Footsteps in the fog: Certificateless fog-based access control

The proliferating adoption of the Internet of Things (IoT) paradigm has fuelled the need for more efficient and resilient access control solutions that aim to prevent unauthorized resource access. The majority of existing works in this field follow either a centralized approach (i.e. cloud-based) or an architecture where the IoT devices are responsible for all decision-making functions. Furthermore, the resource-constrained nature of most IoT devices make securing the communication between these devices and the cloud using standard cryptographic solutions difficult. In this paper, we propose a distributed access control architecture where the core components are distributed between fog nodes and the cloud. To facilitate secure communication, our architecture utilizes a Certificateless Hybrid Signcryption scheme without pairing. We prove the effectiveness of our approach by providing a comparative analysis of its performance in comparison to the commonly used cloud-based centralized architectures. Our implementation uses Azure – an existing commercial platform, and Keycloak – an open-source platform, to demonstrate the real-world applicability. Additionally, we measure the performance of the adopted encryption scheme on two types of resource-constrained devices to further emphasize the applicability of the proposed architecture. Finally, the experimental results are coupled with a theoretical analysis that proves the security of our approach

Footsteps in the fog: Certificateless fog-based access control

The proliferating adoption of the Internet of Things (IoT) paradigm has fuelled the need for more efficient and resilient access control solutions that aim to prevent unauthorized resource access. The majority of existing works in this field follow either a centralized approach (i.e. cloud-based) or an architecture where the IoT devices are responsible for all decision-making functions. Furthermore, the resource-constrained nature of most IoT devices make securing the communication between these devices and the cloud using standard cryptographic solutions difficult. In this paper, we propose a distributed access control architecture where the core components are distributed between fog nodes and the cloud. To facilitate secure communication, our architecture utilizes a Certificateless Hybrid Signcryption scheme without pairing. We prove the effectiveness of our approach by providing a comparative analysis of its performance in comparison to the commonly used cloud-based centralized architectures. Our implementation uses Azure – an existing commercial platform, and Keycloak – an open-source platform, to demonstrate the real-world applicability. Additionally, we measure the performance of the adopted encryption scheme on two types of resource-constrained devices to further emphasize the applicability of the proposed architecture. Finally, the experimental results are coupled with a theoretical analysis that proves the security of our approach

Post-Quantum Era Privacy Protection for Intelligent Infrastructures

As we move into a new decade, the global world of Intelligent Infrastructure (II) services integrated into the Internet of Things (IoT) are at the forefront of technological advancements. With billions of connected devices spanning continents through interconnected networks, security and privacy protection techniques for the emerging II services become a paramount concern. In this paper, an up-to-date privacy method mapping and relevant use cases are surveyed for II services. Particularly, we emphasize on post-quantum cryptography techniques that may (or must when quantum computers become a reality) be used in the future through concrete products, pilots, and projects. The topics presented in this paper are of utmost importance as (1) several recent regulations such as Europe's General Data Protection Regulation (GDPR) have given privacy a significant place in digital society, and (2) the increase of IoT/II applications and digital services with growing data collection capabilities are introducing new threats and risks on citizens' privacy. This in-depth survey begins with an overview of security and privacy threats in IoT/IIs. Next, we summarize some selected Privacy-Enhancing Technologies (PETs) suitable for privacy-concerned II services, and then map recent PET schemes based on post-quantum cryptographic primitives which are capable of withstanding quantum computing attacks. This paper also overviews how PETs can be deployed in practical use cases in the scope of IoT/IIs, and maps some current projects, pilots, and products that deal with PETs. A practical case study on the Internet of Vehicles (IoV) is presented to demonstrate how PETs can be applied in reality. Finally, we discuss the main challenges with respect to current PETs and highlight some future directions for developing their post-quantum counterparts

