Vul-Mirror: A Few-Shot Learning Method for Discovering Vulnerable Code Clone [PDF]
EAI Endorsed Transactions on Security and Safety, 2020 It is quite common for reusing code in soft development, which may lead to the wide spread of the vulnerability, soautomatic detection of vulnerable code clone is becoming more and more important.
Yuan He +3 more
doaj +1 more source
Identify Vulnerability Fix Commits Automatically Using Hierarchical Attention Network [PDF]
EAI Endorsed Transactions on Security and Safety, 2020 The application of machine learning and deep learning in the field of vulnerability detection is a hot topic in security research, but currently it faces the problem of lack of dataset.
Mingxin Sun +4 more
doaj +1 more source
A Novel Deep Learning-Based Intrusion Detection System for IoT Networks
De Computis, 2023 The impressive growth rate of the Internet of Things (IoT) has drawn the attention of cybercriminals more than ever. The growing number of cyber-attacks on IoT devices and intermediate communication media backs the claim.
A. Awajan
semanticscholar +1 more source
E-GraphSAGE: A Graph Neural Network based Intrusion Detection System for IoT [PDF]
IEEE/IFIP Network Operations and Management Symposium, 2021 This paper presents a new Network Intrusion Detection System (NIDS) based on Graph Neural Networks (GNNs). GNNs are a relatively new sub-field of deep neural networks, which can leverage the inherent structure of graph-based data. Training and evaluation
Wai Weng Lo +4 more
semanticscholar +1 more source
Kitsune: An Ensemble of Autoencoders for Online Network Intrusion Detection [PDF]
Network and Distributed System Security Symposium, 2018 Neural networks have become an increasingly popular solution for network intrusion detection systems (NIDS). Their capability of learning complex patterns and behaviors make them a suitable solution for differentiating between normal traffic and network ...
Yisroel Mirsky +3 more
semanticscholar +1 more source
A Deep Learning Model for Network Intrusion Detection with Imbalanced Data
Electronics, 2022 With an increase in the number and types of network attacks, traditional firewalls and data encryption methods can no longer meet the needs of current network security.
Yanfang Fu +4 more
semanticscholar +1 more source
Anterior Deep Bite Malocclusion Treated with Connecticut Intrusion Arch: Biomechanical Consideration [PDF]
Journal of Clinical and Diagnostic Research, 2014 Most Class II division 2 malocclusion manifest a severe deep bite, the orthodontic correction of deep overbite can be achieved with several mechanisms one such mechanics is true intrusion of anterior teeth.
Safiya Sana +4 more
doaj +1 more source
Sources and sinks of bottom water oxygen in a seasonally hypoxic fjord
Frontiers in Marine Science, 2023 Deoxygenation of the ocean has been occurring over the last half century, particularly in poorly ventilated coastal waters. In coastal and estuarine environments, both the water column and sediments play key roles in controlling oxygen variability.
Subhadeep Rakshit +3 more
doaj +1 more source
Intelligent Deep Learning for Anomaly-Based Intrusion Detection in IoT Smart Home Networks
Mathematics, 2022 The Internet of Things (IoT) is a tremendous network based on connected smart devices. These networks sense and transmit data by using advanced communication standards and technologies.
Nazia Butt +6 more
doaj +1 more source
Similarity Based Feature Transformation for Network Anomaly Detection
IEEE Access, 2020 The fundamental objective behind any network intrusion detection system is to automate the detection process whenever intrusions occur in the network.
Arun Nagaraja +5 more
doaj +1 more source