Results 91 to 100 of about 707,343 (186)

Peer Review #2 of "Malware detection using static analysis in Android: a review of FeCO (features, classification, and obfuscation) (v0.3)"

, 2021
  +5 more sources

EDSSR: a secure and power-aware opportunistic routing scheme for WSNs

Scientific Reports
Motivated by the pivotal role of routing in Wireless Sensor Networks (WSNs) and the prevalent security vulnerabilities arising from existing protocols, this research tackles the inherent challenges of securing WSNs.
Ruili Yang, Manoj A. Patil, Potu Narayana, D. Jayaram, K. Keerthi, N. SudhakarYadav, Premkumar Chithaluru, Sunil Kumar, Diaa Salama Abd Elminaam, Deema Mohammed Alsekait   +9 more
doaj   +1 more source

SHRED: An Ensemble-Based Machine Learning Model to Sift Email Messages for Real-Time Spam Detection

IEEE Access
The rapid expansion of email usage has been paralleled by a significant rise in spam, which not only clutters inboxes but also spreads malware and introduces serious security threats.
Shahid Alam, Amina Jameel, Zahida Parveen, Ehab Alnfrawy   +3 more
doaj   +1 more source

Efficient feature ranked hybrid framework for android Iot malware detection. [PDF]

Sci Rep
Saeed NH, Hamza AA, Sobh MA, Bahaa-Eldin AM.   +3 more
europepmc   +1 more source

Improving malware detection performance using hybrid deep representation learning with heuristic search algorithms. [PDF]

Sci Rep
Anuradha A, Chouhan AS, Srinivas Rao S.
europepmc   +1 more source

A bio inspired hybrid optimization framework for efficient real time malware detection. [PDF]

Sci Rep
Abualhaj MM, Al-Mimi H, Al-Zyoud M, Al-Khatib SN, Daoud MS, Al-Aqrabi H, Anbar M, Shalaldeh A.   +7 more
europepmc   +1 more source

A hierarchical deep learning framework with doubly regularized loss for robust malware detection and family categorization. [PDF]

Sci Rep
Abed Alsaedi S, Alwateer M, Helal Alharbi N, Magdy Balaha H, M Aboelnaga M, Badawy M, A Elhosseini M.   +6 more
europepmc   +1 more source

A distributed framework for zero-day malware detection using federated ensemble models. [PDF]

PLoS One
Ishfaq H, Shah JH, Saleem R, Afzal M.
europepmc   +1 more source

MH-1M: A 1.34 Million-Sample Multi-Feature Android Malware Dataset with Rich Metadata. [PDF]

Sci Data
Bragança H, Kreutz D, Rocha V, Assolin J, Feitosa E.   +4 more
europepmc   +1 more source

Integrating NLP and Ensemble Learning into Next-Generation Firewalls for Robust Malware Detection in Edge Computing. [PDF]

Sensors (Basel)
Moila RL, Velempini M.
europepmc   +1 more source