Artificial Intelligence of Things : First International Conference, ICAIoT 2023, Chandigarh, India, March 30–31, 2023, Revised Selected Papers, Part I / edited by Rama Krishna Challa, Gagangeet Singh Aujla, Lini Mathew, Amod Kumar, Mala Kalra, S. L. Shimi, Garima Saini, Kanika Sharma.

Format:

Book

Contributor:

Challa, Rama Krishna, editor.

Series:

Communications in Computer and Information Science, 1865-0937 ; 1929

Language:

English

Subjects (All):

Artificial intelligence.

Database management.

Machine learning.

Application software.

Software engineering.

Artificial Intelligence.

Database Management System.

Machine Learning.

Computer and Information Systems Applications.

Software Engineering.

Local Subjects:

Artificial Intelligence.

Database Management System.

Machine Learning.

Computer and Information Systems Applications.

Software Engineering.

Physical Description:

1 online resource (402 pages)

Edition:

1st ed. 2024.

Place of Publication:

Cham : Springer Nature Switzerland : Imprint: Springer, 2024.

Summary:

These two volumes constitute the revised selected papers of First International Conference, ICAIoT 2023, held in Chandigarh, India, during March 30–31, 2023. The 47 full papers and the 10 short papers included in this volume were carefully reviewed and selected from 401 submissions. The two books focus on research issues, opportunities and challenges of AI and IoT applications. They present the most recent innovations, trends, and concerns as well as practical challenges encountered and solutions adopted in the fields of AI algorithms implementation in IoT Systems.

Contents:

Intro

AI and IoT Enabling Technologies

Securing IoT Using Supervised Machine Learning

1 Introduction

2 IoT and Machine Learning

2.1 Supervised Machine Learning

2.2 Unsupervised Machine Learning

2.3 Deep Learning

2.4 Reinforcement Learning

3 Methods

3.1 UNSW-NB15 Dataset

3.2 Experimental Setup

3.3 Performance Measures

4 Results and Inferences

4.1 Using Hyperparameter Tuned Models

4.2 Using Feature Selection on Parameter-Tuned Models

4.3 Using Class Weights on Parameter-Tuned Models

4.4 Using Class Weights with Important Features on Parameter-Tuned Models

5 Observations

6 Conclusion

References

DDoS Attack Detection in IoT Environment Using Crystal Optimized Deep Neural Network

2 Literature Survey

3 System Model

3.1 Performance Improvement by Feature Extraction

3.2 Traffic Analyzer Module Based DDoS Detection

3.3 Crystal Optimized Deep Neural Network

4 Experimental Results and Analysis

4.1 Dataset Description

4.2 Performance Metrics

4.3 Experimental Results

4.4 Throughput

4.5 Average Throughput

4.6 Energy Consumption

4.7 Memory Utilization

5 Conclusion

Prediction Based Load Balancing in Cloud Computing Using Conservative Q-Learning Algorithm

1.1 Characteristics of Cloud Computing

1.2 Cloud Service Models

1.3 Load Balancing

1.4 Classification of Load Balancing Techniques

1.5 Load Balancing Metrics

1.6 Motivation

1.7 Problem Statement

1.8 Research Objectives

2 Literature Review

3 Methodology

4 Experiment Results

An Attribute Selection Using Propagation-Based Neural Networks with an Improved Cuckoo-Search Algorithm

1.1 Corpus-Based Approach

1.2 Machine Learning Utilization and Swarm Intelligence Approach.

2 Related Work

4 Results

Payable Outsourced Decryption for Functional Encryption Using BlockChain

1.1 Challenges and Contribution

1.2 Related Works

2 Preliminaries

2.1 Blockchain and Smart Contracts

2.2 Functional Encryption with Outsourced Decryption

3 Security and Framework Definitions

3.1 Overview

3.2 Adversarial Model

4 Description of Protocol

4.1 Generic Construction

4.2 Instantiation

4.3 Integrating Into a Blockchain

5 Performance Analysis and Evaluation

5.1 Performance Analysis

5.2 Experiment Results

Multi-environment Audio Dataset Using RPi-Based Sound Logger

2 Review of Similar Public and Private Databases

3 Experimental System for Sound Recording

3.1 Hardware Description

3.2 Software Description

3.3 Data Collection Algorithm

4 Audio Specifications

5 Database Description

6 Application Test Cases

7 Conclusion

A Comparative Analysis of Android Malware Detection Using Deep Learning

3 Proposed Methodology

3.1 Dataset

3.2 Data Preprocessing

3.3 Feature Selection

4 Proposed Framework

5 Experimental Setup

6 Result and Discussion

6.1 Analysis Using Static Features

6.2 Analysis Using Dynamic Features

6.3 Analysis Using a Combination of Static and Dynamic Features

7 Comparison Analysis

8 Conclusion

Optimization of Virtual Machines in Cloud Environment

1.1 Load Rebalancing

3.1 Proposed Queuing Model

3.2 Proposed Placement Algorithm

4 Results and Discussions

References.

