Visible to the public Biblio

Found 197 results

Filters: Keyword is policy  [Clear All Filters]
Fiebig, T..  2020.  How to stop crashing more than twice: A Clean-Slate Governance Approach to IT Security. 2020 IEEE European Symposium on Security and Privacy Workshops (EuroS PW). :67—74.

"Moving fast, and breaking things", instead of "being safe and secure", is the credo of the IT industry. However, if we look at the wide societal impact of IT security incidents in the past years, it seems like it is no longer sustainable. Just like in the case of Equifax, people simply forget updates, just like in the case of Maersk, companies do not use sufficient network segmentation. Security certification does not seem to help with this issue. After all, Equifax was IS027001 compliant.In this paper, we take a look at how we handle and (do not) learn from security incidents in IT security. We do this by comparing IT security incidents to early and later aviation safety. We find interesting parallels to early aviation safety, and outline the governance levers that could make the world of IT more secure, which were already successful in making flying the most secure way of transportation.

Wang, X., Herwono, I., Cerbo, F. D., Kearney, P., Shackleton, M..  2018.  Enabling Cyber Security Data Sharing for Large-scale Enterprises Using Managed Security Services. 2018 IEEE Conference on Communications and Network Security (CNS). :1—7.
Large enterprises and organizations from both private and public sectors typically outsource a platform solution, as part of the Managed Security Services (MSSs), from 3rd party providers (MSSPs) to monitor and analyze their data containing cyber security information. Sharing such data among these large entities is believed to improve their effectiveness and efficiency at tackling cybercrimes, via improved analytics and insights. However, MSS platform customers currently are not able or not willing to share data among themselves because of multiple reasons, including privacy and confidentiality concerns, even when they are using the same MSS platform. Therefore any proposed mechanism or technique to address such a challenge need to ensure that sharing is achieved in a secure and controlled way. In this paper, we propose a new architecture and use case driven designs to enable confidential, flexible and collaborative data sharing among such organizations using the same MSS platform. MSS platform is a complex environment where different stakeholders, including authorized MSSP personnel and customers' own users, have access to the same platform but with different types of rights and tasks. Hence we make every effort to improve the usability of the platform supporting sharing while keeping the existing rights and tasks intact. As an innovative and pioneering attempt to address the challenge of data sharing in the MSS platform, we hope to encourage further work to follow so that confidential and collaborative sharing eventually happens among MSS platform customers.
Du, Jia, Wang, Zhe, Yang, Junqiang, Song, Xiaofeng.  2019.  Research on Cognitive Linkage of Network Security Equipment. 2019 International Conference on Robots Intelligent System (ICRIS). :296–298.
To solve the problems of weak linkage ability and low intellectualization of strategy allocation in existing network security devices, a new method of cognitive linkage of network security equipment is proposed by learning from human brain. Firstly, the basic connotation and cognitive cycle of cognitive linkage are expounded. Secondly, the main functions of cognitive linkage are clarified. Finally, the cognitive linkage system model is constructed, and the information process flow of cognitive linkage is described. Cognitive linkage of network security equipment provides a new way to effectively enhance the overall protection capability of network security equipment.
Bradley, Cerys, Stringhini, Gianluca.  2019.  A Qualitative Evaluation of Two Different Law Enforcement Approaches on Dark Net Markets. 2019 IEEE European Symposium on Security and Privacy Workshops (EuroS PW). :453—463.

This paper presents the results of a qualitative study on discussions about two major law enforcement interventions against Dark Net Market (DNM) users extracted from relevant Reddit forums. We assess the impact of Operation Hyperion and Operation Bayonet (combined with the closure of the site Hansa) by analyzing posts and comments made by users of two Reddit forums created for the discussion of Dark Net Markets. The operations are compared in terms of the size of the discussions, the consequences recorded, and the opinions shared by forum users. We find that Operation Bayonet generated a higher number of discussions on Reddit, and from the qualitative analysis of such discussions it appears that this operation also had a greater impact on the DNM ecosystem.

Akhtar, Nabeel, Matta, Ibrahim, Raza, Ali, Wang, Yuefeng.  2018.  EL-SEC: ELastic Management of Security Applications on Virtualized Infrastructure. IEEE INFOCOM 2018 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS). :778-783.

