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Anomaly detection IDS for detecting DoS attacks in IoT networks based on machine learning algorithms
Widespread and ever-increasing cybersecurity attacks against Internet of Things (IoT)
systems are causing a wide range of problems for individuals and organizations. The IoT is …
systems are causing a wide range of problems for individuals and organizations. The IoT is …
Application of artificial intelligence to network forensics: Survey, challenges and future directions
Network forensics focuses on the identification and investigation of internal and external
network attacks, the reverse engineering of network protocols, and the uninstrumented …
network attacks, the reverse engineering of network protocols, and the uninstrumented …
Knowledge-based anomaly detection: Survey, challenges, and future directions
Due to the rapidly increasing number of Internet-connected objects, a huge amount of data
is created, stored, and shared. Depending on the use case, this data is visualized, cleaned …
is created, stored, and shared. Depending on the use case, this data is visualized, cleaned …
Detection and classification of novel attacks and anomaly in IoT network using rule based deep learning model
Attackers are now using sophisticated techniques, like polymorphism, to change the attack
pattern for each new attack. Thus, the detection of novel attacks has become the biggest …
pattern for each new attack. Thus, the detection of novel attacks has become the biggest …
Securing the Internet of Things in Logistics: Challenges, Solutions, and the Role of Machine Learning in Anomaly Detection
Internet of things (IoT), a network of interconnected devices capable of collecting, storing,
analyzing, and transmitting data, has garnered significant attention. Its widespread adoption …
analyzing, and transmitting data, has garnered significant attention. Its widespread adoption …
Robust machine learning based Intrusion detection system using simple statistical techniques in feature selection
There are serious security issues with the quick growth of IoT devices, which are
increasingly essential to Industry 4.0. These gadgets frequently function in challenging …
increasingly essential to Industry 4.0. These gadgets frequently function in challenging …
IoT security using heuristic aided symmetric convolution-based deep temporal convolution network for intrusion detection by extracting multi-cascaded deep attention …
The successful expansion of the Internet of Things (IoT) has obtained cyber criminal's
attention more than ever. The threats on IoT, if they remain unrecognized for a specific time …
attention more than ever. The threats on IoT, if they remain unrecognized for a specific time …
IoT-based smart home security system with machine learning models
The Internet of Things (IoT) has various applications in practice, such as smart homes and
buildings, traffic management, industrial management, and smart farming. On the other …
buildings, traffic management, industrial management, and smart farming. On the other …
[PDF][PDF] Machine learning with data balancing technique for IoT attack and anomalies detection
__________________________________… owadays the significant concern in IoT
infrastructure is anomaly and attack detection from IoT devices. Due to the advanced …
infrastructure is anomaly and attack detection from IoT devices. Due to the advanced …
Analysis and Mortality Prediction using Multiclass Classification for Older Adults with Type 2 Diabetes
R Desure, GJ Krishna - arxiv preprint arxiv:2402.10999, 2024 - arxiv.org
Designing proper treatment plans to manage diabetes requires health practitioners to pay
heed to the individuals remaining life along with the comorbidities affecting them. Older …
heed to the individuals remaining life along with the comorbidities affecting them. Older …