Adversarial machine learning attacks against intrusion detection systems: A survey on strategies and defense
A Alotaibi, MA Rassam - Future Internet, 2023 - mdpi.com
Concerns about cybersecurity and attack methods have risen in the information age. Many
techniques are used to detect or deter attacks, such as intrusion detection systems (IDSs) …
techniques are used to detect or deter attacks, such as intrusion detection systems (IDSs) …
Towards secure intrusion detection systems using deep learning techniques: Comprehensive analysis and review
Providing a high-performance Intrusion Detection System (IDS) can be very effective in
controlling malicious behaviors and cyber-attacks. Regarding the ever-growing negative …
controlling malicious behaviors and cyber-attacks. Regarding the ever-growing negative …
Imbalanced data classification: A KNN and generative adversarial networks-based hybrid approach for intrusion detection
With the continuous emergence of various network attacks, it is becoming more and more
important to ensure the security of the network. Intrusion detection, as one of the important …
important to ensure the security of the network. Intrusion detection, as one of the important …
An enhanced AI-based network intrusion detection system using generative adversarial networks
As communication technology advances, various and heterogeneous data are
communicated in distributed environments through network systems. Meanwhile, along with …
communicated in distributed environments through network systems. Meanwhile, along with …
A survey on security and privacy issues in modern healthcare systems: Attacks and defenses
Recent advancements in computing systems and wireless communications have made
healthcare systems more efficient than before. Modern healthcare devices can monitor and …
healthcare systems more efficient than before. Modern healthcare devices can monitor and …
Practical gan-based synthetic ip header trace generation using netshare
We explore the feasibility of using Generative Adversarial Networks (GANs) to automatically
learn generative models to generate synthetic packet-and flow header traces for networking …
learn generative models to generate synthetic packet-and flow header traces for networking …
Generative deep learning to detect cyberattacks for the IoT-23 dataset
N Abdalgawad, A Sajun, Y Kaddoura… - IEEE …, 2021 - ieeexplore.ieee.org
The rapid growth of Internet of Things (IoT) is expected to add billions of IoT devices
connected to the Internet. These devices represent a vast attack surface for cyberattacks. For …
connected to the Internet. These devices represent a vast attack surface for cyberattacks. For …
IMIDS: An intelligent intrusion detection system against cyber threats in IoT
The increasing popularity of the Internet of Things (IoT) has significantly impacted our daily
lives in the past few years. On one hand, it brings convenience, simplicity, and efficiency for …
lives in the past few years. On one hand, it brings convenience, simplicity, and efficiency for …
EIDM: deep learning model for IoT intrusion detection systems
Abstract Internet of Things (IoT) is a disruptive technology for the future decades. Due to its
pervasive growth, it is susceptible to cyber-attacks, and hence the significance of Intrusion …
pervasive growth, it is susceptible to cyber-attacks, and hence the significance of Intrusion …
A review of anomaly detection strategies to detect threats to cyber-physical systems
N Jeffrey, Q Tan, JR Villar - Electronics, 2023 - mdpi.com
Cyber-Physical Systems (CPS) are integrated systems that combine software and physical
components. CPS has experienced rapid growth over the past decade in fields as disparate …
components. CPS has experienced rapid growth over the past decade in fields as disparate …