Industrial Symbiotic Networks as Coordinated Games

We present an approach for implementing a specific form of collaborative industrial practices-called Industrial Symbiotic Networks (ISNs)-as MC-Net cooperative games and address the so called ISN implementation problem. This is, the characteristics of ISNs may lead to inapplicability of fair and stable benefit allocation methods even if the collaboration is a collectively desired one. Inspired by realistic ISN scenarios and the literature on normative multi-agent systems, we consider regulations and normative socioeconomic policies as two elements that in combination with ISN games resolve the situation and result in the concept of coordinated ISNs.Comment: 3 pages, Proc. of the 17th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2018

Arguing satisfaction of security requirements

This chapter presents a process for security requirements elicitation and analysis, based around the construction of a satisfaction argument for the security of a system. The process starts with the enumeration of security goals based on assets in the system, then uses these goals to derive security requirements in the form of constraints. Next, a satisfaction argument for the system is constructed, using a problem-centered representation, a formal proof to analyze properties that can be demonstrated, and structured informal argumentation of the assumptions exposed during construction of the argument. Constructing the satisfaction argument can expose missing and inconsistent assumptions about system context and behavior that effect security, and a completed argument provides assurances that a system can respect its security requirements

Machine Understandable Contracts with Deep Learning

This research investigates the automatic translation of contracts to computer understandable rules trough Natural Language Processing. The most challenging aspect, which is studied throughout this paper, is to understand the meaning of the contract and express it into a structured format. This problem can be reduced to the Named Entity Recognition and Rule Extraction tasks, the latter handles the extraction of terms and conditions. These two problems are difficult, but deep learning models can tackle them. We think that this paper is the first work to approach Rule Extraction with deep learning. This method is data-hungry, so the research also introduces data sets for these two tasks. Additionally, it contributes to the literature by introducing Law-Bert, a model based on BERT which is pre-trained on unlabelled contracts. The results obtained on Named Entity Recognition and Rule Extraction show that pre-training on contracts has a positive effect on performance for the downstream tasks

A translator for automated code generation for service-based systems

Service based systems are playing a major role in industry today, everything from the verification of credit cards to booking airplane reservations are using some form of a service based approach. This unfortunately brings up a really big problem, how do we know that these services are actually doing what they are supposed to? Or, how do we know the service based system doesn\u27t get somehow compromised when handling sensitive information.;A collaborative project involving Arizona State University and West Virginia University began in 2004 to first create a language, called alpha-calculus. We can prove that the code written in alpha-calculus adheres to the requirements. The next step was to create a translator that could convert code written in alpha-calculus to Secure Operations Language (SOL), which could then be used to develop service-based systems.;While research has been done in this area, the alpha-calculus to SOL translator provides a real world solution to creating provable/verifiable service based systems