Text mining
T Jo - Studies in Big Data, 2019 - Springer
This book is concerned with the concept, the theories, and the implementations of text
mining. In Part I, we provide the fundamental knowledge about the text mining tasks, such as …
mining. In Part I, we provide the fundamental knowledge about the text mining tasks, such as …
Artificial intelligence and machine learning in cybersecurity: Applications, challenges, and opportunities for mis academics
The availability of massive amounts of data, fast computers, and superior machine learning
(ML) algorithms has spurred interest in artificial intelligence (AI). It is no surprise, then, that …
(ML) algorithms has spurred interest in artificial intelligence (AI). It is no surprise, then, that …
A comprehensive survey of phishing email detection and protection techniques
S Kumar Birthriya, AK Jain - Information Security Journal: A Global …, 2022 - Taylor & Francis
ABSTRACT E-Mails are commonly used as a medium of communication for personal and
pro-fessional purposes. Information shared via mail is also sensitive and private, such as …
pro-fessional purposes. Information shared via mail is also sensitive and private, such as …
Efficient e-mail spam filtering approach combining Logistic Regression model and Orthogonal Atomic Orbital Search algorithm
Phishing emails called spam have created a need for reliable and intelligent spam filters.
Machine-learning techniques are effective, but current methods such as Logistic Regression …
Machine-learning techniques are effective, but current methods such as Logistic Regression …
It ticket classification: The simpler, the better
Recently, automatic classification of IT tickets has gained notable attention due to the
increasing complexity of IT services deployed in enterprises. There are multiple discussions …
increasing complexity of IT services deployed in enterprises. There are multiple discussions …
An efficient flow-based multi-level hybrid intrusion detection system for software-defined networks
M Latah, L Toker - CCF Transactions on Networking, 2020 - Springer
Software-defined networking (SDN) is a novel networking paradigm that provides enhanced
programming abilities, which can be used to solve traditional security challenges on the …
programming abilities, which can be used to solve traditional security challenges on the …
[PDF][PDF] A text-based deception detection model for cybercrime
A Mbaziira, J Jones - Int. Conf. Technol. Manag, 2016 - researchgate.net
Incidents of cybercrime exploiting text-based deception discourse are increasing due to
popularity of text messages. We use machine learning and linguistic approaches to detect …
popularity of text messages. We use machine learning and linguistic approaches to detect …
Design of multi-view based email classification for IoT systems via semi-supervised learning
Suspicious emails are one big threat for Internet of Things (IoT) security, which aim to induce
users to click and then redirect them to a phishing webpage. To protect IoT systems, email …
users to click and then redirect them to a phishing webpage. To protect IoT systems, email …
An empirical study of supervised email classification in Internet of Things: practical performance and key influencing factors
Abstract Internet of Things (IoT) is gradually adopted by many organizations to facilitate the
information collection and sharing. In an organization, an IoT node usually can receive and …
information collection and sharing. In an organization, an IoT node usually can receive and …
A feature-centric spam email detection model using diverse supervised machine learning algorithms
Purpose This research study proposes a feature-centric spam email detection model
(FSEDM) based on content, sentiment, semantic, user and spam-lexicon features set. The …
(FSEDM) based on content, sentiment, semantic, user and spam-lexicon features set. The …