Anomaly Detection IDS for Detecting DoS Attacks in IoT Networks Based on Machine Learning Algorithms
E Altulaihan, MA Almaiah, A Aljughaiman - Sensors, 2024 - mdpi.com
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 …
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 …
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 …
[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 …
[PDF][PDF] Methodological choices in machine learning applications
Machine learning is a subset of artificial intelligence in which a machine has an ability to
learn and employ complex algorithms to impersonate human behavior. Development of a …
learn and employ complex algorithms to impersonate human behavior. Development of a …
Analysis of deep learning models for anomaly detection in time series IoT sensor data
U Sachdeva, PR Vamsi - Proceedings of the 2022 Fourteenth …, 2022 - dl.acm.org
The anomaly detection in Internet of Things (IoT) sensor data has become an important
research area because of the possibility of noise and unavailability of labels in the sensors …
research area because of the possibility of noise and unavailability of labels in the sensors …
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 …
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 …
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 …