Performance analysis of Snort-based Intrusion Detection System

Garg, Anshul; Maheshwari, Prachi

doi:10.1109/icaccs.2016.7586351

Cited by 31 publications

(15 citation statements)

References 10 publications

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“…Discussion Snort types of attacks often occur as part of a system intrusion that can be in the form of scanning Nmap ports, LOIC, SQL Injection, and database access [18]. Some technical aspects must be elaborated such as: How the system handles a variety of effective security that is faced with a high rate of growth in the volume of data, and how aspects of information security will be addressed [19]. Rule Snort is a Snort rule that contains databases with attack patterns.…”

Section: Resultsmentioning

confidence: 99%

Analysis of Snort Rules to Prevent Synflood Attacks on Network Security

Karmadenur¹,

Yusuf²

2019

IJCA

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Snort rules are a form of the database whose attack pattern is applied to a Snort server to filter out the types of attacks, so that the type of attack detected can be isolated, the Snort rule database must be updated so that if there are new types of attack patterns it can be found by Snort rules. This analysis will provide input to update regularly so that if a new type of attack is detected and can be detected. Snort rules to prevent SYN Flood attacks, the type of denial of service that has been formulated using loopholes when connecting to TCP / IP is done. In network security analysis it is very important to formulate an attack pattern that will attack the network so that it can be overcome by Snort rules. Maintaining a secure network from interference can be overcome by Snort rules. Analysis of Snort's rules is to prevent SYN Flood attacks on network security and makes it easier for administrators to report the types of attacks that enter Snort rules and make it easier to make policies improve based on the logs in Snort rules.

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Section: Resultsmentioning

confidence: 99%

Analysis of Snort Rules to Prevent Synflood Attacks on Network Security

Karmadenur¹,

Yusuf²

2019

IJCA

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“…The rule-based detection basically identifies known type of attacks. The most commercially used IDS is Snort [8] which detects an attack based on content matching the rules from the file that contains characteristics of each type of an attack. The main drawback for this method is that it cannot identify new types of attacks.…”

Section: Related Workmentioning

confidence: 99%

NAttack! Adversarial Attacks to bypass a GAN based classifier trained to detect Network intrusion

Piplai

Chukkapalli

Joshi

2020

2020 IEEE 6th Intl Conference on Big Data Security on Cloud (BigDataSecurity), IEEE Intl Conference on High Performance and Sma

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“…The rule can then filter the acquired data. The performance analysis is the topic of [9], where it is stated that Snort works correctly if updated regularly, otherwise it will not be able to detect the newest types of attacks and threats. The operation of Snort can be enhanced for example by using dynamic fuzzy rule interpolation, which enhances Snort to current network conditions dynamically [10].…”

Section: Selected Intrusion Prevention Systemsmentioning

confidence: 99%

Experimental load test statistics for the selected IPS tools on low-performance IoT devices

Zitta

Lucki

Vojtěch

et al. 2019

Journal of Electrical Engineering

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The goal of this paper is to propose a testing procedure for selected intrusion prevention systems (IPS) in a realistic network traffic in terms of their suitability on a given hardware microcomputers for low-performance devices for internet of things (IoT). We perform an IPS research in terms of resource usage in order to establish a universal procedure of checking, whether a given microcomputer controlling IoT devices (often in overloaded state) can additionally burden the installation and start-up of IPS. The experiment is repeated on several boards under overload condition to determine the maximum data rate, above which transmission degrades. The presented testing method is an exemplary tool for IoT applications concerning the security of embedded devices with low performance.

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Performance analysis of Snort-based Intrusion Detection System

Cited by 31 publications

References 10 publications

Analysis of Snort Rules to Prevent Synflood Attacks on Network Security

Analysis of Snort Rules to Prevent Synflood Attacks on Network Security

NAttack! Adversarial Attacks to bypass a GAN based classifier trained to detect Network intrusion

Experimental load test statistics for the selected IPS tools on low-performance IoT devices

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