The inability to check how our Internet traffic is being handled and routed poses all kinds of security and privacy risks. Yet, for the typical end-user, the Internet indeed is such a black box. This thesis, adheres to the call for an Internet that is more transparent, and as a step forward proposes a mechanism that carefully balances the desire to share transparency information with the necessity to not expose all internal details of a network. Presented work realises this by building on the framework of multi-party computation. Proposed architecture and corresponding proof-of-concept is evaluated via experiments and demonstrates the feasibility of the concept to improve Internet transparency.

Online gaming is the world’s largest entertainment industry by revenue, and supports over 3 billion consumers worldwide. Many of the world’s most popular online games must manage millions of concurrent players through a single unified service. Achieving performant and scalable online games is challenging. Online games are subject to stringent quality of service requirements, notably extremely low response times, with at most 50ms being considered acceptable. Unlike many other types of applications, the performance of online games depends to a large degree on the resources available on end-user devices. These devices are typically heterogeneous, limited in compute and network resources, and subject to unpredictable changes in resource availability.
Addressing this challenge, we propose in this work the concept of differentiated deployment, which allows online games to selectively manage and scale online-game systems with fine granularity in response to changes in available resources. We design Polka, a framework for online games which supports differentiated deployment. We then implement PolkaDOTS, an open-source proof of concept of the Polka framework built in an industry standard game development ecosystem.
We evaluate our approach using Dither, a custom-built experiment runner for large scale distributed experiments on online games. We use Dither to perform real-world experiments on a representative Minecraft-like Game, Opencraft 2, built on the PolkaDOTS stack, and analyze the impact of various differentiated deployment scenarios. From these experiments, we find that differentiated deployment can decrease performance variability of online-game servers, and decrease the response time experienced by players by up to 32%. Most importantly, we show that differentiated deployment enables novel deployment techniques, including switching from local rendering to cloud-based rendering (i.e., cloud gaming) at runtime.

The versatility of the internet enables many applications that play an increasingly bigger role in our society. However, users have little control over the route that their internet traffic takes, which prevents them from controlling who sees their packets and how their traffic is handled. Researchers have proposed an extension to the internet, called the responsible internet, that aims to provide users with control over the route that their internet traffic takes.
Providing this control is the aim of this thesis. Users can control their route by specifying requirements that their route has to fulfill. This thesis defines the Maximum Path Requirement Intersection (MPRI) problem as the problem of finding the route that satisfies as many of the user’s requirements as possible, and this thesis proves that MPRI is NP-hard. Subsequently, both a heuristic to solve the problem in a reasonable amount of time as well as an exact algorithm that guarantees to find the globally best path are introduced. The performance of the heuristic is measured relative to the globally optimal solution given by the exact algorithm. Results show that less features allow the heuristic to have a larger search space, which improves the results; that the runtime of the heuristic scales polynomially in the number of hops between the start and end node; that the heuristic is most effective in graphs that have a power-law degree distribution and least effective in grid-like graphs; and that in a realistic setting the heuristic runs quickly while performing close to optimal.

The rapid evolution of 5G technology has paved the way for the proliferation of resource-constrained Internet of Things (IoT) devices, collectively known as ambient IoT. While these devices offer unprecedented opportunities for connectivity and data collection, their limited computational capabilities present significant challenges in implementing robust security measures. This thesis addresses these challenges by proposing two novel lightweight security protocols tailored for ambient IoT devices within 5G networks.

The first protocol, "Lightweight security protocol instantiated using ASCON", leverages the ASCON family of cryptographic functions to ensure essential security properties while adhering to the constraints of ambient IoT devices. The protocol’s effectiveness is evaluated through simulations, focusing on computational efficiency compared to existing solutions.

The second protocol, "Data container-based security protocol", adopts a container-based approach to enhance interoperability and standardization across diverse ambient IoT device applications. This protocol facilitates seamless integration and compatibility among ambient IoT systems by encapsulating authentication and communication data within generic containers. The benefits of this approach are analyzed theoretically, highlighting its potential for standardization in heterogeneous 5G environments.

Together, these lightweight security protocols contribute to developing a secure and efficient ecosystem for ambient IoT devices within 5G networks. By addressing the challenges posed by resource-constrained devices and promoting interoperability, this thesis aims to enhance security and facilitate the widespread adoption of ambient IoT technologies in our increasingly connected world.