A Construction of Secure and Efficient Authenticated Key Exchange Protocol for Deploying Internet of Drones in Smart City

2 Related Works

3 Motivation and Contribution

4 Threat Model

5 Physical Unclonable Functions

6 Network Model

7 Proposed Secure and Efficient Authenticated Key Exchange Protocol for Deploying Internet of Drones in Smart City

7.1 Initialization

7.2 Drone Registration

7.3 Mobile User Registration

7.4 Authentication and Key Agreement Process

8 Security Analysis

8.1 Impersonation Attacks

8.2 Replay Attack

8.3 Physical Capture Attack on Drones

8.4 Disclosed Session Key Attack

8.5 Offline Password Guessing Attack

8.6 Man-in-the-middle Attack

8.7 Ephemeral Secret Leakage Attack

8.8 Anonymity

8.9 Mutual Authentication

9 Performance Analysis

9.1 Computation Time

9.2 Communication Cost

10 Conclusion

Comparative Analysis of Quantum Key Distribution Protocols: Security, Efficiency, and Practicality

2 Comparative Analysis

3 Research Challenges and Issues

4 Conclusion

Fog Intelligence for Energy Optimized Computation in Industry 4.0

2 Why DRL is Important in IIoT Offloading?

2.1 Related Work

2.2 Contribution

3 Network Model

4 Proposed DRL for Task Offloading

5 Experimental Analysis

5.1 Simulation Setup

5.2 Delay Analysis

5.3 Energy Analysis

5.4 Performance Analysis of DRL

Security Enhancement of Content in Fog Environment

2 Cloud Computing

3 Challenges of Cloud Computing

3.1 Fog Computing

3.2 Benefits of Fog Computing

3.3 Disadvantages of Fog Computing

3.4 Cloud vs Fog and Edge Computing

4 Literature Review

5 Problem Statement

6 Proposed Model

6.1 At Sending End.

6.2 At the Receiver End

7 Result and Discussion

7.1 Implementation of Fog

9 Future Scope

Local Database Connectivity and UI Design for the Smart Automated Cooker

2.1 PyQt5

2.2 MySqL Database

3 GUI Design and Database Connectivity

3.1 UI Designing

4 Results and Discussion

5 Challenges

6 Future Scope

A Detection Approach for IoT Traffic-Based DDoS Attacks

1.1 IoT Platform

1.2 DDoS Attack

1.3 Recent Statistical Information of DDoS Attacks

1.4 Contributions

1.5 Structure of the Article

2 Related Work

3.1 Training Process

4 Experimental Environment

5 Results and Analysis

6 Conclusions

Comparison between Performance of Constraint Solver for Prediction Model in Symbolic Execution

2 Symbolic Execution Environment

2.1 Symbolic Execution (SE)

2.2 Constraint Solver

3 Limitation of Symbolic Execution

3.1 Path Explosion

3.2 Search Heuristics

3.3 Pruning Redundant Paths

3.4 Lazy Test Generation

3.5 Constraint Solving

3.6 Redundant Constraint Elimination

3.7 Prioritization of Constraint Set

4.1 By Automatically Learning Search Heuristics

4.2 Improving Symbolic Execution through solver Selection Based on Machine Learning [12]

4.3 SMT Time Prediction Model [15]

5 Proposed Approach

5.1 Methodology

5.2 Framework

5.3 Experimental Setup

6 Result and Analysis

6.1 Comparison by F1 Score

6.2 Comparison by Timeout Query

6.3 Comparison by Original Solving Time

7 Conclusion and Future work

Cost-Deadline Constrained Robust Scheduling of Workflows Using Hybrid Instances in IaaS Cloud

2 Related Work.

3 Application and Resource Model

4 Proposed Work

5 Performance Evaluation

5.1 Analysis Based on Cost

5.2 Analysis Based on Makespan

5.3 Analysis Based on Fault Tolerance

6 Conclusion and Future Scope

AI and IoT for Smart Healthcare

Comparative Performance Analysis of Machine Learning Algorithms for COVID-19 Cases in India

3 Dataset and Methodology

3.2 Model Configuration

3.3 Methodology

4 Results and Observations

5 Conclusion and Future Scope

Performance Analysis of Different Machine Learning Classifiers for Prediction of Lung Cancer

3 Proposed Approach

3.2 Modules

3.3 Algorithm

3.4 Ensemble Learning Prediction

4 Experimental Learning

4.1 Data Preprocessing

4.2 Data Mining

5 Results and Discussion

5.1 Logistic Regression

5.2 KNN

5.3 SVM

5.4 Kernel-SVM

5.5 Naïve Bayes

5.6 Decision Tree

5.7 Random Forest

5.8 Ensemble Learning Model

Localization Improvements in Faster Residual Convolutional Neural Network Model for Temporomandibular Joint - Osteoarthritis Detection

3.1 Progressive Localized-Improved FRCNN Model

4 Experimental Results

Semi-Automated Diabetes Prediction Using AutoGluon and TabPFN Models

2 Methodology

2.1 Data Collection

2.2 Prediction

3 Testbed and Analysis

3.1 Experimental Testbed

3.2 Analysis

Malnutrition Detection Analysis and Nutritional Treatment Using Ensemble Learning

3 Existing System

4 Methodology/Proposed System

4.1 Collection and Classes of Datasets.

4.2 Implementation of the Model.

Notes:

Includes bibliographical references and index.

Other Format:

Print version: Challa, Rama Krishna Artificial Intelligence of Things

ISBN:

3-031-48774-5