期刊,Ad-hoc & sensor wireless networks 2025年60卷1/2期_国家学术搜索

期刊信息/Journal information

Ad-hoc & sensor wireless networks

Old City Publishing, Inc.

主办单位：Old City Publishing, Inc.

出版周期：季刊

国际刊号：1551-9899

Ad-hoc & sensor wireless networks/Journal Ad-hoc & sensor wireless networks

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60 卷1/2 期

Investigative Analysis of Vulnerabilities and Attacks on Underwater Wireless Sensor Networks

Jibran R. KhanShariq M. KhanFarhan A. Siddiqui

1-18页

查看更多>>摘要：Underwater wireless sensor networks (UWSNs) have gained global attention in recent years due to their numerous applications and the vast amount of the world's surface area covered by water. However, the security of UWSNs is a critical concern in order to protect the advantages of this technology and its various applications. This paper presents an investigative study and simulations using ns-3 and aquasim-ng to identify the factors that challenge the security of UWSNs and their applications. The study explores the UWSN architecture, vulnerabilities, and potential attacks, as well as various scenarios including normal, limited, and special conditions. The results of the study and simulations are analyzed to determine the factors that contribute to the security challenges faced by UWSNs. Finally, the paper concludes with a discussion of the factors or components that can assist in overcoming these security challenges and the need to address and consider them in future work. This research aims to provide a deeper understanding of the security issues facing UWSNs and to identify potential solutions for addressing these challenges. Finally, the research concludes with recommendations for addressing and overcoming the challenges to UWSN security in the future.

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Attack Detection on Internet of Things via Deep Ensemble Classifier Model with Proposed Feature Set

Rekha HSiddappa M

19-55页

查看更多>>摘要：Due to the large-scale application & difficulties, IoT is now a prominent subject of research. Initially, detecting the attacks and the malicious traffic is a major problem because of traffic network size. However, with the continuous expansion of its size & applicability, security is a major problem. Individual installment of security measures for each IoT device during new threats arising is indeed a time-consuming task. Yet, existing security measures only address the restricted attacks, as evaluations were limited to outdated datasets. This paper offers a novel attack detection model for IoT that will be implemented in the given stages: "(1) preprocessing, (2) feature extraction, & (3) classification". The challenge of minority class is initially addressed by defining a new logic during the pre - processing stage. Here, a feature extraction stage is applied on the image input (preprocessed data) to extract statistical (Mean, Median, Mode, SD), higher cognitive statistical features (Angular moment, Skewness, Homogeneity, Percentile, Kurtosis), enhanced Correntropy, and better correlations texture methods. The categorization processes are then applied to these characteristics using deep ensemble classifiers including Convolutional Neural Network 1 (CNN 1), Convolutional Neural Network 2(CNN 2), and QNN (Quantum Neural Network). The results of the classifiers (CNN1, CNN2, and QNN) is progressed with enhanced score level integration is used to calculate the outcomes. The proposed ECISF scheme for learning percentage 90 has, respectively, greater specificity of 58.33%, 27.08%, 33.33%, 14.58%, 72.91%, 35.41%, 89.58%, and 68.78% to current schemes like ESFCM, IoT-IDCS-CNN, Bi-GRU,LSTM,SVM, DBN, RNN, and RF.

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Range-Based Localization in Underwater Wireless Sensor Networks Using the Optimization Algorithm

