In Things We Trust? Towards trustability in the Internet of Things

This essay discusses the main privacy, security and trustability issues with the Internet of Things

Trust, Privacy and Transparency with Blockhain Technology in Logistics

Since the introduction of blockchain over a decade ago, many industries and industrial sectors are exploring the potentials of the technology. In line with the trend, logistics sector is not an exception and is investigation various dynamics associated with the implementation of the technology. This study focuses on the linking between the capabilities of blockchain technology and trust, privacy and transparency. In order to explore dynamics of the linkage, the study used case study as a method for the inquiry. These have been common issues in logistics which the existing information solutions are unable in resolving to a greater extent.. The results shows that blockchain technology has the capability to build trust among unknown industry players while maintaining a sufficient level of privacy and transparency at the same time. Overall, the study presents useful insights by contributing to the major issues in logistics and supply chain when an innovative digital technology is put into action

Differentially Private Linear Optimization for Multi-Party Resource Sharing

This study examines a resource-sharing problem involving multiple parties that agree to use a set of capacities together. We start with modeling the whole problem as a mathematical program, where all parties are required to exchange information to obtain the optimal objective function value. This information bears private data from each party in terms of coefficients used in the mathematical program. Moreover, the parties also consider the individual optimal solutions as private. In this setting, the concern for the parties is the privacy of their data and their optimal allocations. We propose a two-step approach to meet the privacy requirements of the parties. In the first step, we obtain a reformulated model that is amenable to a decomposition scheme. Although this scheme eliminates almost all data exchanges, it does not provide a formal privacy guarantee. In the second step, we provide this guarantee with a locally differentially private algorithm, which does not need a trusted aggregator, at the expense of deviating slightly from the optimality. We provide bounds on this deviation and discuss the consequences of these theoretical results. We also propose a novel modification to increase the efficiency of the algorithm in terms of reducing the theoretical optimality gap. The study ends with a numerical experiment on a planning problem that demonstrates an application of the proposed approach. As we work with a general linear optimization model, our analysis and discussion can be used in different application areas including production planning, logistics, and revenue management

Blockchain within Logistics: a SWOT analysis

The industry 4.0 is already developed in many sectors and business. In recent years, some technologies of this trend have appeared in our society providing new business models and improving the effectiveness and efficiency for processes. One of these technologies is Blockchain, a distributed database of records among participants. It is believed that this technology could revolutionize business and redefine logistics. However, Blockchain is an emerging technology and it is still at an early state of development. The objetive of this Master Dissertation is to understand what Blockchain is and to measure the impact of this technology in logistics, analyzing the possible limitations and applications and considering professional judgement. Moreover, this work provide a framework to identify the Blockchain opportunities in the logistics industry and helping managers to know where they can implement it in their processes. The methodology of this work involved three stages: (1) analysis of the literature review to establish the technology basis and the current applications in logistics; (2) The implementation of a SWOT analysis according to recent studies; (3) testing the SWOT analysis using an online interview aimed at experienced business in logistics and cibersecurity. Finally it will be explained the main result of this work. Keywords: Industry 4.0, Blockchain, Logistics, Supply Chain, SWOT analysisOutgoin

Towards the decentralized coordination of multiple self-adaptive systems

When multiple self-adaptive systems share the same environment and have common goals, they may coordinate their adaptations at runtime to avoid conflicts and to satisfy their goals. There are two approaches to coordination. (1) Logically centralized, where a supervisor has complete control over the individual self-adaptive systems. Such approach is infeasible when the systems have different owners or administrative domains. (2) Logically decentralized, where coordination is achieved through direct interactions. Because the individual systems have control over the information they share, decentralized coordination accommodates multiple administrative domains. However, existing techniques do not account simultaneously for both local concerns, e.g., preferences, and shared concerns, e.g., conflicts, which may lead to goals not being achieved as expected. Our idea to address this shortcoming is to express both types of concerns within the same constraint optimization problem. We propose CoADAPT, a decentralized coordination technique introducing two types of constraints: preference constraints, expressing local concerns, and consistency constraints, expressing shared concerns. At runtime, the problem is solved in a decentralized way using distributed constraint optimization algorithms implemented by each self-adaptive system. As a first step in realizing CoADAPT, we focus in this work on the coordination of adaptation planning strategies, traditionally addressed only with centralized techniques. We show the feasibility of CoADAPT in an exemplar from cloud computing and analyze experimentally its scalability

"On the Road" - Reflections on the Security of Vehicular Communication Systems

Vehicular communication (VC) systems have recently drawn the attention of industry, authorities, and academia. A consensus on the need to secure VC systems and protect the privacy of their users led to concerted efforts to design security architectures. Interestingly, the results different project contributed thus far bear extensive similarities in terms of objectives and mechanisms. As a result, this appears to be an auspicious time for setting the corner-stone of trustworthy VC systems. Nonetheless, there is a considerable distance to cover till their deployment. This paper ponders on the road ahead. First, it presents a distillation of the state of the art, covering the perceived threat model, security requirements, and basic secure VC system components. Then, it dissects predominant assumptions and design choices and considers alternatives. Under the prism of what is necessary to render secure VC systems practical, and given possible non-technical influences, the paper attempts to chart the landscape towards the deployment of secure VC systems

Privacy in resource allocation problems

Collaborative decision-making processes help parties optimize their operations, remain competitive in their markets, and improve their performances with environmental issues. However, those parties also want to keep their data private to meet their obligations regarding various regulations and not to disclose their strategic information to the competitors. In this thesis, we study collaborative capacity allocation among multiple parties and present that (near) optimal allocations can be realized while considering the parties' privacy concerns.We first attempt to solve the multi-party resource sharing problem by constructing a single model that is available to all parties. We propose an equivalent data-private model that meets the parties' data privacy requirements while ensuring optimal solutions for each party. We show that when the proposed model is solved, each party can only get its own optimal decisions and cannot observe others' solutions. We support our findings with a simulation study.The third and fourth chapters of this thesis focus on the problem from a different perspective in which we use a reformulation that can be used to distribute the problem among the involved parties. This decomposition lets us eliminate almost all the information-sharing requirements. In Chapter 3, together with the reformulated model, we benefit from a secure multi-party computation protocol that allows parties to disguise their shared information while attaining optimal allocation decisions. We conduct a simulation study on a planning problem and show our proposed algorithm in practice. We use the decomposition approach in Chapter 4 with a different privacy notion. We employ differential privacy as our privacy definition and design a differentially private algorithm for solving the multi-party resource sharing problem. Differential privacy brings in formal data privacy guarantees at the cost of deviating slightly from optimality. We provide bounds on this deviation and discuss the consequences of these theoretical results. We show the proposed algorithm on a planning problem and present insights about its efficiency.<br/

Policy issues in interconnecting networks

To support the activities of the Federal Research Coordinating Committee (FRICC) in creating an interconnected set of networks to serve the research community, two workshops were held to address the technical support of policy issues that arise when interconnecting such networks. The workshops addressed the required and feasible technologies and architectures that could be used to satisfy the desired policies for interconnection. The results of the workshop are documented