837–842.
The rapid development of mobile networks has revolutionized the way of accessing the Internet. The exponential growth of mobile subscribers, devices and various applications frequently brings about excessive traffic in mobile networks. The demand for higher data rates, lower latency and seamless handover further drive the demand for the improved mobile network design. However, traditional methods can no longer offer cost-efficient solutions for better user quality of experience with fast time-to-market. Recent work adopts SDN in LTE core networks to meet the requirement. In these software defined LTE core networks, scalability and security become important design issues that must be considered seriously. In this paper, we propose a scalable channel security scheme for the software defined LTE core network. It applies the VxLAN for scalable tunnel establishment and MACsec for security enhancement. According to our evaluation, the proposed scheme not only enhances the security of the channel communication between different network components, but also improves the flexibility and scalability of the core network with little performance penalty. Moreover, it can also shed light on the design of the next generation cellular network.
Shif, L., Wang, F., Lung, C..  2018.  Improvement of security and scalability for IoT network using SD-VPN. NOMS 2018 - 2018 IEEE/IFIP Network Operations and Management Symposium. :1–5.
The growing interest in the smart device/home/city has resulted in increasing popularity of Internet of Things (IoT) deployment. However, due to the open and heterogeneous nature of IoT networks, there are various challenges to deploy an IoT network, among which security and scalability are the top two to be addressed. To improve the security and scalability for IoT networks, we propose a Software-Defined Virtual Private Network (SD-VPN) solution, in which each IoT application is allocated with its own overlay VPN. The VPN tunnels used in this paper are VxLAN based tunnels and we propose to use the SDN controller to push the flow table of each VPN to the related OpenvSwitch via the OpenFlow protocol. The SD-VPN solution can improve the security of an IoT network by separating the VPN traffic and utilizing service chaining. Meanwhile, it also improves the scalability by its overlay VPN nature and the VxLAN technology.
Blanc, Gregory, Kheir, Nizar, Ayed, Dhouha, Lefebvre, Vincent, de Oca, Edgardo Montes, Bisson, Pascal.  2018.  Towards a 5G Security Architecture: Articulating Software-Defined Security and Security As a Service. Proceedings of the 13th International Conference on Availability, Reliability and Security. :47:1–47:8.
5G is envisioned as a transformation of the communications architecture towards multi-tenant, scalable and flexible infrastructure, which heavily relies on virtualised network functions and programmable networks. In particular, orchestration will advance one step further in blending both compute and data resources, usually dedicated to virtualisation technologies, and network resources into so-called slices. Although 5G security is being developed in current working groups, slice security is seldom addressed. In this work, we propose to integrate security in the slice life cycle, impacting its management and orchestration that relies on the virtualization/softwarisation infrastructure. The proposed security architecture connects the demands specified by the tenants through as-a-service mechanisms with built-in security functions relying on the ability to combine enforcement and monitoring functions within the software-defined network infrastructure. The architecture exhibits desirable properties such as isolating slices down to the hardware resources or monitoring service-level performance.
Noroozi, Hamid, Khodaei, Mohammad, Papadimitratos, Panos.  2018.  VPKIaaS: A Highly-Available and Dynamically-Scalable Vehicular Public-Key Infrastructure. Proceedings of the 11th ACM Conference on Security & Privacy in Wireless and Mobile Networks. :302–304.
The central building block of secure and privacy-preserving Vehicular Communication (VC) systems is a Vehicular Public-Key Infrastructure (VPKI), which provides vehicles with multiple anonymized credentials, termed pseudonyms. These pseudonyms are used to ensure message authenticity and integrity while preserving vehicle (and thus passenger) privacy. In the light of emerging large-scale multi-domain VC environments, the efficiency of the VPKI and, more broadly, its scalability are paramount. In this extended abstract, we leverage the state-of-the-art VPKI system and enhance its functionality towards a highly-available and dynamically-scalable design; this ensures that the system remains operational in the presence of benign failures or any resource depletion attack, and that it dynamically scales out, or possibly scales in, according to the requests' arrival rate. Our full-blown implementation on the Google Cloud Platform shows that deploying a VPKI for a large-scale scenario can be cost-effective, while efficiently issuing pseudonyms for the requesters.
Cao, Gang, Chen, Chen, Jiang, Min.  2018.  A Scalable and Flexible Multi-User Semi-Quantum Secret Sharing. Proceedings of the 2Nd International Conference on Telecommunications and Communication Engineering. :28–32.
