Call for Papers:Vol.12 Issue.2

Submission
Last date		 28-Apr-2026
Acceptance Status In One Day
Paper Publish In Two Days
Submit ManuScript

News & Updates

Submit Article

Dear Authors, Article publish in our journal for Volume-12,Issue-2. For article submission on below link: Submit Manuscript


Join As Board

Dear Reviewer, You can join our Reviewer team without given any charges in our journal. Submit Details on below link: Join As Board


Paper Publication Charges

IJARIIE APP
Download Android App

For Authors

Archives

IJARIIE Board

Downloads

Android App

Download IJARIIE APP

Authors

Title: :  DETECT AND MITIGATE INTRUSION DURING CYBER ATTACKS
PaperId: :  20373
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 9 Issue 3 2023
DUI:    16.0415/IJARIIE-20373
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
N Vishal Krishna BhatDayananda Sagar Academy of Technology & Management
Lekhan HYDayananda Sagar Academy of Technology & Management
N PravalikaDayananda Sagar Academy of Technology & Management
Rakshitha MDayananda Sagar Academy of Technology & Management
Rama AbiramiDayananda Sagar Academy of Technology & Management

Abstract

Cybersecurity
Black lists, NIDS, HIDS, malicious, vulnerabilities, SVM’s, ANN’s, trails
An intrusion detection system (IDS) is a type of security technology that tracks hostile or unauthorized activity on computer networks and systems. An IDS's main objective is to spot potential security gaps, record information about them, and notify security administrators so they may take the necessary action. There are two main types of IDS: network based IDS (NIDS) and host-based IDS (HIDS). While HIDS keeps an eye on each individual host system for odd activity, NIDS watches network traffic for suspicious behavior and spots potential dangers. IDS can be further categorized as signature based or anomaly based, depending on the detection technique used. Anomaly-based IDS employ statistical analysis to find changes from expected network behavior, while signature-based IDS compare known harmful activity patterns with observed network traffic. The employment of IDS, which is frequently used in conjunction with other security measures like firewalls and antivirus software, is essential for defending computer networks from different kinds of cyberattacks. Malt Rail is a harmful traffic detection system that makes use of static-trails generated from various antivirus reports and user-defined custom lists, as well as publicly available (black)lists containing malicious and/or generally suspicious trails. A trail can be anything from a domain name (for example, zvpprsensinaix.com for Banjari malware), URL (for example, hXXp://109.162.38.120/harsh02.exe for known malicious executable), IP address (e.g 185.130.5.231 for known attacker) Additionally, it makes use of (optional) sophisticated heuristic methods that can aid in the discovery of new risks (like malware).

Citations

Copy and paste a formatted citation or use one of the links to import into a bibliography manager and reference.

