Detection and Mitigation of IoT-Based Attacks Using SNMP and Moving Target Defense Techniques

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27230%2F23%3A10251938" target="_blank" >RIV/61989100:27230/23:10251938 - isvavai.cz</a>

Result on the web

<a href="https://www.mdpi.com/1424-8220/23/3/1708" target="_blank" >https://www.mdpi.com/1424-8220/23/3/1708</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/s23031708" target="_blank" >10.3390/s23031708</a>

Result language

angličtina

Original language name

Detection and Mitigation of IoT-Based Attacks Using SNMP and Moving Target Defense Techniques

Original language description

This paper proposes a solution for ensuring the security of IoT devices in the cloud environment by protecting against distributed denial-of-service (DDoS) and false data injection attacks. The proposed solution is based on the integration of simple network management protocol (SNMP), Kullback-Leibler distance (KLD), access control rules (ACL), and moving target defense (MTD) techniques. The SNMP and KLD techniques are used to detect DDoS and false data sharing attacks, while the ACL and MTD techniques are applied to mitigate these attacks by hardening the target and reducing the attack surface. The effectiveness of the proposed framework is validated through experimental simulations on the Amazon Web Service (AWS) platform, which shows a significant reduction in attack probabilities and delays. The integration of IoT and cloud technologies is a powerful combination that can deliver customized and critical solutions to major business vendors. However, ensuring the confidentiality and security of data among IoT devices, storage, and access to the cloud is crucial to maintaining trust among internet users. This paper demonstrates the importance of implementing robust security measures to protect IoT devices in the cloud environment and highlights the potential of the proposed solution in protecting against DDoS and false data injection attacks.

Czech name

—

Czech description

—

Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

20301 - Mechanical engineering

Project

—

Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Sensors

ISSN

1424-3210

e-ISSN

1424-8220

Volume of the periodical

23

Issue of the periodical within the volume

3

Country of publishing house

CH - SWITZERLAND

Number of pages

13

Pages from-to

—

UT code for WoS article

000930934900001

EID of the result in the Scopus database

—