In this letter, we proposed a novel scheme for the realization of scalable and flexible semi-quantum secret sharing between a boss and multiple dynamic agent groups. In our scheme, the boss Alice can not only distribute her secret messages to multiple users, but also can dynamically adjust the number of users and user groups based on the actual situation. Furthermore, security analysis demonstrates that our protocol is secure against both external attack and participant attack. Compared with previous schemes, our protocol is more flexible and practical. In addition, since our protocol involving only single qubit measurement that greatly weakens the hardware requirements of each user.
Rouhani, Bita Darvish, Riazi, M. Sadegh, Koushanfar, Farinaz.  2018.  Deepsecure: Scalable Provably-secure Deep Learning. Proceedings of the 55th Annual Design Automation Conference. :2:1–2:6.
This paper presents DeepSecure, the an scalable and provably secure Deep Learning (DL) framework that is built upon automated design, efficient logic synthesis, and optimization methodologies. DeepSecure targets scenarios in which neither of the involved parties including the cloud servers that hold the DL model parameters or the delegating clients who own the data is willing to reveal their information. Our framework is the first to empower accurate and scalable DL analysis of data generated by distributed clients without sacrificing the security to maintain efficiency. The secure DL computation in DeepSecure is performed using Yao's Garbled Circuit (GC) protocol. We devise GC-optimized realization of various components used in DL. Our optimized implementation achieves up to 58-fold higher throughput per sample compared with the best prior solution. In addition to the optimized GC realization, we introduce a set of novel low-overhead pre-processing techniques which further reduce the GC overall runtime in the context of DL. Our extensive evaluations demonstrate up to two orders-of-magnitude additional runtime improvement achieved as a result of our pre-processing methodology.
Kuhnle, Alan, Crawford, Victoria G., Thai, My T..  2018.  Network Resilience and the Length-Bounded Multicut Problem: Reaching the Dynamic Billion-Scale with Guarantees. Abstracts of the 2018 ACM International Conference on Measurement and Modeling of Computer Systems. :81–83.
Motivated by networked systems in which the functionality of the network depends on vertices in the network being within a bounded distance T of each other, we study the length-bounded multicut problem: given a set of pairs, find a minimum-size set of edges whose removal ensures the distance between each pair exceeds T . We introduce the first algorithms for this problem capable of scaling to massive networks with billions of edges and nodes: three highly scalable algorithms with worst-case performance ratios. Furthermore, one of our algorithms is fully dynamic, capable of updating its solution upon incremental vertex / edge additions or removals from the network while maintaining its performance ratio. Finally, we show that unless NP ⊆ BPP, there is no polynomial-time, approximation algorithm with performance ratio better than Omega (T), which matches the ratio of our dynamic algorithm up to a constant factor.
Sasan, Avesta, Zu, Qi, Wamg, Yanzhi, Seo, Jae-sun, Mohsenin, Tinoosh.  2018.  Low Power and Trusted Machine Learning. Proceedings of the 2018 on Great Lakes Symposium on VLSI. :515–515.
In this special discussion session on machine learning, the panel members discuss various issues related to building secure and low power neuromorphic systems. The security of neuromorphic systems may be discussed in term of the reliability of the model, trust in the model, and security of the underlying hardware. The low power aspect of neuromorphic computing systems may be discussed in terms of adaptation of new devices and technologies, the adaptation of new computational models, development of heterogeneous computing frameworks, or dedicated engines for processing neuromorphic models. This session may include discussion on the design space of such supporting hardware, exploring tradeoffs between power/energy, security, scalability, hardware area, performance, and accuracy.
Garae, J., Ko, R. K. L., Apperley, M..  2018.  A Full-Scale Security Visualization Effectiveness Measurement and Presentation Approach. 2018 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/ 12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE). :639–650.
