Advanced search ?

Object

Download

Title: Markov Decision Process based Model for Performance Analysis an Intrusion Detection System in IoT Networks, Journal of Telecommunications and Information Technology, 2021, nr 3

Creator:

Kalnoor, Gauri ; S, Gowrishankar

Date:

2021, nr 3

Resource Type:

artykuł

Description:

In this paper, a new reinforcement learning intrusion detection system is developed for IoT networks incorporated with WSNs. A research is carried out and the proposed model RL-IDS plot is shown, where the detection rate is improved. The outcome shows a decrease in false alarm rates and is compared with the current methodologies. Computational analysis is performed, and then the results are compared with the current methodologies, i.e. distributed denial of service (DDoS) attack. The performance of the network is estimated based on security and other metrics

Publisher:

Instytut Łączności - Państwowy Instytut Badawczy

Format:

application/pdf

Resource Identifier:

ISSN 1509-4553, on-line: ISSN 1899-8852 ; oai:bc.itl.waw.pl:2195

Source:

Journal of Telecommunications and Information Technology

Language:

ang

Rights Management:

Biblioteka Naukowa Instytutu Łączności

Subject and keywords:

machine learning intrusion detection IoT DDoS Q-learning reinforcement-learning NSL-KDD Markov decision process (MDP)

Object collections:

Last modified:

Oct 11, 2021

In our library since:

Oct 11, 2021

Number of object content hits:

58

All available object's versions:

https://ribes-54.man.poznan.pl/publication/2497

Show description in RDF format:

RDF

Show description in OAI-PMH format:

OAI-PMH

Edition name Date
Kalnoor, Gauri; S, Gowrishankar, Markov Decision Process based Model for Performance Analysis an Intrusion Detection System in IoT Networks, Journal of Telecommunications and Information Technology, 2021, nr 3 Oct 11, 2021

Objects Similar
Battery Drain Denial-of-Service Attacks and Defenses in the Internet of Things, Journal of Telecommunications and Information Technology, 2019, nr 2

Logothetis, Michael D. Vassilakis, Vassilios G. Ioulianou, Philokypros P.

2019, nr 2
artykuł
2024, nr 3, JTIT-artykuły
2024, nr 3, JTIT-artykuły
A Collaborative Approach to Detecting DDoS Attacks in SDN Using Entropy and Deep Learning, Journal of Telecommunications and Information Technology, 2024, nr 3

Narayan, D. G. Heena, W Amit, K

2024, nr 3
artykuł
2023, nr 3, JTIT-artykuły
2023, nr 3, JTIT-artykuły
A Cross-layer Method for Scheduling and Routing Real-time Traffic Flow in Industrial IoT. Journal of Telecommunications and Information Technology, 2023, nr 3

Azimian, Nikta Mohammadi, Reza Nassiri, Mohammad

2023, nr 3
artykuł
2024, nr 4, JTIT-artykuły
2024, nr 4, JTIT-artykuły
Examination of 5G NR, LTE, and NB-IoT Radio Interfaces and Their Vulnerabilities to Interference, Journal of Telecommunications and Information Technology, 2024, nr 4

Rajchowski, Piotr

2024
artykuł
Comparative Analysis of QoS Management and Technical Requirements in 3GPP Standards for Cellular IoT Technologies, Journal of Telecommunications and Information Technology, 2018, nr 2

Bochechka, Grigory Tikhvinskiy, Valery Gryazev, Andrey Aitmagambetov, Altay

2018, nr 2
artykuł
LEES: a Hybrid Lightweight Elliptic ElGamal-Schnorr-Based Cryptography for Secure D2D Communications, Journal of Telecommunications and Information Technology, 2021, nr 2

Prabhakar, M. Ara, Tabassum Ambareen, Javeria

2021, nr 2
artykuł
Multifactor Authentication and Key Management Protocol for WSN-assisted IoT Communication, Journal of Telecommunications and Information Technology, 2019, nr 3

Prabhakar, M. Ara, Tabassum

2019, nr 3
artykuł
Detection of DDoS Attacks in OpenStack-based Private Cloud Using Apache Spark, Journal of Telecommunications and Information Technology, 2020, nr 4

Shinde, Sumedha Gumaste, Shweta K, Amit G., Narayan D.

2020, nr 4
artykuł
More
×

Citation

Citation style:

Contact details

Address

Instytut Łączności – Państwowy Instytut Badawczy ul. Szachowa 1 04-894 Warszawa

Phone

(+48) 5128 696

E-Mail

biblioteka@il-pib.pl

Visit us!

This page uses 'cookies'. More information