Table 1 Survey of the intrusion detection techniques in MANET.

Cheng et al.²¹

PPVF-RSU-CSP

An initiative is undertaken to integrate cloud storage with VANET, and a PPVF is introduced for cloud-assisted VANET

Prasad et al.²²

Machine learning

In the case of wormhole attack detection in ad hoc networks, the accuracy is 93.12%.

Jhanjhi et al.²³

Machine learning

Making a recommendation for a hybrid RPL protocol that uses machine learning to counter attacks utilizing rank and wormholes

Wang et al.²⁴

FD-WCFRSNPS

According to the results of five different experiments, the FD-WCFRSNPS that was suggested is both efficient and effective.

Singh et al.²⁵

Artificial neural network

Monitoring wireless sensor networks for the presence of wormhole attacks

Srilakshmi et al.²⁶

Hybrid reactive search and bat algorithm

It is necessary to estimate both the harm detection rate and the node energy in order to determine the lifespan of the node

Goyal et al.²⁷

CDMA-based security

Wormhole attack in underwater wireless sensor networks. The proposed strategy enhances energy efficiency in comparison to existing methods

Wang et al.²⁸

Approaches to service selection that is quick and dependable

Our proposed approach has more reliability and reduced time expenditure compared to prior implementations, as indicated by the findings.

Ni et al.²⁹

Fault detection method relies on TDMA

The proposed methodology decreases resource use by 88-90% in comparison to the chain-TDMA strategy.

Amutha et al.³⁰

Clustering techniques

An examination of WSN clustering of three categories: classical, optimization, and machine learning techniques.

Jiang et al.³¹

System for adaptive cosite fading channels

The analytical modeling and experiments validate the theoretical reasoning as both sound and beneficial.

Ahmadi et al.³²

New KATP network for adaptation

The state-of-the-art efficiency of your model has been validated by tests on a variety of typical samples and clinical data.

Tami and Lim et al.³³

Ensemble learning

The success value of classification algorithms is statistically studied using metrics such as accuracy, FPR, Matthews coefficients, and AUC.

Chen et al.³⁴

RPPTD

A secure and private method of discovering the truth

Sultana et al.³⁵

Considering bottleneck intermediate node

The data indicate that the oversight of esteemed packet loss nodes by IDS algorithms constitutes a substantial problem that adversely affects network efficiency.

Sultanuddin et al.³⁶

Decision tree and Reinforcement learning

Proposed model to select a dependable and trustworthy nearby node for data transmission in the MANET.

Majid Hamid Ali et al.³⁷

Improved Whale Optimization Algorithm-SVM

It was capable of identifying multiple forms of cyber-attacks, including Distributed Denial of Service (DDoS) attacks, password guessing attempts and phishing attacks.

Jayakanth et al.³⁸

Equalized Multi-routing protocol

It engages with multipath routing strategies to rectify significant flaws. The author employed a trust table to identify malicious nodes.

Edwin Singh et al.³⁹

Fuzzy Extreme Learning Machine

For all circumstances of the Green Smart Transportation network, the attacks are classified after the PCA features

Mohamad et al.⁴⁰

Deep Learning ANN

The application of ANN techniques in the Internet of Things introduces a detection system for rank and wormhole attacks

Manoj Gupta et al.⁴¹

Machine learning and deep learning model

The author devised an advanced, self-learning protection system proficient in detecting and countering Blackhole Attacks in MANET

Mohammadi et al.⁴²

Federated learning with AI

It enables secure data sharing without accessing local data, which ensures fair benefit redistribution

Hassan et al.⁴³

Advanced Machine learning

Analyzing MANET characteristics and detailing black and gray hole attacks and detection techniques