Cover Image

MambaITD: An Efficient Cross-Modal Mamba Network for Insider Threat Detection

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Kong, Kaichuan, Liu, Dongjie, Jin, Xiaobo, Li, Zhiying, Geng, Guanggang, Weng, Jian
Format:	Preprint
Published:	2025
Subjects:	Cryptography and Security Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

DMFI: A Dual-Modality Log Analysis Framework for Insider Threat Detection with LoRA-Tuned Language Models
by: Kong, Kaichuan, et al.
Published: (2025)

Log2Sig: Frequency-Aware Insider Threat Detection via Multivariate Behavioral Signal Decomposition
by: Kong, Kaichuan, et al.
Published: (2025)

Wavelet-Aware Anomaly Detection in Multi-Channel User Logs via Deviation Modulation and Resolution-Adaptive Attention
by: Kong, Kaichuan, et al.
Published: (2026)

MV-Gate: Insider Threat Detection via Multi-View Behavioral Statistics and Semantic Modeling
by: Kong, Kaichuan, et al.
Published: (2026)

Forging the Unforgeable: On the Feasibility of Counterfeit Watermarks in Backdoor-Based Dataset Ownership Verification
by: Li, Zhiying, et al.
Published: (2024)

OrgForge-IT: A Verifiable Synthetic Benchmark for LLM-Based Insider Threat Detection
by: Flynt, Jeffrey
Published: (2026)

LAN: Learning Adaptive Neighbors for Real-Time Insider Threat Detection
by: Cai, Xiangrui, et al.
Published: (2024)

RedChronos: A Large Language Model-Based Log Analysis System for Insider Threat Detection in Enterprises
by: Li, Chenyu, et al.
Published: (2025)

RMSL: Weakly-Supervised Insider Threat Detection with Robust Multi-sphere Learning
by: Wang, Yang, et al.
Published: (2025)

Fine Grained Insider Risk Detection
by: Huber, Birkett, et al.
Published: (2024)

Agentic Misalignment: How LLMs Could Be Insider Threats
by: Lynch, Aengus, et al.
Published: (2025)

Optimizing IoT Threat Detection with Kolmogorov-Arnold Networks (KANs)
by: Emelianova, Natalia, et al.
Published: (2025)

GraphDART: Graph Distillation for Efficient Advanced Persistent Threat Detection
by: Rabooki, Saba Fathi, et al.
Published: (2025)

Network Threat Detection: Addressing Class Imbalanced Data with Deep Forest
by: Chen, Jiaqi, et al.
Published: (2025)

Improving Network Threat Detection by Knowledge Graph, Large Language Model, and Imbalanced Learning
by: Zhang, Lili, et al.
Published: (2025)

Causal Graph Profiling via Structural Divergence for Robust Anomaly Detection in Cyber-Physical Systems
by: Malarkkan, Arun Vignesh, et al.
Published: (2025)

MambaNetBurst: Direct Byte-level Network Traffic Classification without Tokenization or Pretraining
by: Kulatilleke, Gayan K., et al.
Published: (2026)

GESR: Graph-Based Edge Semantic Reconstruction for Stealthy Communication Detection with Benign-Only Training
by: Xu, Henghui, et al.
Published: (2026)

Hashed Watermark as a Filter: Defeating Forging and Overwriting Attacks in Weight-based Neural Network Watermarking
by: Yao, Yuan, et al.
Published: (2025)

TabSec: A Collaborative Framework for Novel Insider Threat Detection
by: Huang, Zilin, et al.
Published: (2024)

Insider Threats Mitigation: Role of Penetration Testing
by: Chauhan, Krutarth
Published: (2024)

Explainable Threat Attribution for IoT Networks Using Conditional SHAP and Flow Behavior Modelling
by: Ozechi, Samuel, et al.
Published: (2026)

Hybrid LLM-Enhanced Intrusion Detection for Zero-Day Threats in IoT Networks
by: Al-Hammouri, Mohammad F., et al.
Published: (2025)

Facade: High-Precision Insider Threat Detection Using Deep Contextual Anomaly Detection
by: Kantchelian, Alex, et al.
Published: (2024)

Insight-LLM: LLM-enhanced Multi-view Fusion in Insider Threat Detection
by: Song, Chengyu, et al.
Published: (2025)

threaTrace: Detecting and Tracing Host-based Threats in Node Level Through Provenance Graph Learning
by: Wang, Su, et al.
Published: (2021)

An Efficient Privacy-preserving Intrusion Detection Scheme for UAV Swarm Networks
by: Gharami, Kanchon, et al.
Published: (2025)

Survey of Privacy Threats and Countermeasures in Federated Learning
by: Hayashitani, Masahiro, et al.
Published: (2024)

X Hacking: The Threat of Misguided AutoML
by: Sharma, Rahul, et al.
Published: (2024)

Signal Decomposition Reveals Structure in Insider Threat Detection under Sparse Temporal Data
by: Beadles, Hayden, et al.
Published: (2026)

Real-Time Detection of Insider Threats Using Behavioral Analytics and Deep Evidential Clustering
by: Ali, Anas, et al.
Published: (2025)

Data Poisoning: An Overlooked Threat to Power Grid Resilience
by: Agah, Nora, et al.
Published: (2024)

PacketCLIP: Multi-Modal Embedding of Network Traffic and Language for Cybersecurity Reasoning
by: Masukawa, Ryozo, et al.
Published: (2025)

BADTV: Unveiling Backdoor Threats in Third-Party Task Vectors
by: Hsu, Chia-Yi, et al.
Published: (2025)

VulStyle: A Multi-Modal Pre-Training for Code Stylometry-Augmented Vulnerability Detection
by: Biringa, Chidera, et al.
Published: (2026)

Shift Detection and Adaptation for Network Intrusion Detection
by: Mousavipour, Ehssan, et al.
Published: (2025)

A Two-Stage CAE-Based Federated Learning Framework for Efficient Jamming Detection in 5G Networks
by: Kuili, Samhita, et al.
Published: (2025)

MDHP-Net: Detecting an Emerging Time-exciting Threat in IVN
by: Liu, Qi, et al.
Published: (2024)

Securing Federated Learning against Backdoor Threats with Foundation Model Integration
by: Bi, Xiaohuan, et al.
Published: (2024)

FRAME : Comprehensive Risk Assessment Framework for Adversarial Machine Learning Threats
by: Shapira, Avishag, et al.
Published: (2025)