IJARIIE N Vishal Krishna Bhat, Lekhan HY, N Pravalika, Rakshitha M, and Rama Abirami. "DETECT AND MITIGATE INTRUSION DURING CYBER ATTACKS" International Journal Of Advance Research And Innovative Ideas In Education Volume 9 Issue 3 2023 Page 1851-1858
MLA N Vishal Krishna Bhat, Lekhan HY, N Pravalika, Rakshitha M, and Rama Abirami. "DETECT AND MITIGATE INTRUSION DURING CYBER ATTACKS." International Journal Of Advance Research And Innovative Ideas In Education 9.3(2023) : 1851-1858.
APA N Vishal Krishna Bhat, Lekhan HY, N Pravalika, Rakshitha M, & Rama Abirami. (2023). DETECT AND MITIGATE INTRUSION DURING CYBER ATTACKS. International Journal Of Advance Research And Innovative Ideas In Education, 9(3), 1851-1858.
Chicago N Vishal Krishna Bhat, Lekhan HY, N Pravalika, Rakshitha M, and Rama Abirami. "DETECT AND MITIGATE INTRUSION DURING CYBER ATTACKS." International Journal Of Advance Research And Innovative Ideas In Education 9, no. 3 (2023) : 1851-1858.
Oxford N Vishal Krishna Bhat, Lekhan HY, N Pravalika, Rakshitha M, and Rama Abirami. 'DETECT AND MITIGATE INTRUSION DURING CYBER ATTACKS', International Journal Of Advance Research And Innovative Ideas In Education, vol. 9, no. 3, 2023, p. 1851-1858. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/DETECT_AND_MITIGATE_INTRUSION_DURING_CYBER_ATTACKS_ijariie20373.pdf (Accessed : ).
Harvard N Vishal Krishna Bhat, Lekhan HY, N Pravalika, Rakshitha M, and Rama Abirami. (2023) 'DETECT AND MITIGATE INTRUSION DURING CYBER ATTACKS', International Journal Of Advance Research And Innovative Ideas In Education, 9(3), pp. 1851-1858IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/DETECT_AND_MITIGATE_INTRUSION_DURING_CYBER_ATTACKS_ijariie20373.pdf (Accessed : )
IEEE N Vishal Krishna Bhat, Lekhan HY, N Pravalika, Rakshitha M, and Rama Abirami, "DETECT AND MITIGATE INTRUSION DURING CYBER ATTACKS," International Journal Of Advance Research And Innovative Ideas In Education, vol. 9, no. 3, pp. 1851-1858, May-Jun 2023. [Online]. Available: https://ijariie.com/AdminUploadPdf/DETECT_AND_MITIGATE_INTRUSION_DURING_CYBER_ATTACKS_ijariie20373.pdf [Accessed : ].
Turabian N Vishal Krishna Bhat, Lekhan HY, N Pravalika, Rakshitha M, and Rama Abirami. "DETECT AND MITIGATE INTRUSION DURING CYBER ATTACKS." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 9 number 3 ().
Vancouver N Vishal Krishna Bhat, Lekhan HY, N Pravalika, Rakshitha M, and Rama Abirami. DETECT AND MITIGATE INTRUSION DURING CYBER ATTACKS. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2023 [Cited : ]; 9(3) : 1851-1858. Available from: https://ijariie.com/AdminUploadPdf/DETECT_AND_MITIGATE_INTRUSION_DURING_CYBER_ATTACKS_ijariie20373.pdf
BibTex EndNote RefMan RefWorks

Number Of Downloads



Save in Google Drive

Similar-Paper

TitleArea of ResearchAuther NameAction
Unsupervised Contribution-Oriented Learning Model for Social Influence DetectionComputer EngineeringSnehal Mahjaan Download
DESIGN AND IMPLEMENTATION OF A BLUETOOTH-CONTROLLED ROBOTIC CAR USING ARDUINOComputer Mr. Swapnil Sanjay Bafana Download
AI-DRIVEN DEEPFAKE IDENTIFICATION IN REAL TIMEComputer EngineeringPavan Gajanan Bhonde Download
RESQ-BOTComputer Engineering Tiparkar Prathamesh Navnath Download
A Critical Review and Modern Contextualization of the 2009 Distributed Real-Time Computer Network Architecture (DRNA)Computer EngineeringNandishwar EN Download
Block-Chain Based Document Verification System using IPFSComputer EngineeringAkash Santosh Devade Download
A COMPREHENSIVE REVIEW OF DUAL FEATURE-BASED INTRUSION DETECTION SYSTEM FOR IoT NETWORK SECURITYComputer Science and EngineeringShrinidhi Hegde Download
Civica AI: A Politician-Centric Grievance Redressal and Service DirectoryComputer EngineeringKaranjule Dhanashri Bhausaheb Download
A Deep Learning Framework for Mood-Based Music Recommendation via Facial Expression AnalysisComputer Vaibhav Ashok Bhangare Download
GREEN NETWORKING: ENERGY-EFFICIENT PROTOCOLS AND SUSTAINABLE NETWORK DESIGN: A COMPREHENSIVE REVIEWComputer Science and EngineeringPradeep Nayak Download
DIABETIC RETINOPATHY DETECTION USING MACHINE LEARNINGComputer EngineeringSiddharth Shukracharya Rokade Download
PERSONALITY PREDICTION USING MLComputer EngineeringTanvi Dashrath Bhagat Download
Crop Disease Detectioncomputer Mansi Sunil Sansare Download
NEXT-GEN PLANT DISEASE DIAGNOSIS WITH GEN-AI AND DEEP LEARNINGComputer ScienceGuruprasad K Download
GEN-AI POWERED PIGEON PEA LEAF-DISEASE DETECTION USING DEEP-LEARNING AND COMPUTER-VISIONComputer ScienceRajshekar G Download
12