An all-important step in the ambitious pursuit towards autonomous networks has been the introduction of Software Defined Networking which has advocated the concept of separating a network’s control plane from the data plane and creating a programmable controller with a wider view of the network. This innovation proved to be very promising, but the non-programmable data plane quickly became a limitation. 
The next step was brought by the emergence of the programmable switch architecture and P4, a language specifically designed for defining the behaviour of programmable network devices. P4 is a remarkably powerful language that allows the software developer to define almost any packet-processing functionality, all while abstracting away from the specifics of the target’s hardware architecture.
Despite its many benefits, P4 brings with it an additional layer of complexity for the network administrators, which may find themselves overwhelmed by having to learn a new programming language.
This report tackles this issue by presenting a prototype that is capable of synthesizing small P4 programs from pairs of input & output packets. Under the hood, the proposed solution uses a bottom-up enumerative synthesizer called Probe. This synthesizer was re-implemented, improved, and tailored to leverage the particularities of the problem domain.

The ongoing digitalization of the world, estimated to reach a yearly data generation of 200 Zettabytes by 2025, is putting increasing pressure on system developers to provide systems capable of scaling with future needs. Of particular importance are the data storage systems, providing the means of storing and retrieving the vast amounts of data. One widely adopted storage technology, predicted to become the leading media for future data storage, is flash-based solid state drives (SSD). The complex architecture of flash SSD however introduces several challenges, such as necessary garbage collection, for managing the flash storage. To readily integrate flash SSD into storage systems, the flash management idiosyncrasies are hidden inside the storage device. The hiding of the flash management idiosyncrasies has however been identified to have significant performance implications. As a result, numerous efforts have pushed towards more open flash storage interfaces, with the most recent addition of Zoned Namespace (ZNS) flash SSD. ZNS SSD presents a unique opportunity for storage software and the flash SSD to coordinate the flash management responsibilities.

While the open flash storage interface of ZNS presents a plethora of opportunity in software optimization, current software support is in its early stages, leaving much of its potentials yet to be explored. In this work, we present msF2FS (multi-streamed F2FS), a file system with optimized ZNS integration, based on the de facto standard flash file system F2FS. msF2FS enhances the ZNS integration by leveraging the parallelism capabilities of ZNS SSD, and increasing the coordination between the file system and applications for data placement decision-making. The data placement coordination between file system and application reduces the sub-optimal data placement decisions made by the file system. Evaluations of msF2Fs show the benefit of the application and file system coordination, with the RocksDB application achieving up to 23.19% higher throughput as a result of optimized data placement. We make all developed code of msF2FS publicly available at https://github.com/nicktehrany/msF2FS.

Intent-based Networking (IBN) is one of the hot topics of research in the modern field of networking. Abstracting the complexity of network management away from the network operator through automation is the cornerstone of the IBN concept. However, a lot of current research on intent-based networking is concentrated towards programmable software defined networks (SDN), rather than traditional non-programmable network devices which still hold a large market share in modern networks. Moreover, when it comes to traditional network devices, network validation becomes very crucial as it needs a endoragnostic environment to evaluate the network. This thesis studies the important aspects necessary for IBN adaptation for legacy devices and provides a solution for adaptation into modern networks, while being vendor-agnostic. Based on the design, the results obtained from the proofs-of-concept are then analyzed and concluded upon, ending by elucidating avenues of future work.

