Blockchain technology emerged in 2009 together with the introduction of Bitcoin, the first virtual currency which enabled nodes in a network, that do not necessarily trust each other, to exchange digital value without the use of trusted intermediaries. Since then, the idea of disintermediation and decentralization has gained traction in a large number of applications outside the world of finance and virtual currencies. This thesis is written in collaboration with Scania, an automotive industry manufacturer, with the purpose of gaining a better understanding of blockchain technology and how it can be used in the transportation industry. This thesis proposes five potential blockchain use cases that aim to either enhance Scania’s existing services or to create new services. Out of these five use cases, one is deemed inappropriate in regards to the use of blockchain technology while the other four have potentials benefits. The common denominator among these use cases is that they are decentralized in nature meaning that the use of intermediaries is mitigated. It is recognized that all use cases could be implemented using traditional, centralized databases and that the use of blockchain boils down to a technology choice with its own trade-offs relative to other potential choices. This thesis concludes that blockchain technology offers a new kind of database architecture, the main benefit of which is that it lets several non-trusting entities agree on a common set of facts, without having a trusted intermediary establishing these facts.

<div>Comprehensive networking security is a goal to achieve for enterprise networks. In forensics, the traffic analysis, causality dependence in intricate program network flows is needed in flow-based attribution techniques. The provenance, the connection between stealthy advanced persistent threats (APTs) and the execution of loadable modules is stripped because loading a module does not guarantee an execution. The reports of common vulnerabilities and exposures (CVE) demonstrate that lots of vulnerabilities have been introduced in protocol engineering process, especially for the emerging Internet-of-Things (IoT) applications. A code generation framework targeting secure protocol implementations can substantially enhance security.</div><div>A novel automaton-based technique, NetCrop, to infer fine-grained program behavior by analyzing network traffic is proposed in this thesis. Based on network flow causality, it constructs automata that describe both the network behavior and the end-host behavior of a whole program to attribute individual packets to their belonging programs and fingerprint the high-level program behavior. A novel provenance-oriented library tracing system, Lprov, which enforces library tracing on top of existing syscall logging based provenance tracking approaches is investigated. With the dynamic library call stack, the provenance of implicit library function execution is revealed and correlated to system events, facilitating the locating and defense of malicious libraries. The thesis presents ProFactory, in which a protocol is modeled, checked and securely generated, averting common vulnerabilities residing in protocol implementations.</div>