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Network Log-Based SSH...(Computers,Materials & Continua, 2021.03)

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논문명

Network Log-Based SSH Brute-Force Attack Detection Model


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Abstract

The rapid advancement of IT technology has enabled the quick

discovery, sharing and collection of quality information,but has also increased

cyberattacks at a fast pace at the same time. There exists no means to block

these cyberattacks completely, and all security policies need to consider the

possibility of external attacks. Therefore, it is crucial to reduce external attacks

through preventative measures. In general, since routers located in the upper

part of a firewall can hardly be protected by security systems, they are exposed

to numerous unblocked cyberattacks. Routers block unnecessary services and

accept necessary ones while taking appropriatemeasures to reduce vulnerability,

block unauthorized access, and generate relevant logs. Most logs created

through unauthorized access are caused by SSH brute-force attacks, and

therefore IP data of the attack can be collected through the logs. This paper

proposes a model to detect SSH brute-force attacks through their logs, collect

their IP address, and control access from that IP address. In this paper, we

present a model that extracts and fragments the specific data required from

the packets of collected routers in order to detect indiscriminate SSH input

attacks. To do so, the model multiplies a user’s access records in each packet

by weights and adds them to the blacklist according to a final calculated result

value. In addition, the model can specify the internal IP of an attack attempt

and defend against the first 29 destination IP addresses attempting the attack.


논문 정보 

Jeonghoon Park1, Jinsu Kim1, B. B. Gupta2 and Namje Park1,*

1Department of Convergence Information Security, Graduate School, Jeju National University, Jeju, 63243, Korea

2Department of Computer Engineering, National Institute of Technology Kurukshetra, Kurukshetra, 136119, India

*Corresponding Author: Namje Park. Email: namjepark@jejunu.ac.kr


Computers,Materials & Continua Tech Science Press

DOI:10.32604/cmc.2021.015172

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