The concept of Virtualized Network Functions (VNFs) aims to move Network Functions (NFs) out of dedicated hardware devices into software that runs on commodity hardware. A single NF consists of multiple VNF instances, usually running on virtual machines in a cloud infrastructure. The elastic management of an NF refers to load management across the VNF instances and the autonomic scaling of the number of VNF instances as the load on the NF changes. In this paper, we present EL-SEC, an autonomic framework to elastically manage security NFs on a virtualized infrastructure. As a use case, we deploy the Snort Intrusion Detection System as the NF on the GENI testbed. Concepts from control theory are used to create an Elastic Manager, which implements various controllers - in this paper, Proportional Integral (PI) and Proportional Integral Derivative (PID) - to direct traffic across the VNF Snort instances by monitoring the current load. RINA (a clean-slate Recursive InterNetwork Architecture) is used to build a distributed application that monitors load and collects Snort alerts, which are processed by the Elastic Manager and an Attack Analyzer, respectively. Software Defined Networking (SDN) is used to steer traffic through the VNF instances, and to block attack traffic. Our results show that virtualized security NFs can be easily deployed using our EL-SEC framework. With the help of real-time graphs, we show that PI and PID controllers can be used to easily scale the system, which leads to quicker detection of attacks.

Bertino, Elisa, Nabeel, Mohamed.  2018.  Securing Named Data Networks: Challenges and the Way Forward. Proceedings of the 23Nd ACM on Symposium on Access Control Models and Technologies. :51-59.

Despite decades of research on the Internet security, we constantly hear about mega data breaches and malware infections affecting hundreds of millions of hosts. The key reason is that the current threat model of the Internet relies on two assumptions that no longer hold true: (1) Web servers, hosting the content, are secure, (2) each Internet connection starts from the original content provider and terminates at the content consumer. Internet security is today merely patched on top of the TCP/IP protocol stack. In order to achieve comprehensive security for the Internet, we believe that a clean-slate approach must be adopted where a content based security model is employed. Named Data Networking (NDN) is a step in this direction which is envisioned to be the next generation Internet architecture based on a content centric communication model. NDN is currently being designed with security as a key requirement, and thus to support content integrity, authenticity, confidentiality and privacy. However, in order to meet such a requirement, one needs to overcome several challenges, especially in either large operational environments or resource constrained networks. In this paper, we explore the security challenges in achieving comprehensive content security in NDN and propose a research agenda to address some of the challenges.

Hanford, Nathan, Ahuja, Vishal, Farrens, Matthew K., Tierney, Brian, Ghosal, Dipak.  2018.  A Survey of End-System Optimizations for High-Speed Networks. ACM Comput. Surv.. 51:54:1-54:36.

The gap is widening between the processor clock speed of end-system architectures and network throughput capabilities. It is now physically possible to provide single-flow throughput of speeds up to 100 Gbps, and 400 Gbps will soon be possible. Most current research into high-speed data networking focuses on managing expanding network capabilities within datacenter Local Area Networks (LANs) or efficiently multiplexing millions of relatively small flows through a Wide Area Network (WAN). However, datacenter hyper-convergence places high-throughput networking workloads on general-purpose hardware, and distributed High-Performance Computing (HPC) applications require time-sensitive, high-throughput end-to-end flows (also referred to as ``elephant flows'') to occur over WANs. For these applications, the bottleneck is often the end-system and not the intervening network. Since the problem of the end-system bottleneck was uncovered, many techniques have been developed which address this mismatch with varying degrees of effectiveness. In this survey, we describe the most promising techniques, beginning with network architectures and NIC design, continuing with operating and end-system architectures, and concluding with clean-slate protocol design.

Wilcox, James R., Flanagan, Cormac, Freund, Stephen N..  2018.  VerifiedFT: A Verified, High-Performance Precise Dynamic Race Detector. Proceedings of the 23rd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming. :354-367.

Dynamic data race detectors are valuable tools for testing and validating concurrent software, but to achieve good performance they are typically implemented using sophisticated concurrent algorithms. Thus, they are ironically prone to the exact same kind of concurrency bugs they are designed to detect. To address these problems, we have developed VerifiedFT, a clean slate redesign of the FastTrack race detector [19]. The VerifiedFT analysis provides the same precision guarantee as FastTrack, but is simpler to implement correctly and efficiently, enabling us to mechanically verify an implementation of its core algorithm using CIVL [27]. Moreover, VerifiedFT provides these correctness guarantees without sacrificing any performance over current state-of-the-art (but complex and unverified) FastTrack implementations for Java.

