379 research outputs found
Graph-Hist: Graph Classification from Latent Feature Histograms With Application to Bot Detection
Neural networks are increasingly used for graph classification in a variety
of contexts. Social media is a critical application area in this space, however
the characteristics of social media graphs differ from those seen in most
popular benchmark datasets. Social networks tend to be large and sparse, while
benchmarks are small and dense. Classically, large and sparse networks are
analyzed by studying the distribution of local properties. Inspired by this, we
introduce Graph-Hist: an end-to-end architecture that extracts a graph's latent
local features, bins nodes together along 1-D cross sections of the feature
space, and classifies the graph based on this multi-channel histogram. We show
that Graph-Hist improves state of the art performance on true social media
benchmark datasets, while still performing well on other benchmarks. Finally,
we demonstrate Graph-Hist's performance by conducting bot detection in social
media. While sophisticated bot and cyborg accounts increasingly evade
traditional detection methods, they leave artificial artifacts in their
conversational graph that are detected through graph classification. We apply
Graph-Hist to classify these conversational graphs. In the process, we confirm
that social media graphs are different than most baselines and that Graph-Hist
outperforms existing bot-detection models
Energy efficient mining on a quantum-enabled blockchain using light
We outline a quantum-enabled blockchain architecture based on a consortium of
quantum servers. The network is hybridised, utilising digital systems for
sharing and processing classical information combined with a fibre--optic
infrastructure and quantum devices for transmitting and processing quantum
information. We deliver an energy efficient interactive mining protocol enacted
between clients and servers which uses quantum information encoded in light and
removes the need for trust in network infrastructure. Instead, clients on the
network need only trust the transparent network code, and that their devices
adhere to the rules of quantum physics. To demonstrate the energy efficiency of
the mining protocol, we elaborate upon the results of two previous experiments
(one performed over 1km of optical fibre) as applied to this work. Finally, we
address some key vulnerabilities, explore open questions, and observe
forward--compatibility with the quantum internet and quantum computing
technologies.Comment: 25 pages, 5 figure
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