As a result of a global pandemic, there has been an increasing interest in tools for remote video conferencing and collaboration. One of these new innovations is social eXtended Reality (XR). By combining Virtual Reality (VR) and Augmented Reality (AR) technologies, social XR can provide a more immersive experience than any other VR application by giving users at different locations the chance to virtually gather in real-time. But such applications impose enormous requirements on computational and communication resources. 5th Generation (5G) mobile networks are targeted as solution to provide ultra-low latency and ultra-high throughput for social XR. In current research, many optimisations are aimed at VR applications such as on-demand streaming, while there is a lack of solutions for real-time user-interactive applications like social XR. In this graduation project we develop and assess cross-layer solutions for optimised scheduling of social XR applications in 5G networks. An existing framework for simulating social XR conference applications serves as the basis for our modelling approach. We devise different schedulers, that utilise cross-layer information in the form of the video frametype and frame-level End-to-End (E2E) latency budgets rather than packet-level latency budgets purely within the Radio Access Network (RAN). In contrast to previous work, we create the VR traffic based on real video data and develop tools to model the packet dispersion caused by multi-hop transmission over the internet towards the RAN. We study the effect of various system and traffic parameters on the Quality of Service (QoS) and perceived Quality of Experience (QoE) in the context of social XR applications through an extensive sensitivity analysis. Herein we also assess the performance impact of different types of cross-layer packet schedulers. Further, we gain insights into the correlation between the network QoS and perceived QoE by end users which are the key in future cross-layer implementations for social XR.

Data planes are responsible for forwarding packets in a network. The P4 language is used for programming programmable data planes. Such data planes give more flexibility to programmers by allowing them to define how the packets should be processed. However, these data planes might also be more vulnerable to malicious attacks than traditional (non-programmable) data planes. That is because software is usually more prone to errors as compared to the hardware. Different research has already analyzed various aspects of the security of the P4 language. However, the security vulnerabilities of P4 programs have not been researched in depth. The main contribution of this paper is providing examples of attacks on P4 programs by using manipulated packet data. In this research, it was attempted to corrupt three P4 programs by manipulating packet data. Two of the three attempts were successful. The paper concludes that some P4 programs can be corrupted by malicious packets.

In software defined networking a controller can control where the data-plane routes packets to. Programmable data-planes make networks even more flexible, as the algorithms on the data-plane can be updated. The P4 programming language can be used to program data-planes, and the P4Runtime data-plane API can be used for controller to data-plane communication. The possibility of man-in-the-middle attacks when using P4Runtime was investigated. Man-in-the-middle attacks are possible either between the controller and data-plane, or between two hosts on the network. A virtual network in Mininet was used to try and demonstrate the difference between secure and insecure channels in these two scenarios. A malicious controller can take control of a switch in order to use it for man-in-the-middle attacks when the P4Runtime channel is insecure, but not in a secure channel. The man-in-the-middle attack between the controller and switch was not achieved due to the switches in Mininet only running on localhost and not being able to run the controller in-band. It was concluded that it is indeed recommended to only use secure P4Runtime channels, and possible extensions to this research could be to attempt the same experiment using a different setup or to research the effects that a successful man-in-the-middle attack can have.

After software defined networking (SDN) separated the control-plane from the dataplane, P4 was proposed as a solution to be able to program the data-plane. The programmable data plane (PDP) is very useful to alter the behaviour of programmable network devices. The drawback, however, is that without virtualization only one single P4 program can run at a time on the PDP. Compiler based and hypervisor based approaches can be used to virtualize the P4 data-plane to let P4 programs run alongside each other. This increases the flexibility when compared to P4, but can potentially come with added risks. Hypervisor based approaches share resources, while compiler based approaches try to minimize the sharing of resources. This opens up hypervisor based approaches, like HyperVDP and Hyper4, to attacks from a corrupt P4 program. Because of the resource sharing, when one of the virtualized P4 programs in HyperVDP is corrupted, there potentially is a risk that the other virtualized programs also get influenced. This paper will attempt to answer the question; can a malicious P4 program corrupt behaviour of another P4 program while running alongside each other. This will be done by laying out a method to answer this question using HyperVDP. A repository containing the updated source code of HyperVDP will also be created and provided to allow for a stable framework.

