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Technical Perspective: Traffic Classification in the Era of Deep Learning
From Communications of the ACM

Technical Perspective: Traffic Classification in the Era of Deep Learning

"Traffic Classification in an Increasingly Encrypted Web," by Iman Akbari et al., does a great job in reviewing related work in the network traffic classification...

Traffic Classification in an Increasingly Encrypted Web
From Communications of the ACM

Traffic Classification in an Increasingly Encrypted Web

In this paper, we design a novel feature engineering approach used for encrypted Web protocols, and develop a neural network architecture based on stacked long...

Technical Perspective: Physical Layer Resilience through Deep Learning in Software Radios
From Communications of the ACM

Technical Perspective: Physical Layer Resilience through Deep Learning in Software Radios

"Polymorphic Wireless Receivers," by Francesco Restuccia and Tommaso Melodia, tackles the problem of physical layer resilience in wireless systems from a completely...

Polymorphic Wireless Receivers
From Communications of the ACM

Polymorphic Wireless Receivers

We introduce PolymoRF, a deep learning-based polymorphic receiver able to reconfigure itself in real time based on the inferred waveform parameters.

Technical Perspective: hXDP
From Communications of the ACM

Technical Perspective: hXDP: Light and Efficient Packet Processing Offload

In "hXDP: Efficient Software Packet Processing on FPGA NICs," the authors offer an interesting solution to bridging the performance gap between the CPU and the...

hXDP
From Communications of the ACM

hXDP: Efficient Software Packet Processing on FPGA NICs

We present hXDP, a solution to run on FPGAs software packet processing tasks described with the eBPF technology and targeting the Linux's eXpress Data Path.

Technical Perspective: Leveraging Social Context for Fake News Detection
From Communications of the ACM

Technical Perspective: Leveraging Social Context for Fake News Detection

In "FANG," the authors focus on a strategy of automatically detecting disinformation campaigns on online media with a new graph-based, contextual technique for...

FANG
From Communications of the ACM

FANG: Leveraging Social Context for Fake News Detection Using Graph Representation

We propose Factual News Graph (FANG), a novel graphical social context representation and learning framework for fake news detection.

Technical Perspective: On Proofs, Entanglement, and Games
From Communications of the ACM

Technical Perspective: On Proofs, Entanglement, and Games

"MIP* = RE," by Zhengfeng Ji et al., studies quantum interactive proofs.

MIP* = RE
From Communications of the ACM

MIP* = RE

In this work, we study a fourth modification to the notion of efficient verification that originates in the study of quantum entanglement.

Technical Perspective: Tracking Pandemic-Driven Internet Traffic
From Communications of the ACM

Technical Perspective: Tracking Pandemic-Driven Internet Traffic

"A Year in Lockdown," by Anja Feldmann, et al., offers a detailed look at how Internet traffic changed during the COVID-19 pandemic.

A Year in Lockdown
From Communications of the ACM

A Year in Lockdown: How the Waves of COVID-19 Impact Internet Traffic

We review the impact of the first year of the COVID-19 pandemic on Internet traffic in order to analyze its performance.

Technical Perspective: An Elegant Model for Deriving Equations
From Communications of the ACM

Technical Perspective: An Elegant Model for Deriving Equations

"Deriving Equations from Sensor Data Using Dimensional Function Synthesis," by Vasileios Tsoutsouras, et al., addresses the key problem of discovering relationships...

Deriving Equations from Sensor Data Using Dimensional Function Synthesis
From Communications of the ACM

Deriving Equations from Sensor Data Using Dimensional Function Synthesis

We present a new method, which we call dimensional function synthesis, for deriving functions that model the relationship between multiple signals in a physical...

From Communications of the ACM

Technical Perspective: Race Logic Presents a Novel Form of Encoding

"In-Sensor Classification With Boosted Race Trees," by Georgios Tzimpragos, et al., proposes a surprising, novel, and creative approach to post-Moore's Law computing...

In-Sensor Classification With Boosted Race Trees
From Communications of the ACM

In-Sensor Classification With Boosted Race Trees

We demonstrate the potential of a novel form of encoding, race logic, in which information is represented as the delay in the arrival of a signal.

From Communications of the ACM

Technical Perspective: A Chiplet Prototype System for Deep Learning Inference

"Simba," by Yakun Sophia Shao, et al., presents a scalable deep learning accelerator architecture that tackles issues ranging from chip integration technology to...

Simba
From Communications of the ACM

Simba: Scaling Deep-Learning Inference with Chiplet-Based Architecture

This work investigates and quantifies the costs and benefits of using multi-chip-modules with fine-grained chiplets for deep learning inference, an application...

From Communications of the ACM

Technical Perspective: Solving the Signal Reconstruction Problem at Scale

"Scalable Signal Reconstruction for a Broad Range of Applications," by Abolfazl Asudeh, et al. shows that algorithmic insights about SRP, combined with database...

Scalable Signal Reconstruction for a Broad Range of Applications
From Communications of the ACM

Scalable Signal Reconstruction for a Broad Range of Applications

Most of the common approaches for solving signal reconstruction problem do not scale to large problem sizes. We propose a novel and scalable algorithm for solving...
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