Ott, David E..  2018.  Software Defined Infrastructure: Rethinking Cybersecurity with a More Capable Toolset. SIGOPS Oper. Syst. Rev.. 52:129-133.

In Software Defined Infrastructure (SDI), virtualization techniques are used to decouple applications and higher-level services from their underlying physical compute, storage, and network resources. The approach offers a set of powerful new capabilities (isolation, encapsulation, portability, interposition), including the formation of a software-based, infrastructure-wide control plane for orchestrated management. In this position paper, we identify opportunities for revisiting ongoing cybersecurity challenges using SDI as a powerful new toolset. Benefits of this approach can be broadly utilized in public, private, and hybrid clouds, data centers, enterprise computing, IoT deployments, and more. The discussion motivates the research challenge underlying VMware's partnership with the National Science Foundation to fund novel and foundational research in this area. Known as the NSF/VMware Partnership on Software Defined Infrastructure as a Foundation for Clean-Slate Computing Security (SDI-CSCS), the jointly funded university research program is set to begin in the fall of 2017.

Leißa, Roland, Boesche, Klaas, Hack, Sebastian, Pérard-Gayot, Arsène, Membarth, Richard, Slusallek, Philipp, Müller, André, Schmidt, Bertil.  2018.  AnyDSL: A Partial Evaluation Framework for Programming High-Performance Libraries. Proc. ACM Program. Lang.. 2:119:1-119:30.

This paper advocates programming high-performance code using partial evaluation. We present a clean-slate programming system with a simple, annotation-based, online partial evaluator that operates on a CPS-style intermediate representation. Our system exposes code generation for accelerators (vectorization/parallelization for CPUs and GPUs) via compiler-known higher-order functions that can be subjected to partial evaluation. This way, generic implementations can be instantiated with target-specific code at compile time. In our experimental evaluation we present three extensive case studies from image processing, ray tracing, and genome sequence alignment. We demonstrate that using partial evaluation, we obtain high-performance implementations for CPUs and GPUs from one language and one code base in a generic way. The performance of our codes is mostly within 10%, often closer to the performance of multi man-year, industry-grade, manually-optimized expert codes that are considered to be among the top contenders in their fields.

Sahu, Abhijeet, Goulart, Ana.  2019.  Implementation of a C-UNB Module for NS-3 and Validation for DLMS-COSEM Application Layer Protocol. 2019 IEEE ComSoc International Communications Quality and Reliability Workshop (CQR). :1-6.

The number of sensors and embedded devices in an urban area can be on the order of thousands. New low-power wide area (LPWA) wireless network technologies have been proposed to support this large number of asynchronous, low-bandwidth devices. Among them, the Cooperative UltraNarrowband (C-UNB) is a clean-slate cellular network technology to connect these devices to a remote site or data collection server. C-UNB employs small bandwidth channels, and a lightweight random access protocol. In this paper, a new application is investigated - the use of C-UNB wireless networks to support the Advanced Metering Infrastructure (AMI), in order to facilitate the communication between smart meters and utilities. To this end, we adapted a mathematical model for C-UNB, and implemented a network simulation module in NS-3 to represent C-UNB's physical and medium access control layer. For the application layer, we implemented the DLMS-COSEM protocol, or Device Language Message Specification - Companion Specification for Energy Metering. Details of the simulation module are presented and we conclude that it supports the results of the mathematical model.

Yu, Yiding, Wang, Taotao, Liew, Soung Chang.  2018.  Deep-Reinforcement Learning Multiple Access for Heterogeneous Wireless Networks. 2018 IEEE International Conference on Communications (ICC). :1-7.

This paper investigates the use of deep reinforcement learning (DRL) in the design of a "universal" MAC protocol referred to as Deep-reinforcement Learning Multiple Access (DLMA). The design framework is partially inspired by the vision of DARPA SC2, a 3-year competition whereby competitors are to come up with a clean-slate design that "best share spectrum with any network(s), in any environment, without prior knowledge, leveraging on machine-learning technique". While the scope of DARPA SC2 is broad and involves the redesign of PHY, MAC, and Network layers, this paper's focus is narrower and only involves the MAC design. In particular, we consider the problem of sharing time slots among a multiple of time-slotted networks that adopt different MAC protocols. One of the MAC protocols is DLMA. The other two are TDMA and ALOHA. The DRL agents of DLMA do not know that the other two MAC protocols are TDMA and ALOHA. Yet, by a series of observations of the environment, its own actions, and the rewards - in accordance with the DRL algorithmic framework - a DRL agent can learn the optimal MAC strategy for harmonious co-existence with TDMA and ALOHA nodes. In particular, the use of neural networks in DRL (as opposed to traditional reinforcement learning) allows for fast convergence to optimal solutions and robustness against perturbation in hyper- parameter settings, two essential properties for practical deployment of DLMA in real wireless networks.