Evidence-based Accountability Audits for Cloud Computing

Cloud computing is known for its on-demand service provisioning and has now become mainstream. Many businesses as well as individuals are using cloud services on a daily basis. There is a big variety of services that ranges from the provision of computing resources to services such as productivity suites and social networks. The nature of these services varies heavily in terms of what kind of information is being out-sourced to the cloud provider. Often, that data is sensitive, for instance when PII is being shared by an individual. Also, businesses that move (parts of) their processes to the cloud are actively participating in a major paradigm shift from having data on-premise to transfering data to a third-party provider. However, many new challenges come along with this trend, which are closely tied to the loss of control over data. When moving to the cloud, direct control over geographical storage location, who has access to it and how it is shared and processed is given up. Because of this loss of control, cloud customers have to trust cloud providers that they treat their data in an appropriate and responsible way. Cloud audits can be used to check how data has been processed in the cloud (i.e., by whom, for what purpose) and whether or not this happened in compliance with what has been defined in agreed-upon privacy and data storage, usage and maintenance (i.e., data handling) policies. This way, a cloud customer can regain some of the control he has given up by moving to the cloud. In this thesis, accountability audits are presented as a way to strengthen trust in cloud computing by providing assurance about the processing of data in the cloud according to data handling and privacy policies. In cloud accountability audits, various distributed evidence sources need to be considered. The research presented in this thesis discusses the use of various heterogeous evidence sources on all cloud layers. This way, a complete picture of the actual data handling practices that is based on hard facts can be presented to the cloud consumer. Furthermore, this strengthens transparency of data processing in the cloud, which can lead to improved trust in cloud providers, if they choose to adopt these mechanisms in order to assure their customers that their data is being handled according to their expectations. The system presented in this thesis enables continuous auditing of a cloud provider's adherence to data handling policies in an automated way that shortens audit intervals and that is based on evidence that is produced by cloud subsystems. An important aspect of many cloud offerings is the combination of multiple distinct cloud services that are offered by independent providers. Data is thereby freuqently exchanged between the cloud providers. This also includes trans-border flows of data, where one provider may be required to adhere to more strict data protection requirements than the others. The system presented in this thesis addresses such scenarios by enabling the collection of evidence at providers and evaluating it during audits. Securing evidence quickly becomes a challenge in the system design, when information that is needed for the audit is deemed sensitive or confidential. This means that securing the evidence at-rest as well as in-transit is of utmost importance, in order not to introduce a new liability by building an insecure data heap. This research presents the identification of security and privacy protection requirements alongside proposed solutions that enable the development of an architecture for secure, automated, policy-driven and evidence-based accountability audits

Online learning on the programmable dataplane

This thesis makes the case for managing computer networks with datadriven methods automated statistical inference and control based on measurement data and runtime observations—and argues for their tight integration with programmable dataplane hardware to make management decisions faster and from more precise data. Optimisation, defence, and measurement of networked infrastructure are each challenging tasks in their own right, which are currently dominated by the use of hand-crafted heuristic methods. These become harder to reason about and deploy as networks scale in rates and number of forwarding elements, but their design requires expert knowledge and care around unexpected protocol interactions. This makes tailored, per-deployment or -workload solutions infeasible to develop. Recent advances in machine learning offer capable function approximation and closed-loop control which suit many of these tasks. New, programmable dataplane hardware enables more agility in the network— runtime reprogrammability, precise traffic measurement, and low latency on-path processing. The synthesis of these two developments allows complex decisions to be made on previously unusable state, and made quicker by offloading inference to the network. To justify this argument, I advance the state of the art in data-driven defence of networks, novel dataplane-friendly online reinforcement learning algorithms, and in-network data reduction to allow classification of switchscale data. Each requires co-design aware of the network, and of the failure modes of systems and carried traffic. To make online learning possible in the dataplane, I use fixed-point arithmetic and modify classical (non-neural) approaches to take advantage of the SmartNIC compute model and make use of rich device local state. I show that data-driven solutions still require great care to correctly design, but with the right domain expertise they can improve on pathological cases in DDoS defence, such as protecting legitimate UDP traffic. In-network aggregation to histograms is shown to enable accurate classification from fine temporal effects, and allows hosts to scale such classification to far larger flow counts and traffic volume. Moving reinforcement learning to the dataplane is shown to offer substantial benefits to stateaction latency and online learning throughput versus host machines; allowing policies to react faster to fine-grained network events. The dataplane environment is key in making reactive online learning feasible—to port further algorithms and learnt functions, I collate and analyse the strengths of current and future hardware designs, as well as individual algorithms

Actas de las VI Jornadas Nacionales (JNIC2021 LIVE)

Estas jornadas se han convertido en un foro de encuentro de los actores más relevantes en el ámbito de la ciberseguridad en España. En ellas, no sólo se presentan algunos de los trabajos científicos punteros en las diversas áreas de ciberseguridad, sino que se presta especial atención a la formación e innovación educativa en materia de ciberseguridad, y también a la conexión con la industria, a través de propuestas de transferencia de tecnología. Tanto es así que, este año se presentan en el Programa de Transferencia algunas modificaciones sobre su funcionamiento y desarrollo que han sido diseñadas con la intención de mejorarlo y hacerlo más valioso para toda la comunidad investigadora en ciberseguridad