What makes a security visualization effective? How do we measure visualization effectiveness in the context of investigating, analyzing, understanding and reporting cyber security incidents? Identifying and understanding cyber-attacks are critical for decision making - not just at the technical level, but also the management and policy-making levels. Our research studied both questions and extends our Security Visualization Effectiveness Measurement (SvEm) framework by providing a full-scale effectiveness approach for both theoretical and user-centric visualization techniques. Our framework facilitates effectiveness through interactive three-dimensional visualization to enhance both single and multi-user collaboration. We investigated effectiveness metrics including (1) visual clarity, (2) visibility, (3) distortion rates and (4) user response (viewing) times. The SvEm framework key components are: (1) mobile display dimension and resolution factor, (2) security incident entities, (3) user cognition activators and alerts, (4) threat scoring system, (5) working memory load and (6) color usage management. To evaluate our full-scale security visualization effectiveness framework, we developed VisualProgger - a real-time security visualization application (web and mobile) visualizing data provenance changes in SvEm use cases. Finally, the SvEm visualizations aims to gain the users' attention span by ensuring a consistency in the viewer's cognitive load, while increasing the viewer's working memory load. In return, users have high potential to gain security insights in security visualization. Our evaluation shows that viewers perform better with prior knowledge (working memory load) of security events and that circular visualization designs attract and maintain the viewer's attention span. These discoveries revealed research directions for future work relating to measurement of security visualization effectiveness.
Martinelli, Fabio, Michailidou, Christina, Mori, Paolo, Saracino, Andrea.  2018.  Too Long, Did Not Enforce: A Qualitative Hierarchical Risk-Aware Data Usage Control Model for Complex Policies in Distributed Environments. Proceedings of the 4th ACM Workshop on Cyber-Physical System Security. :27–37.

Distributed environments such as Internet of Things, have an increasing need of introducing access and usage control mechanisms, to manage the rights to perform specific operations and regulate the access to the plethora of information daily generated by these devices. Defining policies which are specific to these distributed environments could be a challenging and tedious task, mainly due to the large set of attributes that should be considered, hence the upcoming of unforeseen conflicts or unconsidered conditions. In this paper we propose a qualitative risk-based usage control model, aimed at enabling a framework where is possible to define and enforce policies at different levels of granularity. In particular, the proposed framework exploits the Analytic Hierarchy Process (AHP) to coalesce the risk value assigned to different attributes in relation to a specific operation, in a single risk value, to be used as unique attribute of usage control policies. Two sets of experiments that show the benefits both in policy definition and in performance, validate the proposed model, demonstrating the equivalence of enforcement among standard policies and the derived single-attributed policies.

Yang, J., Jeong, J. P..  2018.  An Automata-based Security Policy Translation for Network Security Functions. 2018 International Conference on Information and Communication Technology Convergence (ICTC). :268–272.
This paper proposes the design of a security policy translator in Interface to Network Security Functions (I2NSF) framework. Also, this paper shows the benefits of designing security policy translations. I2NSF is an architecture for providing various Network Security Functions (NSFs) to users. I2NSF user should be able to use NSF even if user has no overall knowledge of NSFs. Generally, policies which are generated by I2NSF user contain abstract data because users do not consider the attributes of NSFs when creating policies. Therefore, the I2NSF framework requires a translator that automatically finds the NSFs which is required for policy when Security Controller receives a security policy from the user and translates it for selected NSFs. We satisfied the above requirements by modularizing the translator through Automata theory.
Zheng, Jianjun, Siami Namin, Akbar.  2018.  A Markov Decision Process to Determine Optimal Policies in Moving Target. Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security. :2321–2323.
Moving Target Defense (MTD) has been introduced as a new game changer strategy in cybersecurity to strengthen defenders and conversely weaken adversaries. The successful implementation of an MTD system can be influenced by several factors including the effectiveness of the employed technique, the deployment strategy, the cost of the MTD implementation, and the impact from the enforced security policies. Several efforts have been spent on introducing various forms of MTD techniques. However, insufficient research work has been conducted on cost and policy analysis and more importantly the selection of these policies in an MTD-based setting. This poster paper proposes a Markov Decision Process (MDP) modeling-based approach to analyze security policies and further select optimal policies for moving target defense implementation and deployment. The adapted value iteration method would solve the Bellman Optimality Equation for optimal policy selection for each state of the system. The results of some simulations indicate that such modeling can be used to analyze the impact of costs of possible actions towards the optimal policies.
Krahn, Robert, Trach, Bohdan, Vahldiek-Oberwagner, Anjo, Knauth, Thomas, Bhatotia, Pramod, Fetzer, Christof.  2018.  Pesos: Policy Enhanced Secure Object Store. Proceedings of the Thirteenth EuroSys Conference. :25:1–25:17.
