1,137 research outputs found
Realization of blockchain in named data networking-based internet-of-vehicles
The revolution of Internet-of-vehicles (IoV) has stimulated a substantial response from academia, research and industry due to its massive potential to improve overall transportation. Current IoV faces huge challenges due to its reliance on the IP-based network architecture. Therefore, Named Data Networking (NDN) is proposed as a promising architecture to solve issues posed by IP-based systems. Recently, Blockchains (BCs) are utilized within IoV to increase network security. However, the integration of BC within NDN-enabled IoV is still an open research problem. In this study, we proposed a novel tier-based architecture known as “Blockchain in NDN-enabled Internet-of-Vehicles (BINDN)” which can support BC within NDN-enabled IoV. BINDN can be used as a reference architecture to design security solutions in NDN-enabled IoV using BC. Further, it provides an extensive set of applications including IoV security, trust management and privacy enhancements. Moreover, we highlighted major challenges and issues when integrating BC within NDN-enabled IoV.N/
Named Data Networking in Vehicular Ad hoc Networks: State-of-the-Art and Challenges
International audienceInformation-Centric Networking (ICN) has been proposed as one of the future Internet architectures. It is poised to address the challenges faced by today's Internet that include, but not limited to, scalability, addressing, security, and privacy. Furthermore, it also aims at meeting the requirements for new emerging Internet applications. To realize ICN, Named Data Networking (NDN) is one of the recent implementations of ICN that provides a suitable communication approach due to its clean slate design and simple communication model. There are a plethora of applications realized through ICN in different domains where data is the focal point of communication. One such domain is Intelligent Transportation System (ITS) realized through Vehicular Ad hoc NETwork (VANET) where vehicles exchange information and content with each other and with the infrastructure. To date, excellent research results have been yielded in the VANET domain aiming at safe, reliable, and infotainment-rich driving experience. However, due to the dynamic topologies, host-centric model, and ephemeral nature of vehicular communication, various challenges are faced by VANET that hinder the realization of successful vehicular networks and adversely affect the data dissemination, content delivery, and user experiences. To fill these gaps, NDN has been extensively used as underlying communication paradigm for VANET. Inspired by the extensive research results in NDN-based VANET, in this paper, we provide a detailed and systematic review of NDN-driven VANET. More precisely, we investigate the role of NDN in VANET and discuss the feasibility of NDN architecture in VANET environment. Subsequently, we cover in detail, NDN-based naming, routing and forwarding, caching, mobility, and security mechanism for VANET. Furthermore, we discuss the existing standards, solutions, and simulation tools used in NDN-based VANET. Finally, we also identify open challenges and issues faced by NDN-driven VANET and highlight future research directions that should be addressed by the research community
BC4LLM: Trusted Artificial Intelligence When Blockchain Meets Large Language Models
In recent years, artificial intelligence (AI) and machine learning (ML) are
reshaping society's production methods and productivity, and also changing the
paradigm of scientific research. Among them, the AI language model represented
by ChatGPT has made great progress. Such large language models (LLMs) serve
people in the form of AI-generated content (AIGC) and are widely used in
consulting, healthcare, and education. However, it is difficult to guarantee
the authenticity and reliability of AIGC learning data. In addition, there are
also hidden dangers of privacy disclosure in distributed AI training. Moreover,
the content generated by LLMs is difficult to identify and trace, and it is
difficult to cross-platform mutual recognition. The above information security
issues in the coming era of AI powered by LLMs will be infinitely amplified and
affect everyone's life. Therefore, we consider empowering LLMs using blockchain
technology with superior security features to propose a vision for trusted AI.
This paper mainly introduces the motivation and technical route of blockchain
for LLM (BC4LLM), including reliable learning corpus, secure training process,
and identifiable generated content. Meanwhile, this paper also reviews the
potential applications and future challenges, especially in the frontier
communication networks field, including network resource allocation, dynamic
spectrum sharing, and semantic communication. Based on the above work combined
and the prospect of blockchain and LLMs, it is expected to help the early
realization of trusted AI and provide guidance for the academic community
Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms
The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications
Integration of ICN and MEC in 5G and beyond networks : mutual benefits, use cases, challenges, standardization, and future research
Multi-access Edge Computing (MEC) is a novel edge computing paradigm that moves cloudbased processing and storage capabilities closer to mobile users by implementing server resources in the access nodes. MEC helps fulfill the stringent requirements of 5G and beyond networks to offer anytimeanywhere connectivity for many devices with ultra-low delay and huge bandwidths. Information-Centric Networking (ICN) is another prominent network technology that builds on a content-centric network architecture to overcome host-centric routing/operation shortcomings and to realize efficient pervasive and ubiquitous networking. It is envisaged to be employed in Future Internet including Beyond 5G (B5G) networks. The consolidation of ICN with MEC technology offers new opportunities to realize that vision and serve advanced use cases. However, various integration challenges are yet to be addressed to enable the wide-scale co-deployment of ICN with MEC in future networks. In this paper, we discuss and elaborate on ICN MEC integration to provide a comprehensive survey with a forward-looking perspective for B5G networks. In that regard, we deduce lessons learned from related works (for both 5G and B5G networks). We present ongoing standardization activities to highlight practical implications of such efforts. Moreover, we render key B5G use cases and highlight the role for ICN MEC integration for addressing their requirements. Finally, we layout research challenges and identify potential research directions. For this last contribution, we also provide a mapping of the latter to ICN integration challenges and use cases
Access Control Mechanisms in Named Data Networks:A Comprehensive Survey
Information-Centric Networking (ICN) has recently emerged as a prominent
candidate for the Future Internet Architecture (FIA) that addresses existing
issues with the host-centric communication model of the current TCP/IP-based
Internet. Named Data Networking (NDN) is one of the most recent and active ICN
architectures that provides a clean slate approach for Internet communication.
NDN provides intrinsic content security where security is directly provided to
the content instead of communication channel. Among other security aspects,
Access Control (AC) rules specify the privileges for the entities that can
access the content. In TCP/IP-based AC systems, due to the client-server
communication model, the servers control which client can access a particular
content. In contrast, ICN-based networks use content names to drive
communication and decouple the content from its original location. This
phenomenon leads to the loss of control over the content causing different
challenges for the realization of efficient AC mechanisms. To date,
considerable efforts have been made to develop various AC mechanisms in NDN. In
this paper, we provide a detailed and comprehensive survey of the AC mechanisms
in NDN. We follow a holistic approach towards AC in NDN where we first
summarize the ICN paradigm, describe the changes from channel-based security to
content-based security and highlight different cryptographic algorithms and
security protocols in NDN. We then classify the existing AC mechanisms into two
main categories: Encryption-based AC and Encryption-independent AC. Each
category has different classes based on the working principle of AC (e.g.,
Attribute-based AC, Name-based AC, Identity-based AC, etc). Finally, we present
the lessons learned from the existing AC mechanisms and identify the challenges
of NDN-based AC at large, highlighting future research directions for the
community.Comment: This paper has been accepted for publication by the ACM Computing
Surveys. The final version will be published by the AC
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