ResearchTrend.AI
  • Communities
  • Connect sessions
  • AI calendar
  • Organizations
  • Join Slack
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2026 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2109.03375
  4. Cited By
Malware Squid: A Novel IoT Malware Traffic Analysis Framework using
  Convolutional Neural Network and Binary Visualisation

Malware Squid: A Novel IoT Malware Traffic Analysis Framework using Convolutional Neural Network and Binary Visualisation

Next Generation Teletraffic and Wired/Wireless Advanced Networking (NEW2AN), 2019
8 September 2021
Robert Shire
S. Shiaeles
Keltoum Bendiab
Bogdan Ghita
N. Kolokotronis
ArXiv (abs)PDFHTML

Papers citing "Malware Squid: A Novel IoT Malware Traffic Analysis Framework using Convolutional Neural Network and Binary Visualisation"

3 / 3 papers shown
Intrusion Detection using Network Traffic Profiling and Machine Learning
  for IoT
Intrusion Detection using Network Traffic Profiling and Machine Learning for IoTIEEE Conference on Network Softwarization (NetSoft), 2021
Joseph R. Rose
Matt Swann
G. Bendiab
S. Shiaeles
N. Kolokotronis
111
39
0
06 Sep 2021
Advanced Metering Infrastructures: Security Risks and Mitigation
Advanced Metering Infrastructures: Security Risks and MitigationARES (ARES), 2020
G. Bendiab
Konstantinos-Panagiotis Grammatikakis
Ioannis Koufos
N. Kolokotronis
S. Shiaeles
74
15
0
10 May 2021
IoT Malware Network Traffic Classification using Visual Representation
  and Deep Learning
IoT Malware Network Traffic Classification using Visual Representation and Deep LearningIEEE Conference on Network Softwarization (NetSoft), 2020
G. Bendiab
S. Shiaeles
Abdulrahman Alruban
N. Kolokotronis
95
76
0
04 Oct 2020
1