Results 81 to 90 of about 11,129 (248)
New P2P Botnets Classification And Detection Framework [PDF]
Botnets is a tool for high-profile cyber-attack. It is a collection of compromised computer infected with advance malware that allows an attacker to remotely control them.
Abdullah, Raihana Syahirah
core
Overview of the proposed work. ABSTRACT Identifying cyber threats maintains the security and operational stability of smart grid systems because they experience escalating attacks that endanger both operating data reliability and system stability and electricity grid performance.
Priya R. Karpaga +3 more
wiley +1 more source
Edge‐Oriented DoS/DDoS Intrusion Detection and Supervision Platform
ABSTRACT This work presents an Edge Node‐Oriented DoS/DDoS Intrusion Detection and Monitoring Platform, a novel anomaly detection system based on temporal analysis with machine learning (ML) and deep learning (DL) algorithms, specifically designed to operate on edge servers with limited resources.
Geraldo Eufrazio Martins Júnior +3 more
wiley +1 more source
ZombieCoin 2.0: managing next-generation botnets using Bitcoin
Botnets are the preeminent source of online crime and arguably one of the greatest threats to the Internet infrastructure. In this paper, we present ZombieCoin, a botnet command-and-control (C&C) mechanism that leverages the Bitcoin network.
S. Ali +3 more
semanticscholar +1 more source
ABSTRACT Zero‐day exploits remain challenging to detect because they often appear in unknown distributions of signatures and rules. The article entails a systematic review and cross‐sectional synthesis of four fundamental model families for identifying zero‐day intrusions, namely, convolutional neural networks (CNN), deep neural networks (DNN ...
Abdullah Al Siam +3 more
wiley +1 more source
Political Bots on Twitter in #Ecuador2017 Presidential Campaigns
We studied the behavior of campaign hashtags on Twitter in the second round of Ecuador 2017 presidential elections. The study analyzed 10 trending hashtags attacking opponents.
Iria Puyosa
doaj +1 more source
This study introduces a two‐phase method for detecting DDoS attacks in cloud environments using ensemble feature fusion and a hybrid CNN‐LSTM model. By combining meta‐heuristic feature selection with deep learning, the approach achieves over 99% accuracy on benchmark datasets, reducing false positives and improving cybersecurity resilience.
Hind Saad Hussein +3 more
wiley +1 more source
Exploiting Vision Transformer and Ensemble Learning for Advanced Malware Classification
Overview of the proposed RF–ViT ensemble for multi‐class malware classification. Textual (BoW/byte‐frequency) and visual representations are combined via a product rule, achieving improved accuracy and robustness over individual models. ABSTRACT Malware remains a significant concern for modern digital systems, increasing the need for reliable and ...
Fadi Makarem +4 more
wiley +1 more source
Detecting Botnets Through Log Correlation [PDF]
Botnets, which consist of thousands of compromised machines, can cause a significant threat to other systems by launching Distributed Denial of Service attacks, keylogging, and backdoors. In response to this threat, new effective techniques are needed to
Al-Hammadi, Yousof +5 more
core +1 more source
RRF‐IPS: A Real‐Time Reputation‐Based Intrusion Prevention System
RRF‐IPS: A Real‐Time Reputation‐Based Intrusion Prevention System. ABSTRACT With the rapid development of technologies such as cloud computing and the Internet of Things, organizations face the thorny reality that network attacks are becoming increasingly diverse, covert, and intelligent.
Zhenghao Qian +7 more
wiley +1 more source