Campioni, Lorenzo, Hauge, Mariann, Landmark, Lars, Suri, Niranjan, Tortonesi, Mauro.  2019.  Considerations on the Adoption of Named Data Networking (NDN) in Tactical Environments. 2019 International Conference on Military Communications and Information Systems (ICMCIS). :1-8.

Mobile military networks are uniquely challenging to build and maintain, because of their wireless nature and the unfriendliness of the environment, resulting in unreliable and capacity limited performance. Currently, most tactical networks implement TCP/IP, which was designed for fairly stable, infrastructure-based environments, and requires sophisticated and often application-specific extensions to address the challenges of the communication scenario. Information Centric Networking (ICN) is a clean slate networking approach that does not depend on stable connections to retrieve information and naturally provides support for node mobility and delay/disruption tolerant communications - as a result it is particularly interesting for tactical applications. However, despite ICN seems to offer some structural benefits for tactical environments over TCP/IP, a number of challenges including naming, security, performance tuning, etc., still need to be addressed for practical adoption. This document, prepared within NATO IST-161 RTG, evaluates the effectiveness of Named Data Networking (NDN), the de facto standard implementation of ICN, in the context of tactical edge networks and its potential for adoption.

Ahmed, Abu Shohel, Aura, Tuomas.  2018.  Turning Trust Around: Smart Contract-Assisted Public Key Infrastructure. 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). :104–111.
In past, several Certificate Authority (CA) compromise and subsequent mis-issue of certificate raise the importance of certificate transparency and dynamic trust management for certificates. Certificate Transparency (CT) provides transparency for issued certificates, thus enabling corrective measure for a mis-issued certificate by a CA. However, CT and existing mechanisms cannot convey the dynamic trust state for a certificate. To address this weakness, we propose Smart Contract-assisted PKI (SCP) - a smart contract based PKI extension - to manage dynamic trust network for PKI. SCP enables distributed trust in PKI, provides a protocol for managing dynamic trust, assures trust state of a certificate, and provides a better trust experience for end-users.
Martiny, Karsten, Denker, Grit.  2018.  Expiring Decisions for Stream-based Data Access in a Declarative Privacy Policy Framework. Proceedings of the 2Nd International Workshop on Multimedia Privacy and Security. :71–80.
This paper describes how a privacy policy framework can be extended with timing information to not only decide if requests for data are allowed at a given point in time, but also to decide for how long such permission is granted. Augmenting policy decisions with expiration information eliminates the need to reason about access permissions prior to every individual data access operation. This facilitates the application of privacy policy frameworks to protect multimedia streaming data where repeated re-computations of policy decisions are not a viable option. We show how timing information can be integrated into an existing declarative privacy policy framework. In particular, we discuss how to obtain valid expiration information in the presence of complex sets of policies with potentially interacting policies and varying timing information.
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.
Hu, Xiaohe, Gupta, Arpit, Feamster, Nick, Panda, Aurojit, Shenker, Scott.  2018.  Preserving Privacy at IXPs. Proceedings of the 2Nd Asia-Pacific Workshop on Networking. :43–49.
Autonomous systems (ASes) on the Internet increasingly rely on Internet Exchange Points (IXPs) for peering. A single IXP may interconnect several 100s or 1000s of participants (ASes) all of which might peer with each other through BGP sessions. IXPs have addressed this scaling challenge through the use of route servers. However, route servers require participants to trust the IXP and reveal their policies, a drastic change from the accepted norm where all policies are kept private. In this paper we look at techniques to build route servers which provide the same functionality as existing route servers without requiring participants to reveal their policies thus preserving the status quo and enabling wider adoption of IXPs. Prior work has looked at secure multiparty computation (SMPC) as a means of implementing such route servers however this affects performance and reduces policy flexibility. In this paper we take a different tack and build on trusted execution environments (TEEs) such as Intel SGX to keep policies private and flexible. We present results from an initial route server implementation that runs under Intel SGX and show that our approach has 20x better performance than SMPC based approaches. Furthermore, we demonstrate that the additional privacy provided by our approach comes at minimal cost and our implementation is at worse 2.1x slower than a current route server implementation (and in some situations up to 2x faster).
Norman, Michael D., Koehler, Matthew T.K..  2017.  Cyber Defense As a Complex Adaptive System: A Model-based Approach to Strategic Policy Design. Proceedings of the 2017 International Conference of The Computational Social Science Society of the Americas. :17:1–17:1.
In a world of ever-increasing systems interdependence, effective cybersecurity policy design seems to be one of the most critically understudied elements of our national security strategy. Enterprise cyber technologies are often implemented without much regard to the interactions that occur between humans and the new technology. Furthermore, the interactions that occur between individuals can often have an impact on the newly employed technology as well. Without a rigorous, evidence-based approach to ground an employment strategy and elucidate the emergent organizational needs that will come with the fielding of new cyber capabilities, one is left to speculate on the impact that novel technologies will have on the aggregate functioning of the enterprise. In this paper, we will explore a scenario in which a hypothetical government agency applies a complexity science perspective, supported by agent-based modeling, to more fully understand the impacts of strategic policy decisions. We present a model to explore the socio-technical dynamics of these systems, discuss lessons using this platform, and suggest further research and development.
Silva, B., Sabino, A., Junior, W., Oliveira, E., Júnior, F., Dias, K..  2017.  Performance Evaluation of Cryptography on Middleware-Based Computational Offloading. 2017 VII Brazilian Symposium on Computing Systems Engineering (SBESC). :205–210.
