Search Results (4)

At the Group of Seven (G7) summit held on 13–15 June in 2024, the Group’s leaders committed to establishing a collective cyber security framework and reinforcing the work of the cyber security working group to manage the risks targeting energy systems. Likewise, oil and electricity, and natural gas rely on complex and interdependent technologies and communication networks from production to consumption. The preparedness to handle cyber security threats in the energy infrastructures among decision makers, planners, and the industry in a concerted manner signifies that cyber security is becoming more appreciated. Therefore, considering the ambition and achievement of the G7 countries towards energy and cyber sovereignty, this paper’s focus and research question aims to explore the potential existence of the cyber governance alliance in the gas subsector within the G7. The objective of this paper is twofold. First, it explores the potential of the G7, the world’s seven largest advanced economies, to lead on a nascent cyber governance for risk management in the gas sector. The qualitative analysis conducted through the institutional analysis and design method examines up-to-date data involving mainly state actors. Second, by drawing on LNG, one of the world’s fastest growing energy types in the coming decades, the paper points out the need for further research on the transnational governance operating through public–private engagement to address the cyber risks to gas systems. While the paper makes an empirical contribution to the field of security governance and a practical contribution to security consulting, its limitations rely on the necessity to also conduct a quantitative enquiry, which would necessitate, among others, a review of the literature in the G7 countries, and a group of researchers from academia and practitioners to obtain a sense of the cyberspace in the energy reality. Full article

Smart contracts, programs running on a blockchain, play a crucial role in driving Web 3.0 across a variety of domains, such as digital finance and future networks. However, they currently face significant security vulnerabilities that could result in potential risks and losses. This paper outlines the inherent vulnerabilities of smart contracts, both those typical of their applications and those unique to Web 3.0 applications. We then systematically classify the techniques based on their core approach to detecting vulnerabilities in smart contracts. Using these approaches, we conduct a comparative analysis of existing tools in terms of their vulnerability coverage, detection effectiveness, open-source availability, and integration capabilities. Finally, we present the Co-Governed Sovereignty Multi-Identifier Network (CoG-MIN) as a case study to demonstrate the significance of smart contract application security in establishing a community with a shared future in cyberspace during the Web 3.0 era and anticipate future research directions with challenges. To conclude, this study addresses the gap in integrating existing smart contract security research with the advancement of Web 3.0 development, while also providing recommendations for future research directions. Full article

Prevention of cybercrime is one of the missions of Law Enforcement Agencies (LEA) aiming to protect and guarantee sovereignty in the cyberspace. In this regard, online sex crimes are among the principal ones to prevent, especially those where a child is abused. The paper at hand proposes $C^3$-Sex, a smart chatbot that uses Natural Language Processing (NLP) to interact with suspects in order to profile their interest regarding online child sexual abuse. This solution is based on our Artificial Conversational Entity (ACE) that connects to different online chat services to start a conversation. The ACE is designed using generative and rule-based models in charge of generating the posts and replies that constitute the conversation from the chatbot side. The proposed solution also includes a module to analyze the conversations performed by the chatbot and calculate a set of 25 features that describes the suspect’s behavior. After 50 days of experiments, the chatbot generated a dataset with 7199 profiling vectors with the features associated to each suspect. Afterward, we applied an unsupervised method to describe the results that differentiate three groups, which we categorize as indifferent, interested, and pervert. Exhaustive analysis is conducted to validate the applicability and advantages of our solution. Full article

The domain name system (DNS) is an important infrastructure of the Internet, providing domain name resolution services for almost all Internet communication systems. However, the current DNS is centrally managed, leading to unfair sovereignty of the Internet among countries. A domestic DNS is unable to work normally, noted as isolated management risk (IMR), especially when the national network is isolated from the rest of the Internet. To improve understanding of the DNS isolated management risk for better DNS resource deployment, it is critical to determine how serious the IMR is among various countries. In order to quantify DNS isolated management risk, this paper proposed an effective approach to collect DNS resolution demand data from the network used by various intelligent devices and to conduct data analysis to estimate isolated management risk of certain country’s domestic DNSs. Our idea is to quantify the domain name resolution demand and its relationship with the overseas resolution processes. We further used our quantitative method to compare the IMR of the USA and China and analyzed the difference between them. Full article