On the Convergence of Artificial Intelligence and Distributed Ledger Technology: A Scoping Review and Future Research Agenda

Developments in Artificial Intelligence (AI) and Distributed Ledger Technology (DLT) currently lead to lively debates in academia and practice. AI processes data to perform tasks that were previously thought possible only for humans. DLT has the potential to create consensus over data among a group of participants in uncertain environments. In recent research, both technologies are used in similar and even the same systems. Examples include the design of secure distributed ledgers or the creation of allied learning systems distributed across multiple nodes. This can lead to technological convergence, which in the past, has paved the way for major innovations in information technology. Previous work highlights several potential benefits of the convergence of AI and DLT but only provides a limited theoretical framework to describe upcoming real-world integration cases of both technologies. We aim to contribute by conducting a systematic literature review on previous work and providing rigorously derived future research opportunities. This work helps researchers active in AI or DLT to overcome current limitations in their field, and practitioners to develop systems along with the convergence of both technologies

Adversarial behaviours in mixing coins under incomplete information

Criminals can launder crypto-currencies through mixing coins, whose original purpose is preservation of privacy in the presence of traceability. Therefore, it is essential to elaborately design mixing polices to achieve both privacy and anti-money laundering. Existing work on mixing policies relies on the knowledge of a blacklist. However, these policies are paralysed under the scenario where the blacklist is unknown or evolving. In this paper, we regard the above scenario as games under incomplete information where parties put down a deposit for the quality of coins, which is suitably managed by a smart contract in case of mixing bad coins. We extend the poison and haircut policies to incomplete information games, where the blacklist is updated after mixing. We prove the existence of equilibria for the improved polices, while it is known that there is no equilibria in the original poison and haircut policies, where blacklist is public known. Furthermore, we propose a seminal suicide policy: the one who mixes more bad coins will be punished by not having the deposit refunded. Thus, parties have no incentives to launder money by leveraging mixing coins. In effect, all three policies contrast money laundering while preserving privacy under incomplete information. Finally, we simulate and verify the validity of these policies

Judicial Intelligent Assistant System: Extracting Events from Divorce Cases to Detect Disputes for the Judge

In formal procedure of civil cases, the textual materials provided by different parties describe the development process of the cases. It is a difficult but necessary task to extract the key information for the cases from these textual materials and to clarify the dispute focus of related parties. Currently, officers read the materials manually and use methods, such as keyword searching and regular matching, to get the target information. These approaches are time-consuming and heavily depending on prior knowledge and carefulness of the officers. To assist the officers to enhance working efficiency and accuracy, we propose an approach to detect disputes from divorce cases based on a two-round-labeling event extracting technique in this paper. We implement the Judicial Intelligent Assistant (JIA) system according to the proposed approach to 1) automatically extract focus events from divorce case materials, 2) align events by identifying co-reference among them, and 3) detect conflicts among events brought by the plaintiff and the defendant. With the JIA system, it is convenient for judges to determine the disputed issues. Experimental results demonstrate that the proposed approach and system can obtain the focus of cases and detect conflicts more effectively and efficiently comparing with existing method.Comment: 20 page

Push, Pull, and Spill: A Transdisciplinary Case Study in Municipal Open Government

Municipal open data raises hopes and concerns. The activities of cities produce a wide array of data, data that is vastly enriched by ubiquitous computing. Municipal data is opened as it is pushed to, pulled by, and spilled to the public through online portals, requests for public records, and releases by cities and their vendors, contractors, and partners. By opening data, cities hope to raise public trust and prompt innovation. Municipal data, however, is often about the people who live, work, and travel in the city. By opening data, cities raise concern for privacy and social justice. This article presents the results of a broad empirical exploration of municipal data release in the City of Seattle. In this research, parties affected by municipal practices expressed their hopes and concerns for open data. City personnel from eight prominent departments described the reasoning, procedures, and controversies that have accompanied their release of data. All of the existing data from the online portal for the city were joined to Municipal open data raises hopes and concerns. The activities of cities produce a wide array of data, data that is vastly enriched by ubiquitous computing. Municipal data is opened as it is pushed to, pulled by, and spilled to the public through online portals, requests for public records, and releases by cities and their vendors, contractors, and partners. By opening data, cities hope to raise public trust and prompt innovation. Municipal data, however, is often about the people who live, work, and travel in the city. By opening data, cities raise concern for privacy and social justice. Results suggest the need for more comprehensive measures to manage the risk latent in opening city data. Cities should maintain inventories of data assets, produce data management plans pertaining to the activities of departments, and develop governance structures to deal with issues as they arise—centrally and amongst the various departments—with ex ante and ex post protocols to govern the push, pull, and spill of data. In addition, cities should consider conditioned access to pushed data, conduct audits and training around public records requests, and develop standardized model contracts to protect against the spill of data by third parties

Security Technologies and Methods for Advanced Cyber Threat Intelligence, Detection and Mitigation

The rapid growth of the Internet interconnectivity and complexity of communication systems has led us to a significant growth of cyberattacks globally often with severe and disastrous consequences. The swift development of more innovative and effective (cyber)security solutions and approaches are vital which can detect, mitigate and prevent from these serious consequences. Cybersecurity is gaining momentum and is scaling up in very many areas. This book builds on the experience of the Cyber-Trust EU project’s methods, use cases, technology development, testing and validation and extends into a broader science, lead IT industry market and applied research with practical cases. It offers new perspectives on advanced (cyber) security innovation (eco) systems covering key different perspectives. The book provides insights on new security technologies and methods for advanced cyber threat intelligence, detection and mitigation. We cover topics such as cyber-security and AI, cyber-threat intelligence, digital forensics, moving target defense, intrusion detection systems, post-quantum security, privacy and data protection, security visualization, smart contracts security, software security, blockchain, security architectures, system and data integrity, trust management systems, distributed systems security, dynamic risk management, privacy and ethics

Security Technologies and Methods for Advanced Cyber Threat Intelligence, Detection and Mitigation

The rapid growth of the Internet interconnectivity and complexity of communication systems has led us to a significant growth of cyberattacks globally often with severe and disastrous consequences. The swift development of more innovative and effective (cyber)security solutions and approaches are vital which can detect, mitigate and prevent from these serious consequences. Cybersecurity is gaining momentum and is scaling up in very many areas. This book builds on the experience of the Cyber-Trust EU project’s methods, use cases, technology development, testing and validation and extends into a broader science, lead IT industry market and applied research with practical cases. It offers new perspectives on advanced (cyber) security innovation (eco) systems covering key different perspectives. The book provides insights on new security technologies and methods for advanced cyber threat intelligence, detection and mitigation. We cover topics such as cyber-security and AI, cyber-threat intelligence, digital forensics, moving target defense, intrusion detection systems, post-quantum security, privacy and data protection, security visualization, smart contracts security, software security, blockchain, security architectures, system and data integrity, trust management systems, distributed systems security, dynamic risk management, privacy and ethics