Evaluation of UDP-Based DDoS Attack Detection by Neural Network Classifier with Convex Optimization and Activation Functions.

K Dasari, S Mekala, JR Kaka - Ingénierie des Systèmes d' …, 2024 - search.ebscohost.com
Abstract Distributed Denial of Service (DDoS) stands as a critical cybersecurity concern,
representing a malicious tactic employed by hackers to disrupt online services, network …

A deep neural network prediction method for diabetes based on Kendall's correlation coefficient and attention mechanism

X Qi, Y Lu, Y Shi, H Qi, L Ren - Plos one, 2024 - journals.plos.org
Diabetes is a chronic disease, which is characterized by abnormally high blood sugar levels.
It may affect various organs and tissues, and even lead to life-threatening complications …

A deep CNN-based framework for distributed denial of services (DDoS) attack detection in internet of things (IoT)

BB Gupta, A Gaurav, V Arya, P Kim - Proceedings of the 2023 …, 2023 - dl.acm.org
As the number of connected devices continues to rise, protecting those networks against
DDoS attacks is more important than ever. Due to IoT devices' specific features and limited …

SynFlood DDoS attack detection with SVM kernels using uncorrelated feature subsets selected by Pearson, spearman and Kendall correlation methods

KB Dasari, N Devarakonda - 2022 second international …, 2022 - ieeexplore.ieee.org
Data availability and protection are getting more important nowadays due to the exponential
growth of digital usage around the world. In cyber attacks Distributed Denial of Service …

Evaluation of svm kernels with multiple uncorrelated feature subsets selected by multiple correlation methods for reflection amplification DDoS attacks detection

KB Dasari, N Devarakonda - Applied Computing for Software and Smart …, 2023 - Springer
Data availability is one of the primary principles of information security. Distributed Denial of
Service (DDoS) is a typical cyber security attack of the DOS family to deny data availability to …

[PDF][PDF] A comparative analysis of machine learning models for crop recommendation in India

DMS Reddy, UR Neerugatti - Revue d'Intelligence …, 2023 - pdfs.semanticscholar.org
Agriculture serves as the mainstay of India's economy, bearing a vital responsibility in
nourishing an expanding populace. The thriving of this sector is contingent upon numerous …

Ensemble Assisted Multi-Feature Learnt Social Media Link Prediction Model Using Machine Learning Techniques.

U Channabasava… - Revue d'Intelligence …, 2022 - search.ebscohost.com
In this paper a robust consensus-based ensemble assisted multi-feature learnt social media
link prediction model is developed. Unlike classical methods, a multi-level enhancement …

Detection syn flood and UDP lag attacks based on machine learning using AdaBoost

NH Syafiuddin, S Mandala… - … Conference on Data …, 2023 - ieeexplore.ieee.org
Syn flood is a commonly used Distributed Denial-of-Service (DDoS) attack that aims to
overwhelm a server by sending a large number of Transmission Control Protocol (TCP) SYN …

Machine Learning for Cloud Data Classification and Anomaly Intrusion Detection

L Megouache, A Zitouni, S Sadouni… - Revue des Sciences et …, 2024 - hal.science
The sheer volume of applications, data and users working in the cloud creates an ecosystem
far too large to protect against possible attacks. Several attack detection mechanisms have …

Security Analysis of SQL Injection Attacks on Multimedia and Journal-Services Sites Using Concatenated Input Validation and Parsing Method (CIVP)

MC Wijaya - Ingenierie des Systemes d'Information, 2024 - search.proquest.com
Web applications and databases continue to face grave danger from SQL injection attacks,
which can result in unauthorized access, data modification, and system compromise. This …