Third-party storage services pose the risk of integrity and confidentiality violations as the current storage policy enforcement mechanisms are spread across many layers in the system stack. To mitigate these security vulnerabilities, we present the design and implementation of Pesos, a Policy Enhanced Secure Object Store (Pesos) for untrusted third-party storage providers. Pesos allows clients to specify per-object security policies, concisely and separately from the storage stack, and enforces these policies by securely mediating the I/O in the persistence layer through a single unified enforcement layer. More broadly, Pesos exposes a rich set of storage policies ensuring the integrity, confidentiality, and access accounting for data storage through a declarative policy language. Pesos enforces these policies on untrusted commodity platforms by leveraging a combination of two trusted computing technologies: Intel SGX for trusted execution environment (TEE) and Kinetic Open Storage for trusted storage. We have implemented Pesos as a fully-functional storage system supporting many useful end-to-end storage features, and a range of effective performance optimizations. We evaluated Pesos using a range of micro-benchmarks, and real-world use cases. Our evaluation shows that Pesos incurs reasonable performance overheads for the enforcement of policies while keeping the trusted computing base (TCB) small.
Nguyen, Phu H., Phung, Phu H., Truong, Hong-Linh.  2018.  A Security Policy Enforcement Framework for Controlling IoT Tenant Applications in the Edge. Proceedings of the 8th International Conference on the Internet of Things. :4:1–4:8.
In the context of edge computing, IoT-as-a-Service (IoTaaS) with IoT data hubs and execution services allow IoT tenant applications (apps) to be executed next to IoT devices, enabling edge analytics and controls. However, this brings up new security challenges on controlling tenant apps in IoTaaS, whilst the great potential of IoTaaS can only be realized by flexible security mechanisms to govern such applications. In this paper, we propose a Model-Driven Security policy enforcement framework, named MDSIoT, for IoT tenant apps deployed in edge servers. This framework allows execution policies specified at the model level and then transformed into the code that can be deployed for policy enforcement at runtime. Moreover, our approach supports for the interoperability of IoT tenant apps when deployed in the edge to access IoTaaS services. The interoperability is enabled by an intermediate proxy layer (gatekeeper) that abstracts underlying communication protocols to the different IoTaaS services from IoT tenant apps. Therefore, our approach supports different IoT tenant apps to be deployed and controlled automatically, independently from their technologies, e.g. programming languages. We have developed a proof-of-concept of the proposed gatekeepers based on ThingML, derived from execution policies. Thanks to the ThingML tool, we can generate platform-specific code of gatekeepers that can be deployed in the edge for controlling IoT tenant apps based on the execution policies.
Pupo, Angel Luis Scull, Nicolay, Jens, Boix, Elisa Gonzalez.  2018.  GUARDIA: Specification and Enforcement of Javascript Security Policies Without VM Modifications. Proceedings of the 15th International Conference on Managed Languages & Runtimes. :17:1–17:15.
The complex architecture of browser technologies and dynamic characteristics of JavaScript make it difficult to ensure security in client-side web applications. Browser-level security policies alone are not sufficient because it is difficult to apply them correctly and they can be bypassed. As a result, they need to be completed by application-level security policies. In this paper, we survey existing solutions for specifying and enforcing application-level security policies for client-side web applications, and distill a number of desirable features. Based on these features we developed Guardia, a framework for declaratively specifying and dynamically enforcing application-level security policies for JavaScript web applications without requiring VM modifications. We describe Guardia enforcement mechanism by means of JavaScript reflection with respect to three important security properties (transparency, tamper-proofness, and completeness). We also use Guardia to specify and deploy 12 access control policies discussed in related work in three experimental applications that are representative of real-world applications. Our experiments indicate that Guardia is correct, transparent, and tamper-proof, while only incurring a reasonable runtime overhead.
Verma, Dinesh, Calo, Seraphin, Cirincione, Greg.  2018.  Distributed AI and Security Issues in Federated Environments. Proceedings of the Workshop Program of the 19th International Conference on Distributed Computing and Networking. :4:1–4:6.
Many real-world IoT solutions have to be implemented in a federated environment, which are environments where many different administrative organizations are involved in different parts of the solution. Smarter Cities, Federated Governance, International Trade and Military Coalition Operations are examples of federated environments. As end devices become more capable and intelligent, learning from their environment, and adapting on their own, they expose new types of security vulnerabilities and present an increased attack surface. A distributed AI approach can help mitigate many of the security problems that one may encounter in such federated environments. In this paper, we outline some of the scenarios in which we need to rethink security issues as devices become more intelligent, and discuss how distributed AI techniques can be used to reduce the security exposures in such environments.