Certificate transparency (CT) is a system that publishes all issued certificates so that they can be audited and monitored by any party. This allows to detect mis­issued certificates quickly and catch the misbehaving certificate authorities. CT makes the certificate ecosystem more transparent and less reliant on trust that trusted certificate authorities (CA) do not issue rogue certificates. Events such as the compromise of the CA DigiNotar in 2011 could be easily and quickly detected with CT. CT makes use of CT logs, where issued certificates from trusted CA are stored. CT logs are append­only ledger that can be accessed by anyone. The entire issue with trust and misissuance seems to be solved by this new technology, CT. But are there any downsides to this solution? Albeit, it helps to detect misissuance quickly, but at the same time introduces an additional source to exploit. CT logs are public ledgers of issued certificates. They can be used to discover new domain names, or to look up what domains exist. Given a domain, an attacker could harness the power of CT logs to look up all the subdomains. CT logs expose every domain, even internal ones that need a certificate but do not want to be known to the public. Furthermore, domains can be easily found without the need to guess domain names or exploiting other resources such as DNS, allowing attackers to generate lists of potential targets easily. In this paper, we analyze the security impact of CT on scanning traffic for domains hosted in IPv4 and IPv6. The domains’ certificates are appended to CT logs, to leak the embedded domain name, which is acting as a honeytoken, a lure. We conduct passive measurements on the domain hosts, the hosting webserver and the authoritative DNS server, perform data analysis on the measurements and evaluate the security impact of the certificate request.

In recent years, researchers proposed several universal caching policies. These universal caching policies aim to work well with any request sequence. However, with this universal well-working property, these caching policies sometimes do not work as well as conventional caching policies such as Least-Recently-Used and Least-Frequently-Used. This thesis introduces an online learning approach to dynamically switch between caching policies. The dynamical switching selects the most suitable caching policy for the request sequence and thus ensures the best of both worlds, working well under any request sequence and having comparable performance to the conventional caching policies. The Dynamic Expert Caching (DEC) policy designed in this thesis uses algorithms from the expert selection problem to achieve the dynamic caching policy selection. The DEC policy is evaluated using various datasets where it is shown to have comparable performance to the best caching policies in the simulations. The DEC policy is also adapted to work in a network of caches, named MultiDEC. In this setting, MultiDEC has significant advantages over other universal caching policies where each caching node can have a different caching policy that is optimal.

This research has been performed in pursuit of the MSc Computer Science at Delft University of Technology in collaboration with the Dutch National Office for Identity Data (RvIG), part of the Dutch Ministry of the Interior and Kingdom Relations. Self-Sovereign Identity (SSI) is a relatively new concept part of a movement aspiring to create a universal identity layer for the Internet. SSI aims to put the citizen at the centre of their data, making them the sovereign over their digital presence. Wherein the current ecosystem personal information is stored in centralised or federated settings, SSI delegates this responsibility entirely to the user. Functioning SSI schemes have been proposed and deployed, even with governmental support. However, we identify that the key issue that remains to be solved is revocation: the invalidation of credentials. Proposed revocation mechanisms typically rely on centralised infrastructure for revocations, defying the principles of SSI itself and, furthermore, lack offline verification capabilities. This research addresses these issues and proposes the first fully distributed revocation mechanism in SSI, using a gossip-based propagation algorithm. Our revocation mechanism requires no centralised infrastructure or strict network requirements and enables offline verification of credentials in case of disaster. Propagation is handled by honest clients, requires no direct communication with authorities and is shown to be robust in case of unreliable communication links. Furthermore, revocation acceptance is at the discretion of individual clients, making our mechanism fully adhere to the principles of Self-Sovereignty. This revocation and verification structure is part of our Industry-Grade Self-Sovereign Identity (IG-SSI) architecture. IG-SSI is a purely academic fully distributed SSI scheme with intrinsic equality across the network. Furthermore, communication is facilitated peer-to-peer, requiring no specialised infrastructure. The architecture allows for the signing, verification and presentation of credentials using Zero-Knowledge Proofs. We believe that the characteristics of our system provide it with use for decades to come, hence, we deem it to be industry-grade. Our simulation portrays that a network comprised of 10,000 clients gossips 1 million revocations within 25 seconds. Feasibility on smartphones is shown through a government-backed real-life trial. Based on our results, we claim that IG-SSI is a viable candidate for facilitating the needs for a digital identity of the European Union.

Multi-label classification has gained a lot of attraction in the field of computer vision over the past couple of years. Here, each instance belongs to multiple class labels simultaneously. There are numerous methods for Multi-label classification, however all of them make the assumption that either the training images are completely labelled or that label correlations are given. Since Active Learning is frequently used when not much data is available, it could be used to determine the missing labels by querying an oracle. This paper proposes a novel solution that combines the current state-of-the-art for Multi-label classification with Active Learning to infer the missing labels. This is done with sampling strategies that try to select the most informative sample from the dataset by exploring the amount of missing labels. With these strategies, we try to minimize the relabeling cost for all samples, while maximizing the information gained. The chosen method called Hard sampling with entropy then looks to select those samples that both the model and we find informative. The chosen measure along with the other measure are then explored and evaluated on a subset of the MSCOCO dataset on 20%, 40% and 60% noise. Hard sampling with entropy then outperforms the state-of-the-art by more then 30%, as well as the baseline sampling method by 2% for 60% noise.

