Search Results - "Mathov Y"

Author Correction: Inferring DNA methylation in non-skeletal tissues of ancient specimens.

Authors: Mathov Y Nissim-Rafinia M Leibson C et al.

Source: Nature ecology & evolution [Nat Ecol Evol] 2025 Oct; Vol. 9 (10), pp. 1962.

Publication Type: Published Erratum

Journal Info: Publisher: Springer Nature Country of Publication: England NLM ID: 101698577 Publication Model: Print Cited Medium: Internet ISSN: 2397-334X (Electronic) Linking ISSN: 2397334X NLM ISO Abbreviation: Nat Ecol Evol Subsets: MEDLINE; In Process

AI‐Driven IoT Botnet Detection: Strengthening Cybersecurity Through Advanced Machine Learning Techniques.

Authors: Al-Naimi, Aysha Baydoun, Ali Alazab, Moutaz et al.

Source: International Journal of Distributed Sensor Networks; 7/15/2026, Vol. 2026, p1-17, 17p

RoAM: computational reconstruction of ancient methylomes and identification of differentially methylated regions.

Authors: Mathov Y Rosen N Leibson C et al.

Source: Genome biology [Genome Biol] 2025 Sep 04; Vol. 26 (1), pp. 266. Date of Electronic Publication: 2025 Sep 04.

Publication Type: Journal Article

Journal Info: Publisher: BioMed Central Ltd Country of Publication: England NLM ID: 100960660 Publication Model: Electronic Cited Medium: Internet ISSN: 1474-760X (Electronic) Linking ISSN: 14747596 NLM ISO Abbreviation: Genome Biol Subsets: MEDLINE

Large‐Scale Benchmarking of Intrusion Detection Datasets With GPU‐Accelerated Data Pipelines, Complexity Analysis, and Model Evaluation.

Authors: Aragão, Marcelo V. C. Figueiredo, Felipe A. P. de Mafra, Samuel B. et al.

Source: International Journal of Intelligent Systems; 5/8/2026, Vol. 2026, p1-30, 30p

Deep learning for intrusion detection in emerging technologies: a comprehensive survey and new perspectives.

Authors: Neto, Euclides Carlos Pinto Iqbal, Shahrear Buffett, Scott et al.

Source: Artificial Intelligence Review; Nov2025, Vol. 58 Issue 11, p1-63, 63p

Towards Privacy-Preserving Deep Learning for Intelligent IoT Botnet Detection.

Authors: Rasool, Ariwan M. Safa, Nader Sohrabi Mbarushimana, Consolee

Source: Applied Sciences (2076-3417); Feb2026, Vol. 16 Issue 3, p1665, 68p

eMQTT Traffic Generator for IoT Intrusion Detection Systems.

Authors: Ortega-Moody, Jorge Isaza, Cesar Jenab, Kouroush et al.

Source: Future Internet. Apr2026, Vol. 18 Issue 4, p203. 20p.

A comprehensive survey on deep learning‐based intrusion detection systems in Internet of Things (IoT).

Authors: Al‐Haija, Qasem Abu Droos, Ayat

Source: Expert Systems; Feb2025, Vol. 42 Issue 2, p1-46, 46p

A Survey of Cross-Layer Security for Resource-Constrained IoT Devices.

Authors: Altaibek, Mamyr Issainova, Aliya Aidynov, Tolegen et al.

Source: Applied Sciences (2076-3417); Sep2025, Vol. 15 Issue 17, p9691, 43p

Federated Learning-Based Intrusion Detection in IoT Networks: Performance Evaluation and Data Scaling Study.

Authors: Albanbay, Nurtay Tursynbek, Yerlan Graffi, Kalman et al.

Source: Journal of Sensor & Actuator Networks; Aug2025, Vol. 14 Issue 4, p78, 24p

Massive IoT network traffic analysis using ML and DL methods: an empirical evaluation.

Authors: Singh, Nongthombam Joychandra Singh, Khumukcham Robindro Hoque, Nazrul et al.

Source: Journal of Supercomputing; Jul2025, Vol. 81 Issue 10, p1-48, 48p

Challenges in detecting security threats in WoT: a systematic literature review.

Authors: Sardar, Ruhma Anees, Tayyaba Al-Shamayleh, Ahmad Sami et al.

Source: Artificial Intelligence Review; Jul2025, Vol. 58 Issue 7, p1-57, 57p

SGGAA: a robust adversarial generation based on synthesizing point cloud and mesh space.

Authors: Hu, Ruihan Yang, Rui

Source: Neural Computing & Applications; Jun2025, Vol. 37 Issue 18, p12767-12789, 23p

Development of a robust model for identifying vulnerabilities in IoT devices via binary and multiclass deep neural network classification.

Authors: Jain, Richa Kumar, Ashok

Source: Journal of Supercomputing; Jun2025, Vol. 81 Issue 8, p1-36, 36p

A Machine-Learning-Based Approach for the Detection and Mitigation of Distributed Denial-of-Service Attacks in Internet of Things Environments.

Authors: Berríos, Sebastián Garcia, Sebastián Hermosilla, Pamela et al.

Source: Applied Sciences (2076-3417); Jun2025, Vol. 15 Issue 11, p6012, 26p

P2ADF: a privacy-preserving attack detection framework in fog-IoT environment.

Authors: Kaur, Jasleen Agrawal, Alka Khan, Raees Ahmad

Source: International Journal of Information Security; Aug2023, Vol. 22 Issue 4, p749-762, 14p

Comparative Review of the Intrusion Detection Systems Based on Federated Learning: Advantages and Open Challenges.

Authors: Fedorchenko, Elena Novikova, Evgenia Shulepov, Anton

Source: Algorithms. Jul2022, Vol. 15 Issue 7, p247-N.PAG. 26p.

Zero-day attack detection: a systematic literature review.

Authors: Ahmad, Rasheed Alsmadi, Izzat Alhamdani, Wasim et al.

Source: Artificial Intelligence Review; Oct2023, Vol. 56 Issue 10, p10733-10811, 79p

Robust and Lightweight Federated Learning for NB-IoT Security: A Blockchain-Verified CNN-RNN Approach.

Authors: Özmen, Gonca Yiltas-Kaplan, Derya

Source: Sensors (14248220). Jun2026, Vol. 26 Issue 11, p3578. 25p.

Self-Organizing Neural Grove for Malware Detection in IoT Edge Devices †.

Authors: Inoue, Hirotaka Komura, Tsukasa Hashimoto, Ibuki

Source: Sensors (14248220). Jun2026, Vol. 26 Issue 11, p3399. 12p.