" Get in Researchers; We're Measuring Reproducibility": A Reproducibility Study of Machine Learning Papers in Tier 1 Security Conferences
D Olszewski, A Lu, C Stillman, K Warren… - Proceedings of the …, 2023 - dl.acm.org
Reproducibility is crucial to the advancement of science; it strengthens confidence in
seemingly contradictory results and expands the boundaries of known discoveries …
seemingly contradictory results and expands the boundaries of known discoveries …
Point cloud analysis for ML-based malicious traffic detection: Reducing majorities of false positive alarms
As an emerging security paradigm, machine learning (ML) based malicious traffic detection
is an essential part of automatic defense against network attacks. Powered by dedicated …
is an essential part of automatic defense against network attacks. Powered by dedicated …
Detecting tunneled flooding traffic via deep semantic analysis of packet length patterns
Distributed denial-of-service (DDoS) protection services capture various flooding attacks by
analyzing traffic features. However, existing services are unable to accurately detect …
analyzing traffic features. However, existing services are unable to accurately detect …
SoK: Pragmatic assessment of machine learning for network intrusion detection
G Apruzzese, P Laskov… - 2023 IEEE 8th European …, 2023 - ieeexplore.ieee.org
Machine Learning (ML) has become a valuable asset to solve many real-world tasks. For
Network Intrusion Detection (NID), however, scientific advances in ML are still seen with …
Network Intrusion Detection (NID), however, scientific advances in ML are still seen with …
Seiot: Detecting anomalous semantics in smart homes via knowledge graph
Existing IoT Network Anomaly Detection Systems (NADSes) typically treat IoT devices as
independent entities and model them by Euclidean space features. These approaches suffer …
independent entities and model them by Euclidean space features. These approaches suffer …
Under the Dark: A Systematical Study of Stealthy Mining Pools (Ab) use in the Wild
Cryptocurrency mining is a crucial operation in blockchains, and miners often join mining
pools to increase their chances of earning rewards. However, the energy-intensive nature of …
pools to increase their chances of earning rewards. However, the energy-intensive nature of …
[HTML][HTML] A convolutional autoencoder architecture for robust network intrusion detection in embedded systems
Security threats are becoming an increasingly relevant concern in cyber–physical systems.
Cyber attacks on these systems are not only common today but also increasingly …
Cyber attacks on these systems are not only common today but also increasingly …
Prevention of cryptojacking attacks in business and FinTech applications
More than 2000 different cryptocurrencies are currently available in business and FinTech
applications. Cryptocurrency is a digital payment system that does not rely on banks to verify …
applications. Cryptocurrency is a digital payment system that does not rely on banks to verify …
Magtracer: Detecting GPU cryptojacking attacks via magnetic leakage signals
GPU cryptojacking is an attack that hijacks GPU resources of victims for cryptocurrency
mining. Such attack is becoming an emerging threat to both local hosts and cloud platforms …
mining. Such attack is becoming an emerging threat to both local hosts and cloud platforms …
Dissecting the Infrastructure Used in Web-based Cryptojacking: A Measurement Perspective
A Adeniran, K Human, D Mohaisen - arXiv preprint arXiv:2408.03426, 2024 - arxiv.org
This paper conducts a comprehensive examination of the infrastructure supporting
cryptojacking operations. The analysis elucidates the methodologies, frameworks, and …
cryptojacking operations. The analysis elucidates the methodologies, frameworks, and …