Results 51 to 60 of about 438,107 (214)
Hybrid DDoS Detection Framework Using Matching Pursuit Algorithm
IEEE Access, 2020 Although a considerable amount of research has been done on DDoS attacks, it still poses a severe threat to many businesses and internet service providers. DDoS attacks commonly generate a high amount of network traffic.
Derya Erhan, Emin Anarim
doaj +1 more source
CAAI Transactions on Intelligence Technology, EarlyView.Abstract Internet of Medical Things (IoMT) has typical advancements in the healthcare sector with rapid potential proof for decentralised communication systems that have been applied for collecting and monitoring COVID‐19 patient data. Machine Learning algorithms typically use the risk score of each patient based on risk factors, which could help ...
Chandramohan Dhasaratha +9 more
wiley +1 more source
DDoS Never Dies? An IXP Perspective on DDoS Amplification Attacks [PDF]
, 2021 To appear at PAM ...
Daniel Kopp +2 more
openaire +4 more sources
Graph neural network‐based attack prediction for communication‐based train control systems
CAAI Transactions on Intelligence Technology, EarlyView.Abstract The Advanced Persistent Threats (APTs) have emerged as one of the key security challenges to industrial control systems. APTs are complex multi‐step attacks, and they are naturally diverse and complex. Therefore, it is important to comprehend the behaviour of APT attackers and anticipate the upcoming attack actions.
Junyi Zhao +3 more
wiley +1 more source
DoS and DDoS Attacks: Defense, Detection and Traceback Mechanisms - A Survey [PDF]
, 2014 Denial of Service (DoS) or Distributed Denial of Service (DDoS) attacks are typically explicit attempts to exhaust victim2019;s bandwidth or disrupt legitimate users2019; access to services.
K.Munivara Prasad
core
Mitigation of Distributed Denial of Service Attacks in the Cloud
Cybernetics and Information Technologies, 2017 Cybersecurity attacks resulting in loss of availability of cloud services can have significantly higher impact than those in the traditional stand-alone enterprise setups.
Alosaimi Wael +4 more
doaj +1 more source
Quantum Machine Learning for Cybersecurity: A Taxonomy and Future Directions
Software: Practice and Experience, Volume 56, Issue 12, Page 1538-1556, December 2026.ABSTRACT Context The rapid increase in cyber threats, coupled with increasingly sophisticated attack strategies and the exponential growth of data in recent years, has exposed significant limitations in classical machine learning, rule‐based, and signature‐based defense mechanisms.
Siva Sai +5 more
wiley +1 more source
Base Semantics—A Novel Approach for Minimizing Malware Detection Rules
SECURITY AND PRIVACY, Volume 9, Issue 6, November/December 2026.ABSTRACT The rapid evolution of malware variants has increasingly undermined traditional signature‐based detection techniques, which are easily evaded through obfuscation and polymorphism that preserve malicious functionality. This challenge is particularly acute in Internet of Things (IoT) environments, where device heterogeneity, resource constraints,
Khizar Hayat +5 more
wiley +1 more source
The Scientific World Journal, 2015 The growth of web technology has brought convenience to our life, since it has become the most important communication channel. However, now this merit is threatened by complicated network-based attacks, such as denial of service (DoS) and distributed ...
Mohammed A. Saleh, Azizah Abdul Manaf
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Retrieval‐Based Deep Hybrid Models for Robust Network Intrusion Detection
SECURITY AND PRIVACY, Volume 9, Issue 6, November/December 2026.ABSTRACT A retrieval‐based deep hybrid model couples a learned encoder with a non‐parametric k‐nearest‐neighbors module that, at inference time, retrieves training records and conditions its predictions on the local neighborhood. Despite strong results on tabular benchmarks, such hybrids and several recent deep tabular architectures have not been ...
Bimal Parakkal +2 more
wiley +1 more source