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Found 8 papers, 2 papers with code
Amoeba: Circumventing ML-supported Network Censorship via Adversarial Reinforcement Learning
Specifically, we cast the problem of finding adversarial flows that will be misclassified as a sequence generation task, which we solve with Amoeba, a novel reinforcement learning algorithm that we design.
NetSentry: A Deep Learning Approach to Detecting Incipient Large-scale Network Attacks
Machine Learning (ML) techniques are increasingly adopted to tackle ever-evolving high-profile network attacks, including DDoS, botnet, and ransomware, due to their unique ability to extract complex patterns hidden in data streams.
CloudLSTM: A Recurrent Neural Model for Spatiotemporal Point-cloud Stream Forecasting
This paper introduces CloudLSTM, a new branch of recurrent neural models tailored to forecasting over data streams generated by geospatial point-cloud sources.
Multi-Service Mobile Traffic Forecasting via Convolutional Long Short-Term Memories
Network slicing is increasingly used to partition network infrastructure between different mobile services.
Driver Behavior Recognition via Interwoven Deep Convolutional Neural Nets with Multi-stream Inputs
Experiments conducted with a dataset that we collect in a mock-up car environment demonstrate that the proposed InterCNN with MobileNet convolutional blocks can classify 9 different behaviors with 73. 97% accuracy, and 5 'aggregated' behaviors with 81. 66% accuracy.
Deep Learning in Mobile and Wireless Networking: A Survey
One potential solution is to resort to advanced machine learning techniques to help managing the rise in data volumes and algorithm-driven applications.
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ZipNet-GAN: Inferring Fine-grained Mobile Traffic Patterns via a Generative Adversarial Neural Network
Large-scale mobile traffic analytics is becoming essential to digital infrastructure provisioning, public transportation, events planning, and other domains.
Breaking Fitness Records without Moving: Reverse Engineering and Spoofing Fitbit
In this paper, we provide an in-depth security analysis of the operation of fitness trackers commercialized by Fitbit, the wearables market leader.
Cryptography and Security
