Malware Feature

Malware feature analysis focuses on identifying characteristics of malicious software to enable accurate and efficient detection. Current research emphasizes developing robust models, including those based on deep learning (e.g., multi-task learning, few-shot learning), random forests, and novel approaches like topological data analysis, to classify malware and detect new variants, even obfuscated ones. These advancements aim to improve the speed and accuracy of malware detection, addressing the challenges posed by increasingly sophisticated and polymorphic threats, and enhancing the explainability of detection methods. The ultimate goal is to strengthen cybersecurity defenses and mitigate the impact of malicious software.

Papers

September 17, 2024

Towards Novel Malicious Packet Recognition: A Few-Shot Learning Approach
Kyle Stein, Andrew A. Mahyari, Guillermo Francia III, Eman El-Sheikh
Malware Detection Learning Approach Malware Representation Deep Packet Inspection Packet Classification Malware Feature

August 23, 2024

Obfuscated Memory Malware Detection
Sharmila S P, Aruna Tiwari, Narendra S Chaudhari
Cyber Attack Malware Attack Malware Sample Metamorphic Malware Malware Feature

July 7, 2024

Detecting new obfuscated malware variants: A lightweight and interpretable machine learning approach
Oladipo A. Madamidola, Felix Ngobigha, Adnane Ez-zizi
Machine Learning Malware Detection Malware Feature

June 4, 2024

kNN Classification of Malware Data Dependency Graph Features
John Musgrave, Anca Ralescu
Classification Code Explanatory Inference Malware Classification Malware Datasets Kaggle Competition Malware Feature

May 9, 2024

Deep Multi-Task Learning for Malware Image Classification
Ahmed Bensaoud, Jugal Kalita
Multi Task Learning Multi Task Malware Detection Multi Task Learning Framework Malware Classification Malware Feature

April 19, 2024

Towards Robust Real-Time Hardware-based Mobile Malware Detection using Multiple Instance Learning Formulation
Harshit Kumar, Sudarshan Sharma, Biswadeep Chakraborty, Saibal Mukhopadhyay
Real Time Multiple Instance Learning Android Malware Malware Representation Novel Malware Malicious Training Malware Feature

May 2, 2023

MDENet: Multi-modal Dual-embedding Networks for Malware Open-set Recognition
Jingcai Guo, Yuanyuan Xu, Wenchao Xu, Yufeng Zhan, Yuxia Sun, Song Guo
Recognition Rate Open Set Recognition Malware Attack Modal Embeddings Malware Representation Malware Feature

November 3, 2022

Reliable Malware Analysis and Detection using Topology Data Analysis
Lionel Nganyewou Tidjon, Foutse Khomh
Data Detection Topological Data Analysis Malware Detection Malware Family Malware Analysis Malware Feature