Malicious Traffic

Malicious traffic detection focuses on identifying and classifying network communications used for harmful purposes, aiming to improve cybersecurity and network performance. Current research heavily utilizes machine learning, employing various architectures like transformers, convolutional neural networks, and message-passing neural networks, often coupled with explainable AI techniques for improved model transparency and robustness against adversarial attacks. This field is crucial for mitigating the impact of diverse threats, from malware propagation and denial-of-service attacks to data poisoning in federated learning, with ongoing efforts to enhance detection accuracy and address the challenges posed by encryption and evolving attack methods.

Papers

November 12, 2024

Zer0-Jack: A Memory-efficient Gradient-based Jailbreaking Method for Black-box Multi-modal Large Language Models
Tiejin Chen, Kaishen Wang, Hua Wei
Jailbreak Attack Black Box Model Multi Modal Large Language Model White Box Malicious Traffic Memory effIcieNt

November 1, 2024

Attention Tracker: Detecting Prompt Injection Attacks in LLMs
Kuo-Han Hung, Ching-Yun Ko, Ambrish Rawat, I-Hsin Chung, Winston H. Hsu, Pin-Yu Chen
Large Language Model Prompt Injection Attack Attention Pattern Malicious Traffic

October 17, 2024

Do LLMs Have Political Correctness? Analyzing Ethical Biases and Jailbreak Vulnerabilities in AI Systems
Isack Lee, Haebin Seong
Large Language Model AI System Jailbreak Attack Social Bias Safety Alignment Malicious Traffic Common Bias Moral Bias

October 2, 2024

Efficient PAC Learning of Halfspaces with Constant Malicious Noise Rate
Jie Shen, Xiaoyu Li
Native Robustness Efficient Algorithm Margin Maximization PAC Learning Margin Halfspaces Malicious Traffic Noise Resistant Property

September 25, 2024

Examining the Rat in the Tunnel: Interpretable Multi-Label Classification of Tor-based Malware
Ishan Karunanayake, Mashael AlSabah, Nadeem Ahmed, Sanjay Jha
Malware Attack Malware Classification Interpretable Classifier Malicious Traffic Rat Image ToR Network

August 21, 2024

EEG-Defender: Defending against Jailbreak through Early Exit Generation of Large Language Models
Chongwen Zhao, Zhihao Dou, Kaizhu Huang
Jailbreak Attack Malicious Traffic Adversarial Suffix Malicious Prompt

April 5, 2024

Precision Guided Approach to Mitigate Data Poisoning Attacks in Federated Learning
K Naveen Kumar, C Krishna Mohan, Aravind Machiry
Data Poisoning Attack Malicious Traffic

March 27, 2024

A Transformer-Based Framework for Payload Malware Detection and Classification
Kyle Stein, Arash Mahyari, Guillermo Francia, Eman El-Sheikh
Classification Code Internet of Thing Intrusion Detection Malware Detection Transformer Based Framework Malicious Traffic Deep Packet Inspection Malicious Attack

March 24, 2024

A Survey on Consumer IoT Traffic: Security and Privacy
Yan Jia, Yuxin Song, Zihou Liu, Qingyin Tan, Yang Song, Yu Zhang, Zheli Liu
Timely Survey Privacy Policy Security Related Traffic Data Malicious Traffic IoT Traffic

February 25, 2024

Communication Traffic Characteristics Reveal an IoT Devices Identity
Rajarshi Roy Chowdhury, Debashish Roy, Pg Emeroylariffion Abas
Internet of Thing Device Network Traffic Malicious Traffic Device Identification IoT Device Identification

December 14, 2023

Data and Model Poisoning Backdoor Attacks on Wireless Federated Learning, and the Defense Mechanisms: A Comprehensive Survey
Yichen Wan, Youyang Qu, Wei Ni, Yong Xiang, Longxiang Gao, Ekram Hossain
Federated Learning Raw Data Comprehensive Survey Attack Strategy Malicious Traffic DEfense Mechanism

December 6, 2023

Feature Analysis of Encrypted Malicious Traffic
Anish Singh Shekhawat, Fabio Di Troia, Mark Stamp
Machine Learning Model Traffic Data Malware Attack Malicious Traffic Feature Mining Malicious Data

