Concept Drift Detection using Ensemble of Integrally Private Models
Fuente:
arXiv
Saved in:
| Main Authors: | Varshney, Ayush K., Torra, Vicenc |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Efficient Federated Unlearning under Plausible Deniability
by: Varshney, Ayush K., et al.
Published: (2024)
by: Varshney, Ayush K., et al.
Published: (2024)
Realistic Image-to-Image Machine Unlearning via Decoupling and Knowledge Retention
by: Varshney, Ayush K., et al.
Published: (2025)
by: Varshney, Ayush K., et al.
Published: (2025)
Cluster Analysis and Concept Drift Detection in Malware
by: Mishra, Aniket, et al.
Published: (2025)
by: Mishra, Aniket, et al.
Published: (2025)
Understanding Concept Drift with Deprecated Permissions in Android Malware Detection
by: Sabbah, Ahmed, et al.
Published: (2025)
by: Sabbah, Ahmed, et al.
Published: (2025)
DRMD: Deep Reinforcement Learning for Malware Detection under Concept Drift
by: McFadden, Shae, et al.
Published: (2025)
by: McFadden, Shae, et al.
Published: (2025)
Binary Anomaly Detection in Streaming IoT Traffic under Concept Drift
by: Carnier, Rodrigo Matos, et al.
Published: (2025)
by: Carnier, Rodrigo Matos, et al.
Published: (2025)
Identifying Predictions That Influence the Future: Detecting Performative Concept Drift in Data Streams
by: Gower-Winter, Brandon, et al.
Published: (2024)
by: Gower-Winter, Brandon, et al.
Published: (2024)
MADCAT: Combating Malware Detection Under Concept Drift with Test-Time Adaptation
by: Roh, Eunjin, et al.
Published: (2025)
by: Roh, Eunjin, et al.
Published: (2025)
ADAPT: A Pseudo-labeling Approach to Combat Concept Drift in Malware Detection
by: Alam, Md Tanvirul, et al.
Published: (2025)
by: Alam, Md Tanvirul, et al.
Published: (2025)
Detecting Concept Drift in Evolving Malware Families Using Rule-Based Classifier Representations
by: Kalný, Tomáš, et al.
Published: (2026)
by: Kalný, Tomáš, et al.
Published: (2026)
Thwarting Cybersecurity Attacks with Explainable Concept Drift
by: Shaer, Ibrahim, et al.
Published: (2024)
by: Shaer, Ibrahim, et al.
Published: (2024)
Optimized Deep Learning Models for Malware Detection under Concept Drift
by: Maillet, William, et al.
Published: (2023)
by: Maillet, William, et al.
Published: (2023)
Optimized Tradeoffs for Private Prediction with Majority Ensembling
by: Jiang, Shuli, et al.
Published: (2024)
by: Jiang, Shuli, et al.
Published: (2024)
LAMDA: A Longitudinal Android Malware Benchmark for Concept Drift Analysis
by: Haque, Md Ahsanul, et al.
Published: (2025)
by: Haque, Md Ahsanul, et al.
Published: (2025)
Empirical Evaluation of Concept Drift in ML-Based Android Malware Detection
by: Sabbah, Ahmed, et al.
Published: (2025)
by: Sabbah, Ahmed, et al.
Published: (2025)
FARM: Few-shot Adaptive Malware Family Classification under Concept Drift
by: Guldemir, Numan Halit, et al.
Published: (2026)
by: Guldemir, Numan Halit, et al.
Published: (2026)
Optimal Guarantees for Auditing Rényi Differentially Private Machine Learning
by: Kim, Benjamin D., et al.
Published: (2026)
by: Kim, Benjamin D., et al.
Published: (2026)
Concept Drift Adaptation Using Self-Supervised and Reinforcement Learning In Android Malware Detection
by: Sabbah, Ahmed, et al.
Published: (2026)
by: Sabbah, Ahmed, et al.
Published: (2026)
Unlearning Clients, Features and Samples in Vertical Federated Learning
by: Varshney, Ayush K., et al.
Published: (2025)
by: Varshney, Ayush K., et al.
Published: (2025)
Enhanced Anomaly Detection in IoMT Networks using Ensemble AI Models on the CICIoMT2024 Dataset
by: Chandekar, Prathamesh, et al.
Published: (2025)
by: Chandekar, Prathamesh, et al.