Mobile cloud computing paradigm enables cloud servers to extend the limited hardware resources of mobile devices improving availability and reliability of the services provided. Consequently, private, financial, business and critical data pass through wireless access media exposed to malicious attacks. Mobile cloud infrastructure requires new security mechanisms, at the same time as offloading operations need to maintain the advantages of saving processing and energy of the device. Thus, this paper implements a middleware-based computational offloading with cryptographic algorithms and evaluates two mechanisms (symmetric and asymmetric), to provide the integrity and authenticity of data that a smartphone offloads to mobile cloud servers. Also, the paper discusses the factors that impact on power consumption and performance on smartphones that's run resource-intensive applications.
Rafique, Ansar, Van Landuyt, Dimitri, Reniers, Vincent, Joosen, Wouter.  2017.  Towards Scalable and Dynamic Data Encryption for Multi-tenant SaaS. Proceedings of the Symposium on Applied Computing. :411–416.
Application-level data management middleware solutions are becoming increasingly compelling to deal with the complexity of a multi-cloud or federated cloud storage and multitenant storage architecture. However, these systems typically support traditional data mapping strategies that are created under the assumption of a fixed and rigorous database schema, and mapping data objects while supporting varying data confidentiality requirements therefore leads to fragmentation of data over distributed storage nodes. This introduces performance over-head at the level of individual database transactions and negatively affects the overall scalability. This paper discusses these challenges and highlights the potential of leveraging the data schema flexibility of NoSQL databases to accomplish dynamic and fine-grained data encryption in a more efficient and scalable manner. We illustrate these ideas in the context of an industrial multi-tenant SaaS application.
Razouk, Wissam, Sgandurra, Daniele, Sakurai, Kouichi.  2017.  A New Security Middleware Architecture Based on Fog Computing and Cloud to Support IoT Constrained Devices. Proceedings of the 1st International Conference on Internet of Things and Machine Learning. :35:1–35:8.
The increase of sensitive data in the current Internet of Things (IoT) raises demands of computation, communication and storage capabilities. Indeed, thanks to RFID tags and wireless sensor networks, anything can be part of IoT. As a result, a large amount of data is generated, which is hard for many IoT devices to handle, as many IoT devices are resource-constrained and cannot use the existing standard security protocols. Cloud computing might seem like a convenient solution, since it offers on-demand access to a shared pool of resources such as processors, storage, applications and services. However this comes as a cost, as unnecessary communications not only burden the core network, but also the data center in the cloud. Therefore, considering suitable approaches such as fog computing and security middleware solutions is crucial. In this paper, we propose a novel middleware architecture to solve the above issues, and discuss the generic concept of using fog computing along with cloud in order to achieve a higher security level. Our security middleware acts as a smart gateway as it is meant to pre-process data at the edge of the network. Depending on the received information, data might either be processed and stored locally on fog or sent to the cloud for further processing. Moreover, in our scheme, IoT constrained devices communicate through the proposed middleware, which provide access to more computing power and enhanced capability to perform secure communications. We discuss these concepts in detail, and explain how our proposal is effective to cope with some of the most relevant IoT security challenges.
Gremaud, Pascal, Durand, Arnaud, Pasquier, Jacques.  2017.  A Secure, Privacy-preserving IoT Middleware Using Intel SGX. Proceedings of the Seventh International Conference on the Internet of Things. :22:1–22:2.
With Internet of Things (IoT) middleware solutions moving towards cloud computing, the problems of trust in cloud platforms and data privacy need to be solved. The emergence of Trusted Execution Environments (TEEs) opens new perspectives to increase security in cloud applications. We propose a privacy-preserving IoT middleware, using Intel Software Guard Extensions (SGX) to create a secure system on untrusted platforms. An encrypted index is used as a database and communication with the application is protected using asymmetric encryption. This set of measures allows our system to process events in an orchestration engine without revealing data to the hosting cloud platform.
Peterson, Brad, Humphrey, Alan, Schmidt, John, Berzins, Martin.  2017.  Addressing Global Data Dependencies in Heterogeneous Asynchronous Runtime Systems on GPUs. Proceedings of the Third International Workshop on Extreme Scale Programming Models and Middleware. :1:1–1:8.
Large-scale parallel applications with complex global data dependencies beyond those of reductions pose significant scalability challenges in an asynchronous runtime system. Internodal challenges include identifying the all-to-all communication of data dependencies among the nodes. Intranodal challenges include gathering together these data dependencies into usable data objects while avoiding data duplication. This paper addresses these challenges within the context of a large-scale, industrial coal boiler simulation using the Uintah asynchronous many-task runtime system on GPU architectures. We show significant reduction in time spent analyzing data dependencies through refinements in our dependency search algorithm. Multiple task graphs are used to eliminate subsequent analysis when task graphs change in predictable and repeatable ways. Using a combined data store and task scheduler redesign reduces data dependency duplication ensuring that problems fit within host and GPU memory. These modifications did not require any changes to application code or sweeping changes to the Uintah runtime system. We report results running on the DOE Titan system on 119K CPU cores and 7.5K GPUs simultaneously. Our solutions can be generalized to other task dependency problems with global dependencies among thousands of nodes which must be processed efficiently at large scale.
Van hamme, Tim, Preuveneers, Davy, Joosen, Wouter.  2017.  A Dynamic Decision Fusion Middleware for Trustworthy Context-aware IoT Applications. Proceedings of the 4th Workshop on Middleware and Applications for the Internet of Things. :1–6.

