NexTech 2021 Congress
October 03, 2021 to October 07, 2021 - Barcelona, Spain

  • UBICOMM 2021, The Fifteenth International Conference on Mobile Ubiquitous Computing, Systems, Services and Technologies
  • ADVCOMP 2021, The Fifteenth International Conference on Advanced Engineering Computing and Applications in Sciences
  • SEMAPRO 2021, The Fifteenth International Conference on Advances in Semantic Processing
  • AMBIENT 2021, The Eleventh International Conference on Ambient Computing, Applications, Services and Technologies
  • EMERGING 2021, The Thirteenth International Conference on Emerging Networks and Systems Intelligence
  • DATA ANALYTICS 2021, The Tenth International Conference on Data Analytics
  • GLOBAL HEALTH 2021, The Tenth International Conference on Global Health Challenges
  • CYBER 2021, The Sixth International Conference on Cyber-Technologies and Cyber-Systems

SoftNet 2021 Congress
October 03, 2021 to October 07, 2021 - Barcelona, Spain

  • ICSEA 2021, The Sixteenth International Conference on Software Engineering Advances
  • ICSNC 2021, The Sixteenth International Conference on Systems and Networks Communications
  • CENTRIC 2021, The Fourteenth International Conference on Advances in Human-oriented and Personalized Mechanisms, Technologies, and Services
  • VALID 2021, The Thirteenth International Conference on Advances in System Testing and Validation Lifecycle
  • SIMUL 2021, The Thirteenth International Conference on Advances in System Simulation
  • SOTICS 2021, The Eleventh International Conference on Social Media Technologies, Communication, and Informatics
  • INNOV 2021, The Tenth International Conference on Communications, Computation, Networks and Technologies
  • HEALTHINFO 2021, The Sixth International Conference on Informatics and Assistive Technologies for Health-Care, Medical Support and Wellbeing

NetWare 2021 Congress
November 14, 2021 to November 18, 2021 - Athens, Greece

  • SENSORCOMM 2021, The Fifteenth International Conference on Sensor Technologies and Applications
  • SENSORDEVICES 2021, The Twelfth International Conference on Sensor Device Technologies and Applications
  • SECURWARE 2021, The Fifteenth International Conference on Emerging Security Information, Systems and Technologies
  • AFIN 2021, The Thirteenth International Conference on Advances in Future Internet
  • CENICS 2021, The Fourteenth International Conference on Advances in Circuits, Electronics and Micro-electronics
  • ICQNM 2021, The Fifteenth International Conference on Quantum, Nano/Bio, and Micro Technologies
  • FASSI 2021, The Seventh International Conference on Fundamentals and Advances in Software Systems Integration
  • GREEN 2021, The Sixth International Conference on Green Communications, Computing and Technologies

TrendNews 2021 Congress
November 14, 2021 to November 18, 2021 - Athens, Greece

  • CORETA 2021, Advances on Core Technologies and Applications
  • DIGITAL 2021, Advances on Societal Digital Transformation

 


ThinkMind // CYBER 2019, The Fourth International Conference on Cyber-Technologies and Cyber-Systems // View article cyber_2019_3_30_80058


Eavesdropping Hackers: Detecting Software Vulnerability Communication on Social Media Using Text Mining

Authors:
Andrei Lima Queiroz
Susan Mckeever
Brian Keegan

Keywords: cyber security threat intelligence; software vulnerability; machine learning; text mining; social media, hacker communication

Abstract:
Cyber security is striving to find new forms of pro- tection against hacker attacks. An emerging approach nowadays is the investigation of security-related messages exchanged on Deep/Dark Web and even Surface Web channels. This approach can be supported by the use of supervised machine learning models and text mining techniques. In our work, we compare a variety of machine learning algorithms, text representations and dimension reduction approaches for the detection accu- racies of software-vulnerability-related communications. Given the imbalanced nature of the three public datasets used, we investigate appropriate sampling approaches to boost detection accuracies of our models. In addition, we examine how feature reduction techniques, such as Document Frequency Reduction, Chi-square and Singular Value Decomposition (SVD) can be used to reduce the number of features of the model without impacting the detection performance. We conclude that: (1) a Support Vector Machine (SVM) algorithm used with traditional Bag of Words achieved highest accuracies (2) The increase of the minority class with Random Oversampling technique improves the detection performance of the model by 5% on average, and (3) The number of features of the model can be reduced by up to 10% without affecting the detection performance. Also, we have provided the labelled dataset used in this work for further research. These findings can be used to support Cyber Security Threat Intelligence (CTI) with respect to the use of text mining techniques for detecting security-related communication.

Pages: 41 to 48

Copyright: Copyright (c) IARIA, 2019

Publication date: September 22, 2019

Published in: conference

ISSN: 2519-8599

ISBN: 978-1-61208-743-6

Location: Porto, Portugal

Dates: from September 22, 2019 to September 26, 2019

SERVICES CONTACT
2010 - 2017 © ThinkMind. All rights reserved.
Read Terms of Service and Privacy Policy.