This is a reading list for those interested in studying Malware. If you have any suggestions, please send a pull request.
- 2019, IEEE S&P, LBM: A Security Framework for Peripherals within the Linux Kernel
- 2018, IEEE S&P, Understanding Linux Malware
- 2018, Class 9: Adversarial Malware Detection
- 2017, USENIX Security, Understanding the Mirai Botnet
- 2016, Github, Mirai-Source-Code
- 2016, Blog, MMD-0056-2016 - Linux/Mirai, how an old ELF malcode is recycled
- 2020, S&P, Security Update Labels: Establishing Economic Incentives for Security Patching of IoT Consumer Products
- 2019, arXiv, [HADES-IoT: A Practical Host-Based Anomaly Detection System
- 2019, DSC, Honor Among Thieves: Towards Understanding the Dynamics and Interdependencies in IoT Botnets
- 2019, USENIX CSET, IDAPro for IoT Malware analysis? for IoT Devices (Extended Version)](https://arxiv.org/pdf/1905.01027.pdf)
- 2019, AsiaCCS, HADES-IoT: A Practical Host-Based Anomaly Detection Systemfor IoT Devices
- 2019, NDSS, Measurement and Analysis of Hajime, a Peer-to-peer IoT Botnet
- 2019, NDSS, Cleaning Up the Internet of Evil Things: Real-World Evidence on ISP and Consumer Efforts to Remove Mirai
- 2018, USENIX, Acquisitional Rule-based Engine for Discovering Internet-of-Thing Devices
- 2018, arXiv, A Survey of Machine and Deep Learning Methods for Internet of Things (IoT) Security
- 2018, RAID, Before Toasters Rise Up: A View into the Emerging IoT Threat Landscape
- 2018, BlackHat, IoT Malware: Comprehensive Survey, Analysis Framework and Case Studies
- 2018 arXiv AutoBotCatcher: Blockchain-based P2P Botnet Detection for the Internet of Things
- 2017 Milcom The Mirai Botnet and the IoT Zombie Armies
- 2016 RapidityNetworks, Hajime: Analysis of a decentralized internet worm for IoT devices
- Analyzing the Propagation of IoT Botnets from DNS Leakage
- 2019, MobiSys, Understanding Fileless Attacks on Linux-based IoT Devices with HoneyCloud
- 2018, arXiv, ThingPot: an interactive Internet-of-Things honeypot
- 2017, BlackHat, IoTCandyJar: Towards an Intelligent-Interaction Honeypot for IoT Devices
- 2017, CPSS, SIPHON: Towards Scalable High-Interaction Physical Honeypots
- 2015, WOOT, IoTPOT: Analysing the Rise of IoT Compromises
- 2020, S&P, PMP: Cost-effective Forced Execution with Probabilistic Memory Pre-planning
- 2019, LiSa – Multiplatform Linux Sandbox for Analyzing IoT Malware
- 2018, Thesis, Evaluating Open Source Malware Sandboxes with Linux Malware
- 2018, TIFS, Using Bayesian Networks for Probabilistic Identification of Zero-Day Attack Paths
- 2018, DBSec, Assessing Attack Impact on Business Processes by Interconnecting Attack Graphs and Entity Dependency Graphs
- 2016, CNS, Towards Probabilistic Identification of Zero-day Attack Paths
- 2013, Journal of Computer Security, Aggregating vulnerability metrics in enterprise networks using attack graphs
- 2013, ESORICS, Patrol: Revealing Zero-Day Attack Paths through Network-Wide System Object Dependencies
- 2018, arXiv, Malicious Software Detection and Classification utilizing Temporal-Graphs of System-call Group Relations
- 2018, IoT S&P, Combining MUD Policies with SDN for IoT Intrusion Detection
- 2018, IoT S&P, Clear as MUD: Generating, Validating and Applying IoT Behavioral Profiles
- 2018, arXiv, Device-Type-Specific Anomaly detection, DIoT: A Self-learning System for Detecting Compromised IoT Devices
- 2018, IEEE Transactions on Industrial Informatics, Detection of Malicious Code Variants Based on Deep Learning
- 2018, IEEE ACCESS, Malware Visualization for Fine-Grained Classification
- 2015, International Journal of Information Security, Malware analysis using visualized images and entropy graphs
- 2013, ICASSP, LARGE-SCALE MALWARE CLASSIFICATION USING RANDOM PROJECTIONS AND NEURAL NETWORKS
- 2019, S&P, HOLMES: Real-Time APT Detection through Correlation of Suspicious Information Flows
- 2018, CCS, Tiresias: Predicting Security Events Through Deep Learning
- 2018, CCS, Towards Paving the Way for Large-Scale Windows Malware Analysis: Generic Binary Unpacking with Orders-of-Magnitude Performance Boost
- 2018, NDSS, Towards a Timely Causality Analysis for Enterprise Security
- 2017, Anatomy of an IoT malware attack
- 2014, TIFS, Data-Centric OS Kernel Malware Characterization
- 2018, CCS, LEMNA: Explaining Deep Learning based Security Applications
- 2018, CCS, HoMonit: Monitoring Smart Home Apps from Encrypted Traffic
- 2018, IoT S&P, Web-based Attacks to Discover and Control Local IoT Devices
- 2017, RAID, Android malware clustering through malicious payload mining
- 2014, CCS, Semantics-Aware Android Malware Classification Using Weighted Contextual API Dependency Graphs
- Automated patch management and the challenges from IoT -- patch challenges.
- Securing the IoT Update Process -- overall update process.
- 7 Patch Command Examples to Apply Diff Patch Files in Linux -- useful patch commands.
- Patch Management is the Catalyst for Growth in the IoT Industry -- software cloud management suite.
- Fixing, upgrading and patching IoT devices can be a real nightmare -- some IoT devices are hard to update.
- Fundamentals of IoT device management -- update time matters.
- The Connected World: ‘With Great Power Comes Great Responsibility’ -- Things are not smart enough to be managed easily.
- Comparison of open-source configuration management software
- 2017, Unauthorized FLIR (Lorex) Cloud Access
- 2016, Security Vulnerabilities Published In 2016 (CVSS score >= 7)
- 2016, Trane IoT Vulnerabilities -- vulnerability in Trane thermostats.
- 2013, Dahua DVR Authentication Bypass - CVE-2013-6117
- 2018, OWASP IoT Vulnerabilities Project
- 2018, OWASP IoT Attack Surface Areas Project
- 2018, Vulnogram
- 2018, NDSS, What You Corrupt Is Not What You Crash: Challenges in Fuzzing Embedded Devices
- 2018, USENIX Security, Inception: System-Wide Security Testing of Real-World Embedded Systems Software
- 2017, IFIP SEC, Towards Automated Classification of Firmware Images and Identification of Embedded Devices
- 2014, USENIX Security, A Large-Scale Analysis of the Security of Embedded Firmwares