Unclonability and quantum cryptanalysis: from foundations to applications

The impossibility of creating perfect identical copies of unknown quantum systems is a fundamental concept in quantum theory and one of the main non-classical properties of quantum information. This limitation imposed by quantum mechanics, famously known as the no-cloning theorem, has played a central role in quantum cryptography as a key component in the security of quantum protocols. In this thesis, we look at \emph{Unclonability} in a broader context in physics and computer science and more specifically through the lens of cryptography, learnability and hardware assumptions. We introduce new notions of unclonability in the quantum world, namely \emph{quantum physical unclonability}, and study the relationship with cryptographic properties and assumptions such as unforgeability, randomness and pseudorandomness. The purpose of this study is to bring new insights into the field of quantum cryptanalysis and into the notion of unclonability itself. We also discuss applications of this new type of unclonability as a cryptographic resource for designing provably secure quantum protocols. First, we study the unclonability of quantum processes and unitaries in relation to their learnability and unpredictability. The instinctive idea of unpredictability from a cryptographic perspective is formally captured by the notion of \emph{unforgeability}. Intuitively, unforgeability means that an adversary should not be able to produce the output of an \emp{unknown} function or process from a limited number of input-output samples of it. Even though this notion is almost easily formalized in classical cryptography, translating it to the quantum world against a quantum adversary has been proven challenging. One of our contributions is to define a new unified framework to analyse the unforgeability property for both classical and quantum schemes in the quantum setting. This new framework is designed in such a way that can be readily related to the novel notions of unclonability that we will define in the following chapters. Another question that we try to address here is "What is the fundamental property that leads to unclonability?" In attempting to answer this question, we dig into the relationship between unforgeability and learnability, which motivates us to repurpose some learning tools as a new cryptanalysis toolkit. We introduce a new class of quantum attacks based on the concept of `emulation' and learning algorithms, breaking new ground for more sophisticated and complicated algorithms for quantum cryptanalysis. Second, we formally represent, for the first time, the notion of physical unclonability in the quantum world by introducing \emph{Quantum Physical Unclonable Functions (qPUF)} as the quantum analogue of Physical Unclonable Functions (PUF). PUF is a hardware assumption introduced previously in the literature of hardware security, as physical devices with unique behaviour, due to manufacturing imperfections and natural uncontrollable disturbances that make them essentially hard to reproduce. We deliver the mathematical model for qPUFs, and we formally study their main desired cryptographic property, namely unforgeability, using our previously defined unforgeability framework. In light of these new techniques, we show several possibility and impossibility results regarding the unforgeability of qPUFs. We will also discuss how the quantum version of physical unclonability relates to randomness and unknownness in the quantum world, exploring further the extended notion of unclonability. Third, we dive deeper into the connection between physical unclonability and related hardware assumptions with quantum pseudorandomness. Like unclonability in quantum information, pseudorandomness is also a fundamental concept in cryptography and complexity. We uncover a deep connection between Pseudorandom Unitaries (PRU) and quantum physical unclonable functions by proving that both qPUFs and the PRU can be constructed from each other. We also provide a novel route towards realising quantum pseudorandomness, distinct from computational assumptions. Next, we propose new applications of unclonability in quantum communication, using the notion of physical unclonability as a new resource to achieve provably secure quantum protocols against quantum adversaries. We propose several protocols for mutual entity identification in a client-server or quantum network setting. Authentication and identification are building-block tasks for quantum networks, and our protocols can provide new resource-efficient applications for quantum communications. The proposed protocols use different quantum and hybrid (quantum-classical) PUF constructions and quantum resources, which we compare and attempt in reducing, as much as possible throughout the various works we present. Specifically, our hybrid construction can provide quantum security using limited quantum communication resources that cause our protocols to be implementable and practical in the near term. Finally, we present a new practical cryptanalysis technique concerning the problem of approximate cloning of quantum states. We propose variational quantum cloning (\VQC), a quantum machine learning-based cryptanalysis algorithm which allows an adversary to obtain optimal (approximate) cloning strategies with short depth quantum circuits, trained using the hybrid classical-quantum technique. This approach enables the end-to-end discovery of hardware efficient quantum circuits to clone specific families of quantum states, which has applications in the foundations and cryptography. In particular, we use a cloning-based attack on two quantum coin-flipping protocols and show that our algorithm can improve near term attacks on these protocols, using approximate quantum cloning as a resource. Throughout this work, we demonstrate how the power of quantum learning tools as attacks on one hand, and the power of quantum unclonability as a security resource, on the other hand, fight against each other to break and ensure security in the near term quantum era

Jornadas Nacionales de Investigación en Ciberseguridad: actas de las VIII Jornadas Nacionales de Investigación en ciberseguridad: Vigo, 21 a 23 de junio de 2023

Jornadas Nacionales de Investigación en Ciberseguridad (8ª. 2023. Vigo)atlanTTicAMTEGA: Axencia para a modernización tecnolóxica de GaliciaINCIBE: Instituto Nacional de Cibersegurida