Temporal association rule mining: An overview considering the time variable as an integral or implied component
Association rules are commonly used to provide decision‐makers with knowledge that helps
them to make good decisions. Most of the published proposals mine association rules …
them to make good decisions. Most of the published proposals mine association rules …
A feature similarity machine learning model for ddos attack detection in modern network environments for industry 4.0
S Sambangi, L Gondi, S Aljawarneh - Computers and Electrical …, 2022 - Elsevier
Recent advancements in artificial intelligence and machine learning technologies have laid
the flagstone for the fourth industrial revolution, Industry 4.0. The industry 4.0 is at a very …
the flagstone for the fourth industrial revolution, Industry 4.0. The industry 4.0 is at a very …
GARUDA: Gaussian dissimilarity measure for feature representation and anomaly detection in Internet of things
SA Aljawarneh, R Vangipuram - The Journal of Supercomputing, 2020 - Springer
The objective of any anomaly detection system is to efficiently detect several types of
malicious traffic patterns that cannot be detected by conventional firewall systems …
malicious traffic patterns that cannot be detected by conventional firewall systems …
Enhanced detection of epileptic seizure using EEG signals in combination with machine learning classifiers
W Mardini, MMB Yassein, R Al-Rawashdeh… - IEEE …, 2020 - ieeexplore.ieee.org
Electroencephalogram (EEG) is one of the most powerful tools that offer valuable
information related to different abnormalities in the human brain. One of these abnormalities …
information related to different abnormalities in the human brain. One of these abnormalities …
Similarity based feature transformation for network anomaly detection
The fundamental objective behind any network intrusion detection system is to automate the
detection process whenever intrusions occur in the network. The problem of the network …
detection process whenever intrusions occur in the network. The problem of the network …
Detection of epileptic seizures from EEG signals by combining dimensionality reduction algorithms with machine learning models
Epilepsy is a neurological condition that affects the central nervous system. While its effects
are different for each person, they mostly include abnormal behaviour, periods of loss of …
are different for each person, they mostly include abnormal behaviour, periods of loss of …
A machine learning approach for imputation and anomaly detection in IoT environment
R Vangipuram, RK Gunupudi, VK Puligadda… - Expert …, 2020 - Wiley Online Library
The problem of anomaly and attack detection in IoT environment is one of the prime
challenges in the domain of internet of things that requires an immediate concern. For …
challenges in the domain of internet of things that requires an immediate concern. For …
[PDF][PDF] Plant disease classification using deep bilinear CNN
Plant diseases have become a major threat in farming and provision of food. Various plant
diseases have affected the natural growth of the plants and the infected plants are the …
diseases have affected the natural growth of the plants and the infected plants are the …
Study of Detection of DDoS attacks in cloud environment Using Regression Analysis
Distributed Denial of Service (DDoS) attacks in the cloud environment are not as simple as
the same attacks which occur in the traditional physical network environment. Not only one …
the same attacks which occur in the traditional physical network environment. Not only one …
VRKSHA: A novel multi-tree based sequential approach for seasonal pattern mining
S Aljawarneh, V Radhakrishna, A Cheruvu - Proceedings of the Fourth …, 2018 - dl.acm.org
Mining association patterns from a time-stamped temporal database is implicitly associated
with task of scanning input database. Finding supports of itemsets requires scanning the …
with task of scanning input database. Finding supports of itemsets requires scanning the …