scholarly journals A SYSTEMATIC REVIEW METHOD FOR SECURITY ANALYSIS OF INTERNET OF THINGS ON HONEYPOT DETECTION

TEKNOKOM ◽  
2021 ◽  
Vol 4 (1) ◽  
pp. 16-20
Author(s):  
Andrie Yuswanto ◽  
Budi Wibowo
Keyword(s):  
Machine Learning ◽  
Systematic Review ◽  
Internet Of Things ◽  
Security Analysis ◽  
The Internet ◽  
Malware Analysis ◽  
Learning Approaches ◽  
Exclusion Criteria ◽  
Recent Approach ◽  
The Internet Of Things

A very significant increase in the spread of malware has resulted in malware analysis. A recent approach to using the internet of things has been put forward by many researchers. Iot tool learning approaches as a more effective and efficient approach to dealing with malware compared to conventional approaches. At the same time, the researchers transformed the honeypot as a device capable of gathering malware information. The honeypot is designed as a malware trap and is stored on the provided system. Then log the managed events and gather information about the activity and identity of the attacker. This paper aims to use a honeypot in machine learning to deal with malware The Systematic Literature Review (SLR) method was used to identify 207. Then 10 papers were selected to be investigated based on inclusion and exclusion criteria. . The technique used by most researchers is to utilize the available honeypot dataset. Meanwhile, based on the type of malware being analyzed, honeypot in machine learning is mostly used to collect IoT-based malware.

Advanced Deep Learning Applications in Big Data Analytics

2021 ◽  
pp. 1-28
Author(s):  
Venkatesan Manian ◽  
Vadivel P.
Keyword(s):  
Machine Learning ◽  
Big Data ◽  
Deep Learning ◽  
Internet Of Things ◽  
Data Analytics ◽  
Big Data Analytics ◽  
The Internet ◽  
Infrastructure Development ◽  
Learning Approaches ◽  
The Internet Of Things

This chapter analyzes the Internet of Things (IoT), its history, and its tools in brief. This chapter also explores the contribution of IoT towards the recent development in infrastructure development of nations represented as smart world. This chapter also discuss the contribution of IoT towards big data analytics era. This chapter also briefly introduce the smart bio world and how it is made possible with the internet of things. This chapter also introduces the machine learning approaches and also discusses the contribution of Internet of Thing for this machine learning. This chapter also briefly introduces some tools used for IoT developments.

Detecting Abnormal Behavior of an IoT Device in the Network Based on a Traffic Model

Telecom IT ◽  
2019 ◽  
Vol 7 (3) ◽  
pp. 50-55
Author(s):  
D. Saharov ◽  
D. Kozlov
Keyword(s):  
Machine Learning ◽  
Internet Of Things ◽  
Mobile Networks ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Abnormal Behavior ◽  
Traffic Model ◽  
The Internet ◽  
Wide Spread ◽  
The Internet Of Things

The article deals with the СoAP Protocol that regulates the transmission and reception of information traf-fic by terminal devices in IoT networks. The article describes a model for detecting abnormal traffic in 5G/IoT networks using machine learning algorithms, as well as the main methods for solving this prob-lem. The relevance of the article is due to the wide spread of the Internet of things and the upcoming update of mobile networks to the 5g generation.

scholarly journals IMPROVING INTERNET OF THINGS PARKING SYSTEMS

2021 ◽  
Vol 19 (3) ◽  
pp. 163
Author(s):  
Dušan Bogićević
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Cloud Computing ◽  
Internet Of Things ◽  
Information Needs ◽  
Vehicle Classification ◽  
The Internet ◽  
Parking Space ◽  
Automated Systems ◽  
The Internet Of Things

Edge data processing represents the new evolution of the Internet and Cloud computing. Its application to the Internet of Things (IoT) is a step towards faster processing of information from sensors for better performance. In automated systems, we have a large number of sensors, whose information needs to be processed in the shortest possible time and acted upon. The paper describes the possibility of applying Artificial Intelligence on Edge devices using the example of finding a parking space for a vehicle, and directing it based on the segment the vehicle belongs to. Algorithm of Machine Learning is used for vehicle classification, which is based on vehicle dimensions.

Encryption Principles and Techniques for the Internet of Things

2019 ◽  
pp. 42-66
Author(s):  
Kundankumar Rameshwar Saraf ◽  
Malathi P. Jesudason
Keyword(s):  
Internet Of Things ◽  
Embedded System ◽  
Security Analysis ◽  
Block Size ◽  
The Internet ◽  
Lightweight Cryptography ◽  
Execution Speed ◽  
Security Algorithm ◽  
Iot Devices ◽  
The Internet Of Things

This chapter explores the encryption techniques used for the internet of things (IoT). The security algorithm used for IoT should follow many constraints of an embedded system. Hence, lightweight cryptography is an optimum security solution for IoT devices. This chapter mainly describes the need for security in IoT, the concept of lightweight cryptography, and various cryptographic algorithms along with their shortcomings given IoT. This chapter also describes the principle of operation of all the above algorithms along with their security analysis. Moreover, based on the algorithm size (i.e., the required number of gate equivalent, block size, key size, throughput, and execution speed of the algorithm), the chapter reports the comparative analysis of their performance. The chapter discusses the merits and demerits of these algorithms along with their use in the IoT system.

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