Preventing Spoofing Threats in IoT: Machine Learning Approaches for Intrusion Detection
The safety and reliability of Internet of Things (IoT) networks have to be guaranteed because
of the quick spread of IoT devices. Significant risks to IoT deployments come from spoofing …
of the quick spread of IoT devices. Significant risks to IoT deployments come from spoofing …
Using Support Vector Machine to Detect and Classify the Alzheimer Disease
S Vashisht, B Sharma, R Chauhan… - 2023 3rd International …, 2023 - ieeexplore.ieee.org
Alzheimer's disease is a neurological condition that gradually affects memory, thinking, and
reasoning abilities as well as daily functioning. The majority of people with this condition are …
reasoning abilities as well as daily functioning. The majority of people with this condition are …
IoT Security in the Age of Botnets: Supervised Learning Strategies for Attack Detection
New security problems have emerged due to the proliferation of Internet of Things (IoT)
devices. There is a serious threat to data integrity and network stability from IoT botnets …
devices. There is a serious threat to data integrity and network stability from IoT botnets …
Guarding Against IoT Threats: An Analysis of Intrusion Detection with the Kitsune Attack Dataset
The extensive adoption of Internet of Things (IoT) devices has resulted in previously
unheard-of levels of connectedness and ease, but it has also created new cybersecurity …
unheard-of levels of connectedness and ease, but it has also created new cybersecurity …
Future Perspective and Emerging Trends in Computational Intelligence
C Prabha - Intelligent Data Analytics for Bioinformatics and …, 2024 - Wiley Online Library
An emerging discipline leading the bioinformatics and biomedical system is Computational
Intelligence (CI). To solve the toughest challenges in disease understanding and healthcare …
Intelligence (CI). To solve the toughest challenges in disease understanding and healthcare …
Implementing Gradient Boosting Techniques for Real-Time Attack Detection in Vehicular Networks
Several attacks pose serious dangers to vehicular networks (VN), crucial to creating smart
transportation systems (ITS). Due to ITS, VN has become more important since it allows for …
transportation systems (ITS). Due to ITS, VN has become more important since it allows for …
Unveiling Backdoor Attacks in Networking with Machine Learning Approaches
The maintenance of cybersecurity and the protection of sensitive information depend on
detecting Backdoor attacks in network environments. This study uses the UNSW-NB15 …
detecting Backdoor attacks in network environments. This study uses the UNSW-NB15 …
Securing Smart Homes: Machine Learning Approaches for Detecting Reconnaissance Attacks
The widespread use of smart home gadgets has resulted in heightened susceptibilities and
the possibility of being exploited by cybercriminals, specifically through reconnaissance …
the possibility of being exploited by cybercriminals, specifically through reconnaissance …
Optimizing DoS Attack Detection in Healthcare Systems Through Ensemble Learning
The healthcare industry is increasingly vulnerable to cyberattacks, particularly Denial of
Service (DoS) attacks, because of the heavy use of digital technology in this field. Serious …
Service (DoS) attacks, because of the heavy use of digital technology in this field. Serious …
IoT-POT: Machine Learning-based Detection of Mirai Botnet Attacks in IoT
The Mirai botnet attack has become a serious threat to Internet of Things (IoT) devices
because it can undermine network security by launching large-scale attacks by taking …
because it can undermine network security by launching large-scale attacks by taking …