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  • 1.
    Fredriksson, Bastian
    KTH, School of Computer Science and Communication (CSC).
    A Distributed Public Key Infrastructure for the Web Backed by a Blockchain2017Independent thesis Advanced level (degree of Master (One Year)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    The thesis investigates how a blockchain can be used to build a decentralised public key infrastructure for the web, by proposing a custom federation blockchain relying on honest majority. Our main contribution is the design of a Proof of Stake protocol based on a stake tree, which builds upon an idea called follow-the-satoshi used in previous papers.

    Digital identities are stored in an authenticated self-balancing tree maintained by blockchain nodes. Our back-of-the-envelope calculations, based on the size of the domain name system, show that the block size must be set to at least 5.2 MB, while each blockchain node with a one-month transaction history would need to store about 243 GB. Thin clients would have to synchronise about 13.6 MB of block headers per year, and download an additional 3.7 KB of proof data for every leaf certificate which is to be checked.

  • 2.
    Fredriksson, Bastian
    et al.
    KTH, School of Computer Science and Communication (CSC).
    Lundberg, Edvin
    KTH, School of Computer Science and Communication (CSC).
    The Monk Problem: Verifier, heuristics and graph decompositions for a pursuit-evasion problem with a node-located evader2015Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    This paper concerns a specific pursuit-evasion problem with a node-located evader which we call the monk problem. First, we propose a way of verifying a strategy using a new kind of recursive systems, called EL-systems. We show how an EL-system representing a graph-instance of the problem can be represented using matrices, and we give an example of how this can be used to efficiently implement a verifier.

    In the later parts we propose heuristics to construct a strategy, based on a greedy algorithm. Our main focus is to minimise the number of pursuers needed, called the search number. The heuristics rely on properties of minimal stable components.

    We show that the minimal stable components are equivalent to the strongly connected components of a graph, and prove that the search number is equal to the maximum search number of its strongly connected components. We also establish lower and upper bounds for the search number to narrow the search space.

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