Big Data Analytics for Improved Risk Management and Customer Segregation in Banking Applications
Volume-3 | Issue-3
Design of Deep Learning Algorithm for IoT Application by Image based Recognition
Volume-3 | Issue-3
Analysis of Serverless Computing Techniques in Cloud Software Framework
Volume-3 | Issue-3
Health Record Management System – A Web-based Application
Volume-3 | Issue-4
A Novel Signal Processing Based Driver Drowsiness Detection System
Volume-3 | Issue-3
IoT Based Monitoring and Control System using Sensors
Volume-3 | Issue-2
Secure Data Sharing Platform for Portable Social Networks with Power Saving Operation
Volume-3 | Issue-3
Review of Internet of Wearable Things and Healthcare based Computational Devices
Volume-3 | Issue-3
Stock Index Prediction with Financial News Sentiments and Technical Indicators
Volume-4 | Issue-3
Hybrid Framework on Automatic Detection and Recognition of Traffic Display board Signs
Volume-3 | Issue-3
Suspicious Human Activity Detection System
Volume-2 | Issue-4
ROBOT ASSISTED SENSING, CONTROL AND MANUFACTURE IN AUTOMOBILE INDUSTRY
Volume-1 | Issue-3
EFFICIENT RESOURCE ALLOCATION AND QOS ENHANCEMENTS OF IOT WITH FOG NETWORK
Volume-1 | Issue-2
Live Streaming Architectures for Video Data - A Review
Volume-2 | Issue-4
IoT Based Monitoring and Control System using Sensors
Volume-3 | Issue-2
Big Data Analytics for Improved Risk Management and Customer Segregation in Banking Applications
Volume-3 | Issue-3
A Novel Signal Processing Based Driver Drowsiness Detection System
Volume-3 | Issue-3
IoT BASED AIR AND SOUND POLLUTION MONITIORING SYSTEM USING MACHINE LEARNING ALGORITHMS
Volume-2 | Issue-1
Analysis of Serverless Computing Techniques in Cloud Software Framework
Volume-3 | Issue-3
Hybrid Intrusion Detection System for Internet of Things (IoT)
Volume-2 | Issue-4
Volume - 5 | Issue - 3 | september 2023
Published
02 September, 2023
As the digital landscape continues to expand, the complexity and frequency of cyber threats targeting critical information systems also increases. Effective cyber threat detection has become a paramount concern for safeguarding sensitive data and ensuring the uninterrupted operation of various infrastructures. This research introduces a novel approach to cyber threat detection through the design of a greedy algorithm tailored for identifying specific types of threats. The algorithm focuses on a simplified aspect of threat detection, aiming to highlight the potential of greedy algorithms in contributing to the broader field of cybersecurity. The methodology involves monitoring network traffic for signs of port scanning activity, a common precursor to potential cyber-attacks. The algorithm's effectiveness is evaluated in terms of its ability to accurately identify suspicious scanning behavior while minimizing false positives. By presenting this algorithmic framework, the research aims to contribute to the ongoing efforts in enhancing cyber threat detection techniques.
KeywordsCyber Security Privacy Greedy Malware Intrusion Threat
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