IoT deployments grow in numbers and size, which makes questions of long-term support and maintainability increasingly important. Without scalable and standard-compliant capabilities to transfer the control of IoT devices between service providers, IoT system owners cannot ensure long-term maintainability, and risk vendor lock-in. The manual overhead must be kept low for large-scale IoT installations to be economically feasible. We propose AutoPKI, a lightweight protocol to update the IoT PKI credentials and shift the trusted domains, enabling the transfer of control between IoT service providers, building upon the latest IoT standards for secure communication and efficient encodings. We show that the overhead for the involved IoT devices is small and that the overall required manual overhead can be minimized. We analyse the fulfilment of the security requirements, and for a subset of them, we demonstrate that the desired security properties hold through formal verification using the Tamarin prover.

The standard Constrained Application Protocol (CoAP) is a lightweight, web-transfer protocol based on the REST paradigm and specifically suitable for constrained devices and the Internet-of-Things. Object Security for Constrained RESTful Environment (OSCORE) is a standard, lightweight security protocol that provides end-to-end protection of CoAP messages. A number of methods exist for managing keying material for OSCORE, as to its establishment and update. This paper provides a detailed comparison of such methods, in terms of their features, limitations and security properties. Also, it especially considers the new key update protocol KUDOS, for which it provides a more extended discussion about its features and mechanics, as well as a formal verification of its security properties.

Critical infrastructure is becoming increasingly connected, with tighter integration to the Internet of Things (IoT). Transportation systems in particular are getting smarter with increased cooperation between vehicles and the supporting infrastructure (V2X communications), and with intelligent devices introduced in the ecosystem, either tightly integrated to the vehicle (e.g. ECUs, cameras, ...) or external sensors (e.g. temperature sensor in an attached container, smart traffic light, ...). A number of communication and security protocols are being standardized for this Cooperative Intelligent Transport Systems (C-ITS). However, using the current C-ITS standards, the security of individual devices may terminate at the gateway of a vehicle, and consequently in most existing vehicles, individual systems leak sensitive data across vendors. In this paper, we propose an end-to-end security architecture between C-ITS devices and back-end servers, in which sensitive data from individual devices can be transmitted without trusting third-parties providing the communication infrastructure (e.g. proxies, vehicle gateways, routers). The proposed solution is a standardbased integrated system that exploits recent IoT security standards and ensures inter-operability between CITS protocols and conventional Internet protocols. We perform a formal analysis of our architecture using the Tamarin Prover and show that it guarantees the secrecy and authenticity of the communications under adversarial settings.

SummaryThis paper focus on providing a secure and trustworthy solution for virtual machine (VM) migration within an existing cloud provider domain, and/or to the other federating cloud providers. The infrastructure‐as‐a‐service (IaaS) cloud service model is mainly addressed to extend and complement the previous Trusted Computing techniques for secure VM launch and VM migration case. The VM migration solution proposed in this paper uses a Trust_Token based to guarantee that the user VMs can only be migrated and hosted on a trustworthy and/or compliant cloud platforms. The possibility to also check the compliance of the cloud platforms with the pre‐defined baseline configurations makes our solution compatible with an existing widely accepted standards‐based, security‐focused cloud frameworks like FedRAMP. Our proposed solution can be used for both inter‐ and intra‐cloud VM migrations. Different from previous schemes, our solution is not dependent on an active (on‐line) trusted third party; that is, the trusted third party only performs the platform certification and is not involved in the actual VM migration process. We use the Tamarin solver to realize a formal security analysis of the proposed migration protocol and show that our protocol is safe under the Dolev‐Yao intruder model. Finally, we show how our proposed mechanisms fulfill major security and trust requirements for secure VM migration in cloud environments.

Distance-bounding anonymous credentials could be used for any location proofs that do not need to identify the prover and thus could make even notoriously invasive mechanisms such as location-based services privacy-preserving. There is, however, no secure distance-bounding protocol for general attribute-based anonymous credentials. Brands and Chaum’s (EUROCRYPT’93) protocol combining distance-bounding and Schnorr identification comes close, but does not fulfill the requirements of modern distance-bounding protocols. For that, we need a secure distance-bounding zero-knowledge proof-of-knowledge resisting mafia fraud, distance fraud, distance hijacking and terrorist fraud. Our approach is another attempt toward combining distance bounding and Schnorr to construct a distance-bounding zero-knowledge proof-of-knowledge. We construct such a protocol and prove it secure in the (extended) DFKO model for distance bounding. We also performed a symbolic verification of security properties needed for resisting these attacks, implemented in Tamarin. Encouraged by results from Singh et al. (NDSS’19), we take advantage of lessened constraints on how much can be sent in the fast phase of the distance-bounding protocol and achieve a more efficient protocol. We also provide a version that does not rely on being able to send more than one bit at a time which yields the same properties except for (full) terrorist fraud resistance.

With the advent of the IoT, Smart Cities, and other large-scale extremely heterogeneous systems, distributed systems are becoming both more complex and pervasive every day and will soon be intractable with current approaches. To hide this growing complexity and facilitate the management of distributed systems at all stages of their life-cycle, this thesis argues for a holistic approach, where the function of a system is considered as a whole, moving away from the behavior of individual components. In parallel to this rise in abstraction levels, basic building blocks need to become more autonomous and able to react to circumstances, to alleviate developers and automate most of the low level operations. We propose three contributions towards this vision : 1) Pleiades: a holistic approach to build complex structures by assembly, easily programmable and supported by an efficient, self-organizing gossip-based run-time engine. 2) Mind-the-Gap: a gossip-based protocol to detect partitions and other large connectivity changes in MANETs, thanks to periodic opportunistic aggregations and a stochastic representation of the network membership. 3) HyFN: an extension to traditional gossip protocols that is able to efficiently solve the k-Furthest-Neighbors problem, which standard methods have been unable to up to now. We believe these three contributions demonstrate our vision is realistic and highlight its attractive qualities.