Published: (2025)
An $\tilde{O}$ptimal Differentially Private Learner for Concept Classes with VC Dimension 1
by: Yan, Chao
Published: (2025)
by: Yan, Chao
Published: (2025)
Adversarial Vulnerability Under Temporal Concept Drift: A Longitudinal Study of Android Malware Detection
by: Sabbah, Ahmed, et al.
Published: (2026)
by: Sabbah, Ahmed, et al.
Published: (2026)
Memory poisoning and secure multi-agent systems
by: Torra, Vicenç, et al.
Published: (2026)
by: Torra, Vicenç, et al.
Published: (2026)
Differentially Private Diffusion Models
by: Dockhorn, Tim, et al.
Published: (2022)
by: Dockhorn, Tim, et al.
Published: (2022)
Concept-ROT: Poisoning Concepts in Large Language Models with Model Editing
by: Grimes, Keltin, et al.
Published: (2024)
by: Grimes, Keltin, et al.
Published: (2024)
McNdroid: A Longitudinal Multimodal Benchmark for Robust Drift Detection in Android Malware
by: Kamol, Md Mahmuduzzaman, et al.
Published: (2026)
by: Kamol, Md Mahmuduzzaman, et al.
Published: (2026)
Differentially Private Random Feature Model
by: Liao, Chunyang, et al.
Published: (2024)
by: Liao, Chunyang, et al.
Published: (2024)
LanFL: Differentially Private Federated Learning with Large Language Models using Synthetic Samples
by: Wu, Huiyu, et al.
Published: (2024)
by: Wu, Huiyu, et al.
Published: (2024)
Efficient Adversarial Malware Defense via Trust-Based Raw Override and Confidence-Adaptive Bit-Depth Reduction
by: Chaudhary, Ayush, et al.
Published: (2025)
by: Chaudhary, Ayush, et al.
Published: (2025)
Differentially Private Training of Mixture of Experts Models
by: Tholoniat, Pierre, et al.
Published: (2024)
by: Tholoniat, Pierre, et al.
Published: (2024)
Privately Aligning Language Models with Reinforcement Learning
by: Wu, Fan, et al.
Published: (2023)
by: Wu, Fan, et al.
Published: (2023)
Scaling Laws for Differentially Private Language Models
by: McKenna, Ryan, et al.
Published: (2025)
by: McKenna, Ryan, et al.
Published: (2025)
BLens: Contrastive Captioning of Binary Functions using Ensemble Embedding
by: Benoit, Tristan, et al.
Published: (2024)
by: Benoit, Tristan, et al.
Published: (2024)
CaBaGe: Data-Free Model Extraction using ClAss BAlanced Generator Ensemble
by: Rosenthal, Jonathan, et al.
Published: (2024)
by: Rosenthal, Jonathan, et al.
Published: (2024)
Efficient Differentially Private Fine-Tuning of Diffusion Models
by: Liu, Jing, et al.
Published: (2024)
by: Liu, Jing, et al.
Published: (2024)
Training Differentially Private Models with Secure Multiparty Computation
by: Pentyala, Sikha, et al.
Published: (2022)
by: Pentyala, Sikha, et al.
Published: (2022)
DP-LDMs: Differentially Private Latent Diffusion Models
by: Liu, Michael F., et al.
Published: (2023)
by: Liu, Michael F., et al.
Published: (2023)
Privately Learning Decision Lists and a Differentially Private Winnow
by: Bun, Mark, et al.
Published: (2026)
by: Bun, Mark, et al.
Published: (2026)
SEED: Semi-supervised Continual MalwarE Detection for Tackling ConcEpt Drift on a BuDget
by: Amalapuram, Suresh Kumar, et al.
Published: (2026)
by: Amalapuram, Suresh Kumar, et al.
Published: (2026)
Attacker Behaviour Profiling using Stochastic Ensemble of Hidden Markov Models
by: Deshmukh, Soham, et al.
Published: (2019)
by: Deshmukh, Soham, et al.
Published: (2019)
Similar Items
-
Efficient Federated Unlearning under Plausible Deniability
by: Varshney, Ayush K., et al.
Published: (2024) -
Realistic Image-to-Image Machine Unlearning via Decoupling and Knowledge Retention
by: Varshney, Ayush K., et al.
Published: (2025) -
Cluster Analysis and Concept Drift Detection in Malware
by: Mishra, Aniket, et al.
Published: (2025) -
Understanding Concept Drift with Deprecated Permissions in Android Malware Detection
by: Sabbah, Ahmed, et al.
Published: (2025) -
DRMD: Deep Reinforcement Learning for Malware Detection under Concept Drift
by: McFadden, Shae, et al.
Published: (2025)