# Advanced Malware Detection Techniques

**Type:** Topics  
**Canonical URL:** https://scholariq.org/topics/advanced-malware-detection-techniques/

## Facts

| Field | Value |
| --- | --- |
| Description | This cluster of papers focuses on the characterization, detection, and analysis of Android malware. It covers topics such as machine learning-based detection, security analysis, behavioral and permission analysis, deep learning approaches, dynamic analysis, IoT security, and ransomware threats. |
| Domain | Physical Sciences |
| Field | Computer Science |
| OpenAlex ID | t11241 |
| Works | 179 |

## Topic papers all

Showing 15 of 179.

- [StackGuard: automatic adaptive detection and prevention of buffer-overflow attacks](https://scholariq.org/papers/stackguard-automatic-adaptive-detection-and-prevention-of-buffer-overflow/)
- [Combating Fake News](https://scholariq.org/papers/combating-fake-news/)
- [An effective feature engineering for DNN using hybrid PCA-GWO for intrusion detection in IoMT architecture](https://scholariq.org/papers/an-effective-feature-engineering-for-dnn-using-hybrid-pca-gwo-for-intrusion/)
- [A hybrid deep learning model for efficient intrusion detection in big data environment](https://scholariq.org/papers/a-hybrid-deep-learning-model-for-efficient-intrusion-detection-in-big-data/)
- [Deep Ground Truth Analysis of Current Android Malware](https://scholariq.org/papers/deep-ground-truth-analysis-of-current-android-malware/)
- [Efficient flow-sensitive interprocedural computation of pointer-induced aliases and side effects](https://scholariq.org/papers/efficient-flow-sensitive-interprocedural-computation-of-pointer-induced-aliases/)
- [TSDL: A Two-Stage Deep Learning Model for Efficient Network Intrusion Detection](https://scholariq.org/papers/tsdl-a-two-stage-deep-learning-model-for-efficient-network-intrusion-detection/)
- [Cyber Threat Intelligence Mining for Proactive Cybersecurity Defense: A Survey and New Perspectives](https://scholariq.org/papers/cyber-threat-intelligence-mining-for-proactive-cybersecurity-defense-a-survey/)
- [PhishStorm: Detecting Phishing With Streaming Analytics](https://scholariq.org/papers/phishstorm-detecting-phishing-with-streaming-analytics/)
- [An Efficient DenseNet-Based Deep Learning Model for Malware Detection](https://scholariq.org/papers/an-efficient-densenet-based-deep-learning-model-for-malware-detection/)
- [Fake News Detection Using Machine Learning approaches: A systematic Review](https://scholariq.org/papers/fake-news-detection-using-machine-learning-approaches-a-systematic-review/)
- [DroidBot: a lightweight UI-Guided test input generator for android](https://scholariq.org/papers/droidbot-a-lightweight-ui-guided-test-input-generator-for-android/)
- [Real-Time Lateral Movement Detection Based on Evidence Reasoning Network for Edge Computing Environment](https://scholariq.org/papers/real-time-lateral-movement-detection-based-on-evidence-reasoning-network-for/)
- [LibRadar](https://scholariq.org/papers/libradar/)
- [WuKong: a scalable and accurate two-phase approach to Android app clone detection](https://scholariq.org/papers/wukong-a-scalable-and-accurate-two-phase-approach-to-android-app-clone-detection/)

## Topic primary papers

Showing 15 of 45.

- [Deep Ground Truth Analysis of Current Android Malware](https://scholariq.org/papers/deep-ground-truth-analysis-of-current-android-malware/)
- [Cyber Threat Intelligence Mining for Proactive Cybersecurity Defense: A Survey and New Perspectives](https://scholariq.org/papers/cyber-threat-intelligence-mining-for-proactive-cybersecurity-defense-a-survey/)
- [An Efficient DenseNet-Based Deep Learning Model for Malware Detection](https://scholariq.org/papers/an-efficient-densenet-based-deep-learning-model-for-malware-detection/)
- [DroidBot: a lightweight UI-Guided test input generator for android](https://scholariq.org/papers/droidbot-a-lightweight-ui-guided-test-input-generator-for-android/)
- [Real-Time Lateral Movement Detection Based on Evidence Reasoning Network for Edge Computing Environment](https://scholariq.org/papers/real-time-lateral-movement-detection-based-on-evidence-reasoning-network-for/)
- [LibRadar](https://scholariq.org/papers/libradar/)
- [WuKong: a scalable and accurate two-phase approach to Android app clone detection](https://scholariq.org/papers/wukong-a-scalable-and-accurate-two-phase-approach-to-android-app-clone-detection/)
- [Trends in Ransomware Attacks on US Hospitals, Clinics, and Other Health Care Delivery Organizations, 2016-2021](https://scholariq.org/papers/trends-in-ransomware-attacks-on-us-hospitals-clinics-and-other-health-care/)
- [Beyond Google Play](https://scholariq.org/papers/beyond-google-play/)
- [Machine learning-assisted signature and heuristic-based detection of malwares in Android devices](https://scholariq.org/papers/machine-learning-assisted-signature-and-heuristic-based-detection-of-malwares-in/)
- [FraudDroid: automated ad fraud detection for Android apps](https://scholariq.org/papers/frauddroid-automated-ad-fraud-detection-for-android-apps/)
- [A survey of android application and malware hardening](https://scholariq.org/papers/a-survey-of-android-application-and-malware-hardening/)
- [Software Vulnerability Analysis and Discovery Using Deep Learning Techniques: A Survey](https://scholariq.org/papers/software-vulnerability-analysis-and-discovery-using-deep-learning-techniques-a/)
- [MalScan: Fast Market-Wide Mobile Malware Scanning by Social-Network Centrality Analysis](https://scholariq.org/papers/malscan-fast-market-wide-mobile-malware-scanning-by-social-network-centrality/)
- [Generative adversarial attacks against intrusion detection systems using active learning](https://scholariq.org/papers/generative-adversarial-attacks-against-intrusion-detection-systems-using-active/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.