Mobile Ad-hoc Networks (MANETs) use limited-range wireless communications and are thus exposed to partitions when nodes fail or move out of reach of each other. Detecting partitions in MANETs is unfortunately a nontrivial task due to their inherently decentralized design and limited resources such as power or bandwidth. In this paper, we propose a novel and fully decentralized approach to detect partitions (and other large membership changes) in MANETs that is both accurate and resource efficient. We monitor the current composition of a MANET using the lightweight aggregation of compact membership-encoding filters. Changes in these filters allow us to infer the likelihood of a partition with a quantifiable level of confidence. We first present an analysis of our approach, and show that it can detect close to 100% of partitions under realistic settings, while at the same time being robust to false positives due to churn or dropped packets. We perform a series of simulations that compare against alternative approaches and confirm our theoretical results, including above 90% accurate detection even under a 40% message loss rate.

Modern large scale distributed systems increasingly espouse sophisticated distributed architectures characterized by complex distributed structural invariants. Unfortunately, maintaining these structural invariants at scale is time consuming and error prone, as developers must take into account asynchronous failures, loosely coordinated sub-systems and network delays. To address this problem, we propose PLEIADES, a new framework to construct and enforce large-scale distributed structural invariants under aggressive conditions. PLEIADES combines the resilience of self-organizing overlays, with the expressiveness of an assembly-based design strategy. The result is a highly survivable framework that is able to dynamically maintain arbitrary complex distributed structures under aggressive crash failures. Our evaluation shows in particular that PLEIADES is able to restore the overall structure of a 25,600 node system in less than 11 asynchronous rounds after half of the nodes have crashed.

Modern large scale distributed systems increasingly espouse sophisticated distributed architectures characterized by complex distributed structural invariants. Unfortunately, maintaining these structural invariants at scale is time consuming and error prone, as developers must take into account asynchronous failures, loosely coordinated sub-systems and network delays. To address this problem, we propose PLEIADES, a new framework to construct and enforce large-scale distributed structural invariants under aggressive conditions. PLEIADES combines the resilience of self-organizing overlays, with the expressiveness of an assembly-based design strategy. The result is a highly survivable framework that is able to dynamically maintain arbitrary complex distributed structures under aggressive crash failures. Our evaluation shows in particular that PLEIADES is able to restore the overall structure of a 25,600 node system in less than 11 asynchronous rounds after half of the nodes have crashed.

The decentralized construction of k-Furthest-Neighbor graphs has been little studied, although such structures can play a very useful role, for instance in a number of distributed resource allocation problems. In this paper we define KFN graphs; we propose HyFN, a generic peer-to-peer KFN construction algorithm, and thoroughly evaluate its behavior on a number of logical networks of varying sizes.

Large scale distributed systems have become ubiquitous, from on-line social networks to the Internet-of-things. To meet rising expectations (scalability, robustness, flexibility,...) these systems increasingly espouse complex distributed architectures, that are hard to design, deploy and maintain. To grasp this complexity, developers should be allowed to assemble large distributed systems from smaller parts using a seamless, high-level programming paradigm. We present such an assembly-based programming framework, enabling developers to easily de fine and realize complex distributed topologies as a construction of simpler blocks (e.g. rings, grids). It does so by harnessing the power of self-organizing overlays, that is made accessible to developers through a high-level Domain Specific Language and self-stabilizing runtime. Our evaluation further shows that our approach is generic, expressive, low-overhead and robust.

Popular social and e-commerce sites increasingly rely on crowd computing to rate and rank content, users, products and businesses. Today, attackers who create fake (Sybil) identities can easily tamper with these computations. Existing defenses that largely focus on detecting individual Sybil identities have a fundamental limitation: Adaptive attackers can create hard-to-detect Sybil identities to tamper arbitrary crowd computations. In this paper, we propose Stamper, an approach for detecting tampered crowd computations that significantly raises the bar for evasion by adaptive attackers. Stamper design is based on two key insights: First, Sybil attack detection gains strength in numbers: we propose statistical analysis techniques that can determine if a large crowd computation has been tampered by Sybils, even when it is fundamentally hard to infer which of the participating identities are Sybil. Second, Sybil identities cannot forge the timestamps of their activities as they are recorded by system operators; Stamper analyzes these unforgeable timestamps to foil adaptive attackers. We applied Stamper to detect tampered computations in Yelp and Twitter. We not only detected previously known tampered computations with high accuracy, but also uncovered tens of thousands of previously unknown tampered computations in these systems.

Decentralized topology construction protocols organize nodes along a predefined topology (e.g. a torus, ring, or hypercube). Such topologies have been used in many contexts ranging from routing and storage systems, to publish-subscribe and event dissemination. Since most topologies assume no correlation between the physical location of nodes and their positions in the topology, they do not handle catastrophic failures well, in which a whole region of the topology disappears. When this occurs, the overall shape of the system typically gets lost. This is highly problematic in applications in which overlay nodes are used to map a virtual data space, be it for routing, indexing or storage. In this paper, we propose a novel decentralized approach that maintains the initial shape of the topology even if a large (consecutive) portion of the topology fails. Our approach relies on the dynamic decoupling between physical nodes and virtual ones enabling a fast reshaping. For instance, our results show that a 51,200-node torus converges back to a full torus in only 10 rounds after 50% of the nodes have crashed. Our protocol is both simple and flexible and provides a novel form of collective survivability that goes beyond the current state of the art.