153 citations · 169 across the 8 of their papers we have counts for
8 papers
Detecting Anomalous Microflows in IoT Volumetric Attacks via Dynamic Monitoring of MUD Activity
Ayyoob Hamza, Hassan Habibi Gharakheili, Theophilus A. Benson +2
IoT networks are increasingly becoming target of sophisticated new cyber-attacks. Anomaly-based detection methods are promising in finding new attacks, but there are certain practi…
Quantifying and Managing Impacts of Concept Drifts on IoT Traffic Inference in Residential ISP Networks
Arman Pashamokhtari, Norihiro Okui, Masataka Nakahara +3
Millions of vulnerable consumer IoT devices in home networks are the enabler for cyber crimes putting user privacy and Internet security at risk. Internet service providers (ISPs)…
Update Compression for Deep Neural Networks on the Edge
Bo Chen, Ali Bakhshi, Gustavo Batista +2
An increasing number of artificial intelligence (AI) applications involve the execution of deep neural networks (DNNs) on edge devices. Many practical reasons motivate the need to…
AdIoTack: Quantifying and Refining Resilience of Decision Tree Ensemble Inference Models against Adversarial Volumetric Attacks on IoT Networks
Arman Pashamokhtari, Gustavo Batista, Hassan Habibi Gharakheili
Machine Learning-based techniques have shown success in cyber intelligence. However, they are increasingly becoming targets of sophisticated data-driven adversarial attacks resulti…
An Open-Source Tool for Classification Models in Resource-Constrained Hardware
Lucas Tsutsui da Silva, Vinicius M. A. Souza, Gustavo E. A. P. A. Batista
Applications that need to sense, measure, and gather real-time information from the environment frequently face three main restrictions: power consumption, cost, and lack of infras…
Challenges in Benchmarking Stream Learning Algorithms with Real-world Data
Vinicius M. A. Souza, Denis M. dos Reis, Andre G. Maletzke +1
Streaming data are increasingly present in real-world applications such as sensor measurements, satellite data feed, stock market, and financial data. The main characteristics of t…
Quantifying With Only Positive Training Data
Denis dos Reis, Marcílio de Souto, Elaine de Sousa +1
Quantification is the research field that studies methods for counting the number of data points that belong to each class in an unlabeled sample. Traditionally, researchers in thi…
Flying Insect Classification with Inexpensive Sensors
Yanping Chen, Adena Why, Gustavo Batista +2
The ability to use inexpensive, noninvasive sensors to accurately classify flying insects would have significant implications for entomological research, and allow for the developm…