Related papers: ANDaNA: Anonymous Named Data Networking Applicatio…
Anonymous communication networks have emerged as crucial tools for obfuscating communication pathways and concealing user identities. However, their practical deployments face significant challenges, including susceptibility to artificial…
Peer-to-peer file sharing envisions a data-centric dissemination model, where files consisting of multiple data pieces can be shared from any peer that can offer the data or from multiple peers simultaneously. This aim, implemented at the…
Deep Neural Network (DNN), one of the most powerful machine learning algorithms, is increasingly leveraged to overcome the bottleneck of effectively exploring and analyzing massive data to boost advanced scientific development. It is not a…
The Domain Name System (DNS) is involved in practically all web activity, translating easy-to-remember domain names into Internet Protocol (IP) addresses. Due to its central role on the Internet, DNS exposes user web activity in detail. The…
Sender anonymity in network communication is an important problem, widely addressed in the literature. Mixnets, combined with onion routing, represent certainly the most concrete and effective approach achieving the above goal. In general,…
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…
Domain Name System (DNS) is a hierarchical distributed naming system for computers, services, or any resource connected to the Internet. A DNS resolves queries for URLs into IP addresses for the purpose of locating computer services and…
By requiring all data packets been cryptographically authenticatable, the Named Data Networking (NDN) architecture design provides a basic building block for secured networking. This basic NDN function requires that all entities in an NDN…
Enormous amounts of data collected from social networks or other online platforms are being published for the sake of statistics, marketing, and research, among other objectives. The consequent privacy and data security concerns have…
We propose a privacy-preserving ensemble infused enhanced Deep Neural Network (DNN) based learning framework in this paper for Internet-of-Things (IoT), edge, and cloud convergence in the context of healthcare. In the convergence, edge…
Information Centric Networking (ICN) advocates the philosophy of accessing the content independent of its location. Owing to this location independence in ICN, the routers en-route can be enabled to cache the content to serve the future…
Deep Neural Network (DNN) workloads are quickly moving from datacenters onto edge devices, for latency, privacy, or energy reasons. While datacenter networks can be protected using conventional cybersecurity measures, edge neural networks…
The current internet architecture is inefficient in fulfilling the demands of newly emerging internet applications. To address this issue, several over-the-top (OTT) application-level solutions have been employed, making the overall…
The proliferation of autonomous AI agents represents a paradigmatic shift from traditional web architectures toward collaborative intelligent systems requiring sophisticated mechanisms for discovery, authentication, capability verification,…
Named Data networking ensure data integrity so that every important data has to be signed by its owner in order to send it safely inside the network. Similarly, in NDN we have to assure that none could open the data except authorized users.…
Named-entity recognition (NER) aims at identifying entities of interest in a text. Artificial neural networks (ANNs) have recently been shown to outperform existing NER systems. However, ANNs remain challenging to use for non-expert users.…
User-facing software services are becoming increasingly reliant on remote servers to host Deep Neural Network (DNN) models, which perform inference tasks for the clients. Such services require the client to send input data to the service…
Anonymizing sensitive information in user text is essential for privacy, yet existing methods often apply uniform treatment across attributes, which can conflict with communicative intent and obscure necessary information. This is…
Utilization of Machine Learning (ML) algorithms, especially Deep Neural Network (DNN) models, becomes a widely accepted standard in many domains more particularly IoT-based systems. DNN models reach impressive performances in several…
With the development of new technologies and applications, such as the Internet of Things, smart cities, 5G, and edge computing, traditional Internet Protocol-based (IP-based) networks have been exposed as having many problems.…