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This paper proposes a new visual explanation-based defense mechanism, namely, FedCAMAE, against model poisoning attacks on federated learning (FL), which integrates Layer Class Activation Mapping (LayerCAM) and autoencoder to offer a scientifically more ...

Vehicular services aim to provide smart and timely services (e.g., collision warning) by taking the advantage of recent advances in artificial intelligence and employing task offloading techniques in mobile edge computing. In practice, the volume of ...

Minimizing database access latency is crucial in serverless edge computing for many applications, but databases are predominantly deployed in cloud environments, resulting in costly network round-trips. Embedding an in-process database library such as ...

The existing Internet architecture lacks support for naming locations and resolving them to the myriad addressing mechanisms we use beyond IP. We propose the Spatial Name System (SNS) that allows for the assignment of hierarchical location-based names ...

Personalized federated learning aims to address two key challenges in federated systems: performance degradation of the global model, and the lack of specificity to individual clients. Both of them are caused by client heterogeneity. Previous solutions ...

Smart Cities will cause major societal change because they will provide a comprehensive set of key services including seamless communication, intelligent transport systems, advanced healthcare platforms, urban and infrastructure management, and digital ...

IoT is a fundamental enabling technology for creating smart spaces, which can assist the effective face-to-face and online education systems. The transition to smart education (integrating IoT and AI into the education system) is appealing, which has a ...

Not all research leads to fruitful results; trying new ways or methods may surpass state of the art, but sometimes the hypothesis is not proven, the improvement is insignificant, or the system fails because of a design error done years ago in previous ...

Following the success of previous years, the main CoNEXT conference will be accompanied by this one-day Student Workshop providing a platform for graduate students in the area of computer networks and communications to learn from senior researchers in ...

Distributed ML is a rapidly evolving, interdisciplinary field bringing together techniques from distributed systems, networks and machine learning. The advent of deep learning and the pursuit of artificial intelligence has created previously unfathomable ...

Mobile devices and the immense amount and variety of data they generate are key enablers of machine learning (ML)-based applications. Traditional ML techniques have shifted toward new paradigms such as federated learning (FL) and split learning (SL) to ...

Federated learning (FL) has recently attracted much attention due to its advantages for data privacy. But every coin has two sides: protecting users' data (not requiring users to send their data) also makes FL more vulnerable to some types of attacks, ...

Modern foundational electronic IDentity (eID) systems commonly rely on biometric authentication so as to reduce both their deployment costs and the need for cryptographically capable end-user devices (e.g., smartcards, smartphones). However, this ...

In this brief statement, we trace the line of thought from Internet Multicast through to Information Centric Networking, and use this to outline what we think should have been the priorities in ICN work from the start.

The number of Internet-of-Things (IoT) devices is expected to reach 64 billion by 2025. These IoT devices will mostly use cellular networks for transferring a huge amount of IoT data to the cloud for machine learning (ML) based ...

During the COVID-19 pandemic, many smaller conferences have moved entirely online and larger ones are being held as hybrid events. Even beyond the pandemic, hybrid events reduce the carbon footprint of conference travel and makes events more accessible ...

We are pleased towelcome you to the 3rd InternationalWorkshop on AI in Networks and Distributed Systems (WAIN). The workshop aims to present high-quality researches leveraging machine learning and data analysis solutions to take full advantage of ...

Wireless jammer activity from malicious or malfunctioning devices cause significant disruption to mobile network services and user QoE degradation. In practice, detection of such activity is manually intensive and costly, taking days and weeks after the ...

In this paper we propose SCDP, a general-purpose data transport protocol for data centres that, in contrast to all other protocols proposed to date, supports efficient one-to-many and many-to-one communication, which is extremely common in modern data ...

Device‐to‐device (D2D) communication is a promising technique to enhance the spectral efficiency for 5G and beyond cellular networks. Traditionally, D2D communication was considered solely as communication directly between two closely‐located ...

This work aims to determine the statistical quality‐of‐service (QoS) guarantees of a D2D link assisted by a full‐duplex relay. We provide a closed form expression for the effective service capacity of the relay‐assisted D2D communication, in which both ...