Nishi YadavVishnu Prasad Yadav

57-95页

查看更多>>摘要：Underwater wireless sensor networks (UWSNs) are made up of several underwater wireless sensor nodes that are scattered throughout the marine environment and can be utilized for resource discovery, navigation, surveillance, data collecting, and disaster prediction. Energy efficiency becomes a significant issue in the UWSN's design due to the use of limited battery capacity and the difficulties of changing or charging the inbuilt batteries. To overcome the energy efficiency problem in routing, a hybrid approach is developed in this study for UWSNs. Initially, a Range-based Localization technique was used to locate sensor nodes, which used the received signal intensity and arrival time to provide reliable node range estimation. Accordingly, this work presents a Recursive Position Estimation (RPE) technique, which determines the sensor location for a given number of available anchor references. A path must be built between a sensor (or source) and the desired destination (or surface sink) for effective and reliable data transmission. Between the sensor nodes, a multi-hop communication channel is conceivable. The intermediate nodes deliver the packet data until it reaches the sink node in multi-hopping. To route packet data towards the destination, an Artificial Bee Colony (ABC) integrated Chaotic Particle-swarm Krill Herd (ABC-CPKH) technique is used, as the main contribution deals with the choice of cluster head. Due to the harsh underwater environment, its capabilities, and the open acoustic channel is vulnerable to threats and malicious attacks. The research suggested a Delphi detection system to reduce the threat problem in UWSN, which prevents undesired packets from being deliv-ered to the destination, mainly, it prevents the data from the wormhole attack. PDR, end-to-end delay, energy consumption, network lifetime, localization energy, localization coverage, detection rate, etc., are performance metrics for the proposed study, which is simulated using Python software. The proposed method is compared to the existing IRL-WOA, EECRP, and DSIP methods, Compared to these methods, the proposed method provided 6%, 3.5% and 4% better performance for time complexity, energy consumption and delay. Consequently, future research can suggest new metaheuristic algorithms to more efficiently allocate resources and increase localization accuracy, respectively.

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An Energy-Efficient and Balanced Method for Centralized Clustering Routing Protocol in Wireless Sensor Networks

Hamid Karimi

97-116页

查看更多>>摘要：To address the challenges of uneven energy usage and limited network lifespan in wireless sensor networks (WSNs), centralized hierarchical routing protocols are commonly utilized. One of the main focuses in WSNs is clustering and selecting cluster heads. This paper proposes an energy efficient clustering routing algorithm, improved by the sine cosine algorithm (ECRA). The algorithm first determines the optimal number of cluster heads per round based on the surviving nodes, and creates a candidate cluster head set by selecting high-energy nodes. A random population is then constructed to represent a group of cluster head selection schemes, with a fitness function designed based on inter-cluster distance. The ECRA algorithm is improved using a monotone decreasing convex function, and a certain number of iterations are carried out to select a group of individuals with the minimum fitness function value. Simulation experiments show that the improved algorithm can extend the network's effective life by balancing energy consumption among nodes and avoiding premature death of some nodes. It greatly improves energy utilization and network lifespan and reduces the overall network energy consumption better than the previous method.

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An Efficient and Secure Information Dissemination Framework for Vehicular Ad Hoc Networks with Edge Intelligence

Ying HeYuan LiGuang ZhouZhong Ming...

117-140页

查看更多>>摘要：Vehicular ad hoc networks (VANETs) have attracted great interest from both academia and industry. Information dissemination among vehicles is an important application in VANETs with edge intelligence. Defining "appropriate vehicle" and protecting vehicle privacy in information dissemination is challenging. In this paper, we present an efficient and secure information dissemination framework built on a new ciphertext-policy attribute-based encryption (CP-ABE) scheme. The distinct features of this novel framework are as follows. First, the number of pairing operations used by the decryption algorithm in our framework is independent of the number of input attributes. Therefore, our framework can greatly reduce the computational burden. Second, the group used in our paper is generated based on a novel curve, which can bring higher security to VANETs. Third, we use a short-signature technology to reduce the computation overhead of the key generation process in the vehicle rental scenario. Performance evaluation shows the effectiveness of the proposed framework.

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Old City Publishing Inc

Safe Reinforcement Learning for Pedestrian Collision Avoidance in Connected and Autonomous Vehicles

Ying HeGuangyuan ZouGuang ZhouWeike Pan...

141-169页

查看更多>>摘要：Pedestrian collision avoidance is one of the most fundamental problems in autonomous driving. Reinforcement learning (RL) provides a promising solution to solve this problem by learning to adapt to pedestrian behaviors. However, it is difficult to directly apply traditional RL methods due to the weak safety in training and deployment. To address this issue, we propose three safe RL methods: 1) RL with safe reward, 2) RL with constraints, 3) RL with limited exploration. Our results show that the proposed three safe RL methods make a better trade-off between the driving efficiency and the unsafety caused by unexpected pedestrian behaviors. These three safe RL methods are applicable of avoiding pedestrian collision in different environments. If the safe reward can be well designed, standard RL method can have good performance. If the safety reward is not well designed, RL with constraints should be the optimal choice. If the safety guarantee is strictly required for the RL training process, RL with limited exploration should be considered. In addition, we present several useful observations about parameter settings in safe RL methods.

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NETL
NSTL
Old City Publishing Inc