IoT Technology Module - 4

Krishna Gudi Asst. Prof, CSE Dept

Overview

Data Analytics for IoT

Machine Learning

Big Data Analytics Tools and Technology

Edge Streaming Analytics

Network Analytics

Introduction

Structured Vs Unstructured Data

IoT Data Analytics

IoT Data Analytics Challenges

Scaling problems : Continually send data, relational databases can grow incredibly large very quickly.

Volatility of data: With relational databases, it is critical that the schema be designed correctly from the beginning.

• Due to the lack of flexibility, revisions to the schema must be kept at a minimum.

Machine Learning Overview

Supervised Learning

Unsupervised Learning

Neural Network

Q

Big Data Tools and Technology

Velocity - how quickly data is being collected and analyzed.

Variety - different types of data

Volume - scale of the data

Massively Parallel Processing

Document stores

Key-value stores

Wide-column stores

Graph stores

NoSQL Databases

Hadoop

Cont..

Cont..

Edge Analytics Core Functions

Securing IoT

OT Security

Cybersecurity incidents in industrial environments can result in physical consequences that can cause threats to human lives.

Operational interruptions have occurred in OT environments due to cybersecurity incidents.

Attackers were skilled individuals with deep knowledge of technology and the systems they were attacking.

Challenges in OT Security

Erosion of Network Architecture

Pervasive Legacy Systems

Insecure Operational Protocols

Common Industrial Protocols - Modbus

- DNP3 (Distributed Network Protocol)

- ICCP (Inter-Control Center Communications Protocol)

- OPC (OLE for Process Control)

IT and OT Security Practices

Formal Risk Analysis Structures

Cont..

FAIR Risk Model