Optimized Deep Neuro Fuzzy Network for Cyber Forensic Investigation in Big Data-Based IoT Infrastructures

Optimized Deep Neuro Fuzzy Network for Cyber Forensic Investigation in Big Data-Based IoT Infrastructures

Suman Thapaliya, Pawan Kumar Sharma
Copyright: © 2023 |Pages: 22
DOI: 10.4018/IJISP.315819
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Abstract

Forensic skills analysts play an imperative support to practice streaming data generated from the IoT networks. However, these sources pose size limitations that create traffic and increase big data assessment. The obtainable solutions have utilized cybercrime detection techniques based on regular pattern deviation. Here, a generalized model is devised considering the MapReduce as a backbone for detecting the cybercrime. The objective of this model is to present an automatic model, which using the misbehavior in IoT device can be manifested, and as a result the attacks exploiting the susceptibility can be exposed by newly devised automatic model. The simulation of IoT is done such that energy constraints are considered as basic part. The routing is done with fractional gravitational search algorithm to transmit the information amongst the nodes. Apart from this, the MapReduce is adapted for cybercrime detection and is done at base station (BS) considering deep neuro fuzzy network (DNFN) for identifying the malwares.
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1. Introduction

The IoT devices link the static or mobile devices and objects using the sensors and actuator and offers smooth communication through network. IoT provides the widespread utilization of several modern technologies and models using the transmission control protocol (TCP) /internet protocol, which emerges in the model of interconnecting devices considering the physical platform. The main aspect adapted in routing considering IoT is efficiency of energy, safe communication, and scalability. The routing and data transmission using sophisticated services provides a key problem in IoT. The online business and Mobile commerce are emerging IoT application. The security considering IoT includes in-depth assessment as a basic need to preserve the network and is essential task. The genuine susceptibility in the IoT platform is insecure web interface, mobile interface and deficiency of security configurability. The aspects to avert cyber-attacks are devised by specified authors (Chhabra et al., 2020). A major IoT model accumulates large quantity of data known as big data and it transmits to layer that performs processing. The big data are devised with three features, such as volume, variety and velocity (Srinivasan et al., 2012). The big data is growing each year and thus the rebellion in the technology and scientific face influenced the size of data to maximize the lucrative tasks (Triguero et al., 2016 ; Venugopal et al., 2021). The database of big data is complex to accumulate, split, sort, envisage and examine the contemporary techniques (Terzi et al., 2015 ; Suthaharan, 2014 ; Venugopal et al., 2021).

Classically, the majority of data contained in big data represents streaming data, because of the connections, capacity, and events of the data modeling, which progress through the internet. The data are produced considering the time instance (Zhang et al., 2012 ; Venugopal et al., 2021). Cybercrime represents a crime through computer in which the computers are utilized for prohibited tasks, such as child pornography, theft, fraudulent behavior, intellectual possessions. The Cybercrime is progressively growing in internet technologies because of the computer operations, like commerce, entertainment and government. The server can conceal its data by foraging sender address, which are transmitted through unidentified server or channel. The detection of cybercrime is a basic domain in the retrieval of information, processing language and machine learning (Venugopal et al., 2021). Cybercrime is digital crime caused by considering network as weapon. The multiple cybercrime domains are extended from uncomplicated credential risks to geopolitical crime in recent days (Guarino, 2013). The report of crime survey reveals that 49% of global CEOs pose issues over the emerging network and figures out way to avert its institutions from risks (Meidan et al., 2017). The cybercrime requires coherent and logically effective technique for managing the crime space (Fahdi et al., 2013). Here, the cyber-attacks on IoT devices tend to be emerging. Some of the IoT attacks pose a hit in IoT platform in several years due to attacks, like Mirai botnet and Brickerbot (Chhabra et al., 2020).

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