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In today's dynamic cybersecurity landscape, timely and accurate threat intelligence is essential for proactive defense.
Spam detection on twitter using traditional classifiers
Michael Mccord and M Chuah · 2011
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The national vulnerability database (nvd): Overview
Harold Booth, Doug Rike, and Gregory Witte · 2013
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Empirical evaluation and new design for fighting evolving twitter spammers
Chao Yang, Robert Harkreader, and Guofei Gu · 2013
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Cats: Characterizing automation of twitter spammers
Amit A Amleshwaram, Narasimha Reddy, Sandeep Yadav, Guofei Gu, and Chao Yang · 2013
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Glove: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher D Manning · 2014
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Emotion identification in fifa world cup tweets using convolutional neural network
Dario Stojanovski, Gjorgji Strezoski, Gjorgji Madjarov, and Ivica Dimitrovski · 2015
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6 million spam tweets: A large ground truth for timely twitter spam detection
Chao Chen, Jun Zhang, Xiao Chen, Yang Xiang, and Wanlei Zhou · 2015
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Threat intelligence: What it is, and how to use it effectively
Matt Bromiley · 2016
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Acing the ioc game: Toward automatic discovery and analysis of open-source cyber threat intelligence
Xiaojing Liao, Kan Yuan, XiaoFeng Wang, Zhou Li, Luyi Xing, and Raheem Beyah · 2016
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Misp: The design and implementation of a collaborative threat intelligence sharing platform
Cynthia Wagner, Alexandre Dulaunoy, Gérard Wagener, and Andras Iklody · 2016
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Discriminating bot accounts based solely on temporal features of microblog behavior
Junshan Pan, Ying Liu, Xiang Liu, and Hanping Hu · 2016
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" why should i trust you?" explaining the predictions of any classifier
Marco Tulio Ribeiro, Sameer Singh, and Carlos Guestrin · 2016
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Ttpdrill: Automatic and accurate extraction of threat actions from unstructured text of cti sources
Ghaith Husari, Ehab Al-Shaer, Mohiuddin Ahmed, Bill Chu, and Xi Niu · 2017
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Omar Al-Ibrahim, Aziz Mohaisen, Charles Kamhoua, Kevin Kwiat, and Laurent Njilla · 2017
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A hybrid approach for spam detection for twitter
Malik Mateen, Muhammad Azhar Iqbal, Muhammad Aleem, and Muhammad Arshad Islam · 2017
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Twitter fake account detection
Buket Erşahin, Özlem Aktaş, Deniz Kılınç, and Ceyhun Akyol · 2017
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A survey of spam detection methods on twitter
Abdullah Talha Kabakus and Resul Kara · 2017
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A unified approach to interpreting model predictions
Scott M Lundberg and Su-In Lee · 2017
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Chainsmith: Automatically learning the semantics of malicious campaigns by mining threat intelligence reports
Ziyun Zhu and Tudor Dumitras · 2018
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Detection of spammers in twitter marketing: a hybrid approach using social media analytics and bio inspired computing
Reema Aswani, Arpan Kumar Kar, and P Vigneswara Ilavarasan · 2018
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Discover: Mining online chatter for emerging cyber threats
Anna Sapienza, Sindhu Kiranmai Ernala, Alessandro Bessi, Kristina Lerman, and Emilio Ferrara · 2018
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Corpus and deep learning classifier for collection of cyber threat indicators in twitter stream
Vahid Behzadan, Carlos Aguirre, Avishek Bose, and William Hsu · 2018
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A hybrid approach for detecting automated spammers in twitter
Mohd Fazil and Muhammad Abulaish · 2018
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Discovering spammer communities in twitter
PV Bindu, Rahul Mishra, and P Santhi Thilagam · 2018
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Who is who on twitter–spammer, fake or compromised account? a tool to reveal true identity in real-time
Monika Singh, Divya Bansal, and Sanjeev Sofat · 2018
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A neural network-based ensemble approach for spam detection in twitter
Sreekanth Madisetty and Maunendra Sankar Desarkar · 2018
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Semi-supervised clue fusion for spammer detection in sina weibo
Cybersecurity event detection with new and re-emerging words
Hyejin Shin, WooChul Shim, Jiin Moon, Jae Woo Seo, Sol Lee, and Yong Ho Hwang · 2020
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A new text classification model based on contrastive word embedding for detecting cybersecurity intelligence in twitter
Han-Sub Shin, Hyuk-Yoon Kwon, and Seung-Jin Ryu · 2020
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Cti-twitter: Gathering cyber threat intelligence from twitter using integrated supervised and unsupervised learning
