Search Results - (( worm detection a algorithm ) OR ( botnet detection system algorithm ))
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Designing a new model for Trojan horse detection using sequential minimal optimization
Published 2024Conference Paper -
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A new mobile botnet classification based on permission and API calls
Published 2024Subjects:Conference Paper -
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Systematic analysis on mobile botnet detection techniques using genetic algorithm
Published 2024Subjects:Conference Paper -
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Botnet Detection Using a Feed-Forward Backpropagation Artificial Neural Network
Published 2019“…The proposed technique aims to detect Botnet zero-day attack in real time. This technique applies a backpropagation algorithm to the CTU-13 dataset to train and evaluate the Botnet detection classifier. …”
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Botnet detection using automated script / Norfathin Rosli
Published 2020“…This paper is about a Botnet Detection using Automated Script, the programming language is and the operating system is Windows 7. …”
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Improving The Algorithm To Detect Internet Worms
Published 2008“…The aim of this project is to improved algorithm to detect internet worm by two sub algorithm. …”
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Intelligent failure connection algorithm for detecting internet worms
Published 2009“…In this paper, we show that our algorithm can detect new types of worms. This paper shows that intelligent Failure Connection Algorithm (IFCA) operation is faster than traditional algorithm in detecting worms.…”
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A behavior based algorithm to detect spam bots
Published 2009“…Spamming causes illegal consuming of network resources in general and mail system in particular. The objective of this research is to detect the source of spam on the network by detecting the abnormal behaviors that reflect spamming activities. …”
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A traffic signature-based algorithm for detecting scanning internet worms
Published 2009“…In this paper, we propose a method for detecting traffic signature for unknown internet worm. …”
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Intelligent DNA signature detection for internet worms
Published 2011“…Active worms spread in an automated fashion flooding the Internet in a very short time.Slammer worm infected more than 90% of vulnerable machines within 10 minutes on January 25th, 2003.Hence it is necessary to monitor and detect the worms as soon as they are introduced to minimize the damage caused by them.This project concentrates on developing an anti-scanning worm detection system that can automatically detect and control the spread of internet scanning worms without any manual intervention.The Intelligent Failure Connection Algorithm (IFCA) developed in this project can detect both stealth and normal worms within a short time.Experiments conducted as part of the evaluation shows that IFCA detects a worm within two scanning cycles of the worm.This is faster than any of the currently available algorithms or mechanisms reported in the literature.The IFCA uses Artificial Immune System (AIS) for the purpose of monitoring and detecting the worms.The Traffic Signature Algorithm (TSA) developed in the project captures the traffic signature of the worm from the infector when it sends the traffic to the victim.The Intelligent DNA Signature Detection Algorithm (IDNASDA) algorithm works by breaking an infection session into different infection phases, each phase containing a number of different traffic such as Internet Control Message Protocol (ICMP), Transmission Control Protocol (TCP), or User Datagram Protocol (UDP).Finally it converts the traffic signature to DNA signature.The tests carried out show that the IDNASD could detect DNA signature for MSBlaster worm.…”
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An enhanced android botnet detection approach using feature refinement
Published 2019“…In order to detect botnet attacks which causes immense chaos and problems to smartphones, first the Android botnet need to be analysed. …”
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Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level
Published 2024thesis::doctoral thesis -
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A Static Approach towards Mobile Botnet Detection
Published 2016“…In this study we propose a static approach towards mobile botnet detection. This technique combines MD5, permissions, broadcast receivers as well as background services and uses machine learning algorithm to detect those applications that have capabilities for mobile botnets. …”
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IoT-based botnet attacks systematic mapping study of literature
Published 2024journal::journal article -
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A new generation for intelligent anti-internet worm early system detection
Published 2009“…Worm requires host computer with an address on the Internet and any of several vulnerabilities to create a big threat environment.We propose intelligent early system detection mechanism for detecting internet worm.The mechanism is combined of three techniques: Failure Connection Detection (FCD) which concerns with detecting the internet worm and stealthy worm in which computer infected by the worm by using Artificial Immune System; and the Traffic Signature Detection (TSD) which responsible for detecting traffic signature for the worm; and the DNA Filtering Detection (DNAFD) which converts traffic signature to DNA signature and sending it to all computer that connected with the router to create a firewall for new worms.Our proposed algorithm can detect difficult stealthy internet worm in addition to detecting unknown internet worm.…”
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An Innovative Signature Detection System for Polymorphic and Monomorphic Internet Worms Detection and Containment
Published 2012“…Anomaly detection systems can detect unknown worms but usually suffer from a high false alarm rate. …”
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Server scanning worm detection by using intelligent failure connection algorithm
Published 2010“…Our proposal decreases the false alarm in Intelligent Failure Connection Algorithm (IFCA). Our proposal also works when the computer is infected by the worm and IFCDA detected the worm, many computers that are connected through the internet will receive the warning by using our proposal. …”
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