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The last few years have seen an increasing wave of attacks with serious economic and privacy damages, which evinces the need for accurate Network Intrusion Detection Systems (NIDS). Recent works propose the use of Machine Learning (ML)…

Knowledge graph (KG) plays an increasingly important role in recommender systems. A recent technical trend is to develop end-to-end models founded on graph neural networks (GNNs). However, existing GNN-based models are coarse-grained in…

The client-server model is known to scale badly without redundant servers and caches. Information-Centric Networks (ICN) are an alternative designed to lessen that problem by distributing load to intermediary routers, lowering the bar to…

Graph data contains rich node features and unique edge information, which have been applied across various domains, such as citation networks or recommendation systems. Graph Neural Networks (GNNs) are specialized for handling such data and…

Partitioned DNN inference is a promising approach for latency-sensitive intelligent services in edge networks, since it allows different parts of a model to be executed across end devices, edge servers, and the cloud. However, in a…

Name-oriented networks introduce the vision of an information-centric, secure, globally available publish-subscribe infrastructure. Current approaches concentrate on unicast-based pull mechanisms and thereby fall short in automatically…

In this paper, we investigate the Domain Name System (DNS) over QUIC (DoQ) and propose a non-disruptive extension, which can greatly reduce DoQ's resource consumption. This extension can benefit all DNS clients - especially Internet of…

With the frequent happening of privacy leakage and the enactment of privacy laws across different countries, data owners are reluctant to directly share their raw data and labels with any other party. In reality, a lot of these raw data are…

Graph condensation (GC), which reduces the size of a large-scale graph by synthesizing a small-scale condensed graph as its substitution, has benefited various graph learning tasks. However, existing GC methods rely on centralized data…

This paper explores the feasibility, advantages, and challenges of an ICN-based approach in the Internet of Things. We report on the first NDN experiments in a life-size IoT deployment, spread over tens of rooms on several floors of a…

Robust object tracking requires knowledge of tracked objects' appearance, motion and their evolution over time. Although motion provides distinctive and complementary information especially for fast moving objects, most of the recent…

Recent literature suggests that the Internet of Things (IoT) scales much better in an Information-Centric Networking (ICN) model instead of the current host-centric Internet Protocol (IP) model. In particular, the Named Data Networking…

In this paper, we present Conjoint Attentions (CAs), a class of novel learning-to-attend strategies for graph neural networks (GNNs). Besides considering the layer-wise node features propagated within the GNN, CAs can additionally…

Mobility has become a basic premise of network communications, thereby requiring a native integration into 5G networks. Despite the numerous efforts to propose and to standardize effective mobility management models for IP, the result is a…

In this paper, a new routing algorithm based on a flooding method is introduced. Flooding techniques have been used previously, e.g. for broadcasting the routing table in the ARPAnet [1] and other special purpose networks [3][4][5].…

Graph research, the systematic study of interconnected data points represented as graphs, plays a vital role in capturing intricate relationships within networked systems. However, in the real world, as graphs scale up, concerns about data…

Fog computing, a non-trivial extension of cloud computing to the edge of the network, has great advantage in providing services with a lower latency. In smart grid, the application of fog computing can greatly facilitate the collection of…

Information Centric Networks (ICNs) have emerged in recent years as a new networking paradigm for the next-generation Internet. The primary goal of these networks is to provide effective mechanisms for content distribution and retrieval…

Name lookup is a key technology for the forwarding plane of content router in Named Data Networking (NDN). To realize the efficient name lookup, what counts is deploying a highperformance index in content routers. So far, the proposed…

This paper discusses challenges and opportunities of considering the Metaverse as an Information-Centric Network (ICN). The Web today essentially represents a data-centric application layer: data named by URLs is manipulated with REST…