In the Dutch motorway traffic management (MTM) system used by Rijkswaterstaat, a central system and multiple outstations alongside the road communicate with each other to keep highways safe. This makes the MTM system a form of distributed flow control system. However, Rijkswaterstaat faces 2 problems with regards to traffic control: the control system is hierarchical leading to a single point of failure and communication failures between the central system and the outstations lead to unsafe situations. A solution to both problems is the use of a multi-agent system (MAS). However, no fault-tolerant MAS solution exists for the type of flow network that the highway network is. We therefore design our own fault-tolerant MAS solution for flow networks where the failure of a controller does not change the characteristics of the flow network. Our design associates an agent with every outstation in the network giving it the ability to make its own decisions. The communication protocol used by these agents to communicate with each other is capable of detecting communication failures with outstations and rearrange them so that the control action remains unchanged. This results in a system which keeps the highway safe when one or more outstations or their communication abilities fail.

With the proliferation of IoT devices across the globe, the adoption of IoT related technologies has been increasing rapidly. Newer technologies which fall in the category of Low Power Wide Area Network (LPWAN) have increased this adoption even further. A lot of research is being done in LPWAN licensed band as well as unlicensed band technologies to make them more efficient, such as in terms of power consumption and latency. In this thesis the author has focused on cellular IoT technologies (licensed spectrum LPWAN technologies), to improve the end-to-end behavior. The focus is to see and improve the effect of the device on the network behavior. We have done tests on different networks and went through the 3GPP Specification Release 14 to find possible areas of improvement. Keeping this in mind we have designed a solution to increase the number of pageable devices that can be maintained by the network compared to its original capacity (when not using our solution). This solution can be used to optimize as per the use case, whether to provide lower latency or save energy consumption of the device. To verify that the solution can be used in real life, we have tested it with Stedin critical application device in their substation.

LoRaWAN is amongst the most prominent LPWAN (Low Power Wide Area Networking) technologies and provides an operation mode, called Class B, where devices can be reached with limited latency. One of the most important features of LoRaWAN Class B is multicast, which allows a single transmission to be shared by multiple multicast group member end-devices. This enables key IoT functionalities such as FOTA (Firmware Over The Air) and other applications that need to transfer multiple packets to a set
of end-devices. This thesis will delve into LoRaWAN Class B multicast and study its scalability -- the most important behavior to study in all IoT technologies. An ns-3 module for LoRaWAN Class B multicast has been extended and used for in-depth analysis and drawing scalability insights. The study also explores methods to improve performance as well as enhance scalability.

Switches that can be (re)programmed through the network programming language P4 are able to completely change – even while in the field – the way they process packets. While powerful, P4 code is inherently static, as it is written and installed to accommodate a particular network requirement. Writing new P4 code each time new requirements arise may be complex and limits our agility to deal with changes in network traffic and services. To solve that problem, we present two frameworks within this work: P4I/O and GP4P4. P4I/O is a new approach to data-plane programmability based on the philosophy of Intent-Based Networking. P4I/O provides an intent-driven interface that can be used to install and/or remove P4 programs on the switches when needed and which is easy to use. In particular, to realize P4I/O, we (1) describe an extensible Intent Definition Language (IDL), (2) create a repository of P4 code templates, which are parsed and merged based on the intents, (3) provide a technique to realize the resulting P4 program in a programmable switch, while accommodating intent modifications at any time, and finally (4) implement a proof-of-concept to demonstrate that intent modifications can be done on-the-fly. Our second framework, GP4P4, is a genetic programming approach able to autonomously generate programs for P4-programmable switches directly from network intents. We demonstrate that GP4P4 is able to generate various network functions in up to a few minutes; an important first step towards realizing the vision of ‘Self-Driving’ networks.