Linn-Mari Kristiansen, Vinti Agarwal, Katrin Franke, and Raj Sanjay Shah · 2020
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Explainable artificial intelligence (xai): Concepts, taxonomies, opportunities and challenges toward responsible ai
Alejandro Barredo Arrieta, Natalia Díaz-Rodríguez, Javier Del Ser, Adrien Bennetot, Siham Tabik, Alberto Barbado, Salvador García, Sergio Gil-López, Daniel Molina, Richard Benjamins, et al · 2020
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Evaluating the cyber security readiness of organizations and its influence on performance
Shaikha Hasan, Mazen Ali, Sherah Kurnia, and Ramayah Thurasamy · 2021
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Hao Chen, Jun Liu, Yanzhang Lv, Max Haifei Li, Mengyue Liu, and Qinghua Zheng · 2018
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Cyber threat intelligence sharing: Survey and research directions
Thomas D Wagner, Khaled Mahbub, Esther Palomar, and Ali E Abdallah · 2019
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Collecting indicators of compromise from unstructured text of cybersecurity articles using neural-based sequence labelling
Zi Long, Lianzhi Tan, Shengping Zhou, Chaoyang He, and Xin Liu · 2019
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Iocminer: Automatic extraction of indicators of compromise from twitter
Amirreza Niakanlahiji, Lida Safarnejad, Reginald Harper, and Bei-Tseng Chu · 2019
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A quantitative evaluation of trust in the quality of cyber threat intelligence sources
Thomas Schaberreiter, Veronika Kupfersberger, Konstantinos Rantos, Arnolnt Spyros, Alexandros Papanikolaou, Christos Ilioudis, and Gerald Quirchmayr · 2019
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Smsad: a framework for spam message and spam account detection
Kayode Sakariyah Adewole, Nor Badrul Anuar, Amirrudin Kamsin, and Arun Kumar Sangaiah · 2019
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Detecting cybersecurity events from noisy short text
Semih Yagcioglu, Mehmet Saygin Seyfioglu, Begum Citamak, Batuhan Bardak, Seren Guldamlasioglu, Azmi Yuksel, and Emin Islam Tatli · 2019
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#twiti: Social listening for threat intelligence
Hyejin Shin, WooChul Shim, Saebom Kim, Sol Lee, Yong Goo Kang, and Yong Ho Hwang · 2021
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A novel framework for detecting social bots with deep neural networks and active learning
Yuhao Wu, Yuzhou Fang, Shuaikang Shang, Jing Jin, Lai Wei, and Haizhou Wang · 2021
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Tracing relevant twitter accounts active in cyber threat intelligence domain by exploiting content and structure of twitter network
Avishek Bose, Shreya Gopal Sundari, Vahid Behzadan, and William H Hsu · 2021
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An empirical study of machine learning algorithms for social media bot detection
Maryam Heidari, H James Jr, and Ozlem Uzuner · 2021
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Generating fake cyber threat intelligence using transformer-based models
Priyanka Ranade, Aritran Piplai, Sudip Mittal, Anupam Joshi, and Tim Finin · 2021
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A survey on predictions of cyber-attacks utilizing real-time twitter tracing recognition
Sahar Altalhi and Adnan Gutub · 2021
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Birdspotter: A tool for analyzing and labeling twitter users
Rohit Ram, Quyu Kong, and Marian-Andrei Rizoiu · 2021
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Detecting malicious activity in twitter using deep learning techniques
Loukas Ilias and Ioanna Roussaki · 2021
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It’s a matter of style: Detecting social bots through writing style consistency
Matteo Cardaioli, Mauro Conti, Andrea Di Sorbo, Enrico Fabrizio, Sonia Laudanna, and Corrado Aaron Visaggio · 2021
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Bot-mgat: A transfer learning model based on a multi-view graph attention network to detect social bots
Eiman Alothali, Motamen Salih, Kadhim Hayawi, and Hany Alashwal · 2022
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Machine learning-based automatic annotation and detection of covid-19 fake news
Mohammad Majid Akhtar, Bibhas Sharma, Ishan Karunanayake, Rahat Masood, Muhammad Ikram, and Salil S Kanhere · 2022
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An evolutionary computation approach for twitter bot detection
Luigi Rovito, Lorenzo Bonin, Luca Manzoni, and Andrea De Lorenzo · 2022
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Key requirements for the detection and sharing of behavioral indicators of compromise
Antonio Villalón-Huerta, Ismael Ripoll-Ripoll, and Hector Marco-Gisbert · 2022
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A comprehensive study on cybersecurity challenges and opportunities in the iot world
Aejaz Nazir Lone, Suhel Mustajab, and Mahfooz Alam · 2023
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Understanding indicators of compromise against cyber-attacks in industrial control systems: a security perspective
Mohammed Asiri, Neetesh Saxena, Rigel Gjomemo, and Pete Burnap · 2023
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Continuous learning for android malware detection
Yizheng Chen, Zhoujie Ding, and David Wagner · 2023
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