A survey on deep learning for cybersecurity: Progress, challenges, and opportunities

M Macas, C Wu, W Fuertes - Computer Networks, 2022 - Elsevier
As the number of Internet-connected systems rises, cyber analysts find it increasingly difficult
to effectively monitor the produced volume of data, its velocity and diversity. Signature-based …

Impact of word embedding models on text analytics in deep learning environment: a review

DS Asudani, NK Nagwani, P Singh - Artificial intelligence review, 2023 - Springer
The selection of word embedding and deep learning models for better outcomes is vital.
Word embeddings are an n-dimensional distributed representation of a text that attempts to …

A survey on machine learning techniques for cyber security in the last decade

K Shaukat, S Luo, V Varadharajan, IA Hameed… - IEEE …, 2020 - ieeexplore.ieee.org
Pervasive growth and usage of the Internet and mobile applications have expanded
cyberspace. The cyberspace has become more vulnerable to automated and prolonged …

A framework for hate speech detection using deep convolutional neural network

PK Roy, AK Tripathy, TK Das, XZ Gao - IEEE Access, 2020 - ieeexplore.ieee.org
The rapid growth of Internet users led to unwanted cyber issues, including cyberbullying,
hate speech, and many more. This article deals with the problems of hate speech on Twitter …

Machine learning techniques and older adults processing of online information and misinformation: A covid 19 study

J Choudrie, S Banerjee, K Kotecha, R Walambe… - Computers in human …, 2021 - Elsevier
This study is informed by two research gaps. One, Artificial Intelligence's (AI's) Machine
Learning (ML) techniques have the potential to help separate information and …

Hate speech and offensive language detection in Dravidian languages using deep ensemble framework

PK Roy, S Bhawal, CN Subalalitha - Computer Speech & Language, 2022 - Elsevier
Social networking platforms gained widespread popularity and are used for various activities
like: promoting products, sharing news, achievements and many more. On the other hand, it …

Long short-term memory and fuzzy logic for anomaly detection and mitigation in software-defined network environment

MP Novaes, LF Carvalho, J Lloret, ML Proença - IEEE Access, 2020 - ieeexplore.ieee.org
Computer networks become complex and dynamic structures. As a result of this fact, the
configuration and the managing of this whole structure is a challenging activity. Software …

A spam transformer model for SMS spam detection

X Liu, H Lu, A Nayak - IEEE Access, 2021 - ieeexplore.ieee.org
In this paper, we aim to explore the possibility of the Transformer model in detecting the
spam Short Message Service (SMS) messages by proposing a modified Transformer model …

A hybrid CNN-LSTM model for SMS spam detection in arabic and english messages

A Ghourabi, MA Mahmood, QM Alzubi - Future Internet, 2020 - mdpi.com
Despite the rapid evolution of Internet protocol-based messaging services, SMS still remains
an indisputable communication service in our lives until today. For example, several …

An efficient approach for privacy preserving decentralized deep learning models based on secure multi-party computation

AT Tran, TD Luong, J Karnjana, VN Huynh - Neurocomputing, 2021 - Elsevier
This paper aims to develop a new efficient framework named Secure Decentralized Training
Framework (SDTF) for Privacy Preserving Deep Learning models. The main feature of the …