Neural network approach for intrusion detection

Choudhary, Amit; Swarup, Akhilesh

doi:10.1145/1655925.1656163

Cited by 14 publications

(9 citation statements)

References 4 publications

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“…In ANN, these preparing units/ neurons are to model a human brain neural network such that a robot can remember stuff and make human decisions (Yakura et al, 2018;. Although these neurons can be strongly interlinked in a given topology, ANN has been effectively applied to a wide scope of data demanding appliances (Choudhary & Swarup, 2009).…”

Section: Ann For Data Securitymentioning

confidence: 99%

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Cognitive Intelligence for Interrogation and Inflation of Information Security: A Survey

Jagannathan

Parvees²

2022

JART

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Information security is the set of forms that secure data faraway from illegal connection, revelation, duplication, alteration. As of late, increasingly legitimate frameworks such as resourceful inter and intra urban city, remote sensor systems, authentication digital signature frameworks, and superintendence, have recently needed data security affirmations. Hence, over the past researches numerous diverse strategies focused on cognitive intelligence are created for data security. In any case, there are not complete reviews which recapitulate strategies. In this way, this document surveyed on cognitive intelligence move toward presented on publications and symposiums for data security within most recent years. This article gives a precise review to audit various cognitive intelligence access and applications of data security. In additionally, deliberate the threat of cognitive intelligence access and applications for data security is conferred.

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Section: Ann For Data Securitymentioning

confidence: 99%

“…For a broader spectrum of sectors, this would not have the obvious benefit or versatility of handling scenario-based situations. Development cycles are gradually becoming shorter over time (Choudhary & Swarup, 2009;.…”

Section: Health Carementioning

confidence: 99%

Cognitive Intelligence for Interrogation and Inflation of Information Security: A Survey

Jagannathan

Parvees²

2022

JART

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“…The TMC is 74 058, and the cost per example is 0.2381 when tested on KDDCup'99 dataset. Amit Kumar Choudhary and et al [10] proposed a neural network approach to improve the alert throughput of a network and making it attack prohibitive using IDS. For evolving and testing intrusion the KDD CUP 99 dataset were used.…”

Section: Related Workmentioning

confidence: 99%

Dynamics of Foreign Exchange Rates

Nathani¹,

Kaur²,

Shrivas³

2015

PIJMIT

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With the rapid expansion of computer networks during the past few years, security has become a crucial issue for modern computer systems. A good way to identify malicious use is through monitoring unusual user activity. To identify these malicious activities various data-mining and machine learning techniques have been deployed for intrusion detection. The manual tuning process required by current systems depends on the system operators in working out the tuning solution and in integrating it into the detection model. This paper proposes RULE LEARNING Intrusion Detection System (RLIDS) to make tuning automatically. The key idea is to use the binary SLIPPER as a basic module, which is a rule learner based on confidence-rated boosting. This system is evaluated using the NSL KDD intrusion detection dataset. An experimental result shows the RLIDS system with SLIPPER algorithm gives better performance in terms of detection rate, false alarm rate, total misclassification cost and cost per example on NSL-KDD dataset than that of on KDD.

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“…In this paper they set to examine the differences between the intrusion detection domain and other areas where machine learning is used with more success [5]. They have discussed the threat model and address the questions to include: What kind of environment does the system target?…”

Section: Neural Network Approach For Intrusion Detection [5]mentioning

confidence: 99%

Integrating Machine Learning Techniques to Constitute a Hybrid Security System

Singh

Chandra

2014

2014 Fourth International Conference on Communication Systems and Network Technologies

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Computer Security has been discussed and improvised in many forms and using different techniques as well as technologies. The enhancements keep on adding as the security remains the fastest updating unit in a computer system. In this paper we propose a model for securing the system along with the network and enhance it more by applying machine learning techniques SVM (support vector machine) and ANN (Artificial Neural Network). Both the techniques are used together to generate results which are appropriate for analysis purpose and thus, prove to be the milestone for security.

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Neural network approach for intrusion detection

Cited by 14 publications

References 4 publications

Cognitive Intelligence for Interrogation and Inflation of Information Security: A Survey

Cognitive Intelligence for Interrogation and Inflation of Information Security: A Survey

Dynamics of Foreign Exchange Rates

Integrating Machine Learning Techniques to Constitute a Hybrid Security System

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