Internet of Things (IoT) devices offer new sources of contextual information, which can be leveraged by applications to make smart decisions. However, due to the decentralized and heterogeneous nature of such devices - each only having a partial view of their surroundings - there is an inherent risk of uncertain, unreliable and inconsistent observations. This is a serious concern for applications making security related decisions, such as context-aware authentication. We propose and evaluate a middleware for IoT that provides trustworthy context for a collaborative authentication use case. It abstracts a dynamic and distributed fusion scheme that extends the Chair-Varshney (CV) optimal decision fusion rule such that it can be used in a highly dynamic IoT environment. We compare performance and cost trade-offs against regular CV. Experimental evaluation demonstrates that our solution outperforms CV with 10% in a highly dynamic IoT environments, with the ability to detect and mitigate unreliable sensors.

Daniels, Wilfried, Hughes, Danny, Ammar, Mahmoud, Crispo, Bruno, Matthys, Nelson, Joosen, Wouter.  2017.  SΜV - the Security Microvisor: A Virtualisation-based Security Middleware for the Internet of Things. Proceedings of the 18th ACM/IFIP/USENIX Middleware Conference: Industrial Track. :36–42.
The Internet of Things (IoT) creates value by connecting digital processes to the physical world using embedded sensors, actuators and wireless networks. The IoT is increasingly intertwined with critical industrial processes, yet contemporary IoT devices offer limited security features, creating a large new attack surface and inhibiting the adoption of IoT technologies. Hardware security modules address this problem, however, their use increases the cost of embedded IoT devices. Furthermore, millions of IoT devices are already deployed without hardware security support. This paper addresses this problem by introducing a Security MicroVisor (SμV) middleware, which provides memory isolation and custom security operations using software virtualisation and assembly-level code verification. We showcase SμV by implementing a key security feature: remote attestation. Evaluation shows extremely low overhead in terms of memory, performance and battery lifetime for a representative IoT device.