December 4, 2023

Intrusion Detection System with Machine Learning and Multiple Datasets
Haiyan Xuan, Mohith Manohar
Machine Learning Artificial Intelligence Artificial Intelligence System Intrusion Detection System Malicious Traffic

September 11, 2023

A Novel Supervised Deep Learning Solution to Detect Distributed Denial of Service (DDoS) attacks on Edge Systems using Convolutional Neural Networks (CNN)
Vedanth Ramanathan, Krish Mahadevan, Sejal Dua
Deep Learning Convolutional Neural Network New Attack Deep Learning Based Edge Server Malicious Traffic Denial of Service Attack

August 28, 2023

Are Existing Out-Of-Distribution Techniques Suitable for Network Intrusion Detection?
Andrea Corsini, Shanchieh Jay Yang
Network Intrusion Detection Detection Method Malicious Traffic Class Out of Distribution Malicious Attack

June 27, 2023

Classification and Explanation of Distributed Denial-of-Service (DDoS) Attack Detection using Machine Learning and Shapley Additive Explanation (SHAP) Methods
Yuanyuan Wei, Julian Jang-Jaccard, Amardeep Singh, Fariza Sabrina, Seyit Camtepe
Machine Learning Explainable Artificial Intelligence Attack Detection Attack Dataset Distributed Denial of Service Malicious Traffic

April 30, 2023

SoK: Pragmatic Assessment of Machine Learning for Network Intrusion Detection
Giovanni Apruzzese, Pavel Laskov, Johannes Schneider
Machine Learning Network Intrusion Detection Adversarial Scenario Malicious Traffic

April 7, 2023

Feature Mining for Encrypted Malicious Traffic Detection with Deep Learning and Other Machine Learning Algorithms
Zihao Wang, Vrizlynn L. L. Thing
Deep Learning Malicious Traffic Encrypted Traffic Feature Mining

April 2, 2023

MalIoT: Scalable and Real-time Malware Traffic Detection for IoT Networks
Ethan Weitkamp, Yusuke Satani, Adam Omundsen, Jingwen Wang, Peilong Li
Internet of Thing Internet of Thing Device Internet of Thing Network Malicious Traffic

June 21, 2022

Open-Source Framework for Encrypted Internet and Malicious Traffic Classification
Ofek Bader, Adi Lichy, Amit Dvir, Ran Dubin, Chen Hajaj
Intrusion Detection Traffic Classification Open Source Framework Malicious Traffic Encrypted Traffic

Malicious Traffic

Papers

Zer0-Jack: A Memory-efficient Gradient-based Jailbreaking Method for Black-box Multi-modal Large Language Models

Attention Tracker: Detecting Prompt Injection Attacks in LLMs

Do LLMs Have Political Correctness? Analyzing Ethical Biases and Jailbreak Vulnerabilities in AI Systems

Efficient PAC Learning of Halfspaces with Constant Malicious Noise Rate

Examining the Rat in the Tunnel: Interpretable Multi-Label Classification of Tor-based Malware

EEG-Defender: Defending against Jailbreak through Early Exit Generation of Large Language Models

Precision Guided Approach to Mitigate Data Poisoning Attacks in Federated Learning

A Transformer-Based Framework for Payload Malware Detection and Classification

A Survey on Consumer IoT Traffic: Security and Privacy

Communication Traffic Characteristics Reveal an IoT Devices Identity

Data and Model Poisoning Backdoor Attacks on Wireless Federated Learning, and the Defense Mechanisms: A Comprehensive Survey

Feature Analysis of Encrypted Malicious Traffic

Intrusion Detection System with Machine Learning and Multiple Datasets

A Novel Supervised Deep Learning Solution to Detect Distributed Denial of Service (DDoS) attacks on Edge Systems using Convolutional Neural Networks (CNN)

Are Existing Out-Of-Distribution Techniques Suitable for Network Intrusion Detection?

Classification and Explanation of Distributed Denial-of-Service (DDoS) Attack Detection using Machine Learning and Shapley Additive Explanation (SHAP) Methods

SoK: Pragmatic Assessment of Machine Learning for Network Intrusion Detection

Feature Mining for Encrypted Malicious Traffic Detection with Deep Learning and Other Machine Learning Algorithms

MalIoT: Scalable and Real-time Malware Traffic Detection for IoT Networks

Open-Source Framework for Encrypted Internet and Malicious Traffic Classification