Malware Analysis

Malware analysis focuses on identifying and understanding malicious software to improve cybersecurity defenses. Current research emphasizes the use of machine learning, particularly deep learning models like convolutional neural networks (CNNs), recurrent neural networks (RNNs), transformers, and generative adversarial networks (GANs), often applied to visual representations of malware or sequences of API calls. These techniques aim to improve detection accuracy, address class imbalance issues, and enhance the explainability of malware detection systems. The field's impact is significant, contributing to more robust and adaptable security solutions for both individual users and organizations.

Papers

June 9, 2023

A Survey on Cross-Architectural IoT Malware Threat Hunting
Anandharaju Durai Raju, Ibrahim Abualhaol, Ronnie Salvador Giagone, Yang Zhou, Shengqiang Huang
Timely Survey Internet of Thing Device Malware Attack Malware Analysis

May 15, 2023

Survey of Malware Analysis through Control Flow Graph using Machine Learning
Shaswata Mitra, Stephen A. Torri, Sudip Mittal
Machine Learning Timely Survey Malware Detection Malware Analysis Control Flow

April 14, 2023

Combining Generators of Adversarial Malware Examples to Increase Evasion Rate
Matouš Kozák, Martin Jureček
Adversarial Attack Malware Detection Malware Attack Malware Analysis Adversarial Malware Multi Layer Generator

January 15, 2023

A Review on the effectiveness of Dimensional Reduction with Computational Forensics: An Application on Malware Analysis
Aye Thaw Da Naing, Justin Soh Beng Guan, Yarzar Shwe Win, Jonathan Pan
Application Proficiency Principal Component Analysis Malware Detection Dimension Reduction Malware Analysis

December 5, 2022

From Malware Samples to Fractal Images: A New Paradigm for Classification. (Version 2.0, Previous version paper name: Have you ever seen malware?)
Ivan Zelinka, Miloslav Szczypka, Jan Plucar, Nikolay Kuznetsov
Classification Code Malware Detection New Paradigm Malware Attack Malware Analysis Fractal Structure Malware Representation Malware Sample

November 6, 2022

MAIL: Malware Analysis Intermediate Language
Shahid Alam
Data Detection Malware Detection Detection Method Malware Analysis

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

August 17, 2022

An Efficient Multi-Step Framework for Malware Packing Identification
Jong-Wouk Kim, Yang-Sae Moon, Mi-Jung Choi
Malware Detection Multi Step Malware Analysis Malware Classifier

April 12, 2022

April 4, 2022

Deep Image: A precious image based deep learning method for online malware detection in IoT Environment
Meysam Ghahramani, Rahim Taheri, Mohammad Shojafar, Reza Javidan, Shaohua Wan
Deep Learning Malware Detection Deep Image Internet of Thing Environment Malware Analysis Image Service

December 28, 2021

Rank-1 Similarity Matrix Decomposition For Modeling Changes in Antivirus Consensus Through Time
Robert J. Joyce, Edward Raff, Charles Nicholas
Time Matter Pre Change Information Low Rank Decomposition Malware Analysis Order Interaction Group Consensus

November 8, 2021

HAPSSA: Holistic Approach to PDF Malware Detection Using Signal and Statistical Analysis
Tajuddin Manhar Mohammed, Lakshmanan Nataraj, Satish Chikkagoudar, Shivkumar Chandrasekaran, B. S. Manjunath
Malware Detection Abnormal Signal Holistic Approach Malware Analysis Statistical Analysis Novel Malware Malware Sample Malicious Attachment

Malware Analysis

Papers

A Survey on Cross-Architectural IoT Malware Threat Hunting

Survey of Malware Analysis through Control Flow Graph using Machine Learning

Combining Generators of Adversarial Malware Examples to Increase Evasion Rate

A Review on the effectiveness of Dimensional Reduction with Computational Forensics: An Application on Malware Analysis

From Malware Samples to Fractal Images: A New Paradigm for Classification. (Version 2.0, Previous version paper name: Have you ever seen malware?)

MAIL: Malware Analysis Intermediate Language

Reliable Malware Analysis and Detection using Topology Data Analysis

An Efficient Multi-Step Framework for Malware Packing Identification

Malceiver: Perceiver with Hierarchical and Multi-modal Features for Android Malware Detection

Malware Analysis with Symbolic Execution and Graph Kernel

Deep Image: A precious image based deep learning method for online malware detection in IoT Environment

Rank-1 Similarity Matrix Decomposition For Modeling Changes in Antivirus Consensus Through Time

HAPSSA: Holistic Approach to PDF Malware Detection Using Signal and Statistical Analysis