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Found 10 papers, 0 papers with code
A Cyber Threat Intelligence Sharing Scheme based on Federated Learning for Network Intrusion Detection
The framework has been designed and evaluated in this paper by using two key datasets in a NetFlow format known as NF-UNSW-NB15-v2 and NF-BoT-IoT-v2.
Feature Extraction for Machine Learning-based Intrusion Detection in IoT Networks
In an analysis of related works, it was observed that most researchers aim to obtain better classification results by using a set of untried combinations of Feature Reduction (FR) and Machine Learning (ML) techniques on NIDS datasets.
Security and Privacy for Artificial Intelligence: Opportunities and Challenges
The increased adoption of Artificial Intelligence (AI) presents an opportunity to solve many socio-economic and environmental challenges; however, this cannot happen without securing AI-enabled technologies.
Mitigating the Impact of Adversarial Attacks in Very Deep Networks
In it, a Defensive Feature Layer (DFL) is integrated with a well-known DNN architecture which assists in neutralizing the effects of illegitimate perturbation samples in the feature space.
A Deep Marginal-Contrastive Defense against Adversarial Attacks on 1D Models
Several research studies have been conducted to address this issue and build more robust deep learning models.
Federated TON_IoT Windows Datasets for Evaluating AI-based Security Applications
This paper presents the description of new datasets, the so-called ToN_IoT, which involve federated data sources collected from telemetry datasets of IoT services, operating system datasets of Windows and Linux, and datasets of network traffic.
Cryptography and Security
Densely Connected Residual Network for Attack Recognition
High false alarm rate and low detection rate are the major sticking points for unknown threat perception.
Enhancing network forensics with particle swarm and deep learning: The particle deep framework
The popularity of IoT smart things is rising, due to the automation they provide and its effects on productivity.
Pelican: A Deep Residual Network for Network Intrusion Detection
To address this problem, the network intrusion detection system (NIDS) has been used.
Towards the Development of Realistic Botnet Dataset in the Internet of Things for Network Forensic Analytics: Bot-IoT Dataset
The proliferation of IoT systems, has seen them targeted by malicious third parties.
Cryptography and Security
