Relevant bibliographies by topics / Black-hole attack Tree

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Black-hole attack Tree'

Author: Grafiati
Published: 6 September 2023
Last updated: 31 July 2025

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Journal articles on the topic "Black-hole attack Tree"

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Moudni, Houda, Mohamed Er-rouidi, Mansour Lmkaiti, and Hicham Mouncif. "Customized dataset-based machine learning approach for black hole attack detection in mobile ad hoc networks." International Journal of Electrical and Computer Engineering (IJECE) 15, no. 2 (2025): 2138. https://doi.org/10.11591/ijece.v15i2.pp2138-2149.

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This article explores the application of machine learning (ML) algorithms to classify the black hole attack in mobile ad hoc networks (MANETs). Black hole attacks threaten MANETs by disrupting communication and data transmission. The primary goal of this study is to develop an intrusion detection system (IDS) to detect and classify this attack. The research process involves feature selection, the creation of a custom dataset tailored to the characteristics of black hole attacks, and the evaluation of four machine learning models: random forest (RF), logistic regression (LR), k-nearest neighbor
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Moudni, Houda, Mohamed Er-Rouidi, Mansour Lmkaiti, and Hicham Mouncif. "Customized dataset-based machine learning approach for black hole attack detection in mobile ad hoc networks." International Journal of Electrical and Computer Engineering (IJECE) 15, no. 2 (2025): 2138–49. https://doi.org/10.11591/ijece.v15i2.pp2138-2149.

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This article explores the application of machine learning (ML) algorithms to classify the black hole attack in mobile ad hoc networks (MANETs). Black hole attacks threaten MANETs by disrupting communication and data transmission. The primary goal of this study is to develop an intrusion detection system (IDS) to detect and classify this attack. The research process involves feature selection, the creation of a custom dataset tailored to the characteristics of black hole attacks, and the evaluation of four machine learning models: random forest (RF), logistic regression (LR), k-nearest neighbor
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Yassein, Muneer, Yaser Khamayseh, and Mai Abujazoh. "Feature Selection for Black Hole Attacks." JUCS - Journal of Universal Computer Science 22, no. (4) (2016): 521–36. https://doi.org/10.3217/jucs-022-04-0521.

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The security issue is essential and more challenging in Mobile Ad-Hoc Network (MANET) due to its characteristics such as, node mobility, self-organizing capability and dynamic topology. MANET is vulnerable to different types of attacks. One of possible attacks is black hole attack. Black hole attack occurs when a malicious node joins the network with the aim of intercepting data packets which are exchanged across the network and dropping them which affects the performance of the network and its connectivity. This paper proposes a new dataset (BDD dataset) for black hole intrusion detection sys
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Al Madani, Anhar, Saima Anwar Lashari, Sana Salah Uddin, Abdullah Khan, Muhammad Nouman Atta Muhammad Attaullah, and Dzati Athiar Ramli. "Detecting Black Hole Attack using Support Vector Machine with XGBoosting in Mobile Ad-Hoc Networks." Journal of Informatics and Web Engineering 4, no. 2 (2025): 209–24. https://doi.org/10.33093/jiwe.2025.4.2.13.

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Mobile Ad-Hoc Networks (MANET) is a type of ad-hoc networks which use less infrastructure, that means the nodes in this network forward the massages without the need of infrastructure such as routers, switches etc. One of the most used attacks that can affect MANET performance is the black hole attack. This attack leads to dropping the packets that means these packets will never arrive and it will decrease the delivery ratio for the packets. This attack is a real problem as the sender is not informed that the data has not reached the intended receiver. The main goal of this study is to propose
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Rahul Nawkhare, Daljeet Singh, Swati Giadhane, and Saurabh Chakole. "Smart Detection of Routing Attacks in Wireless Sensor Networks Using Ml: Focus On Black Hole Threats." International Research Journal on Advanced Engineering and Management (IRJAEM) 3, no. 05 (2025): 1605–10. https://doi.org/10.47392/irjaem.2025.0259.

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As wireless communication networks continue to expand, the need for protection against attacks on the routing of these networks, especially Blackhole attack, has increasingly been recognized as one of the most critical needs of the era. This research involves detecting and classifying Blackhole attacks in wireless sensor networks using different machine learning algorithms. The labeled dataset was then built using normal and Blackhole traffic, and a comparative analysis of four classification models was made: Decision Tree, Random Forest, Logistic Regression and K-Nearest Neighbors. The propos
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Boland, John M., and Deborah L. Woodward. "Thick bark can protect trees from a severe ambrosia beetle attack." PeerJ 9 (February 16, 2021): e10755. http://dx.doi.org/10.7717/peerj.10755.

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Thick bark has been shown to protect trees from wildfires, but can it protect trees from an ambrosia beetle attack? We addressed this question by examining the distribution of holes of the invasive Kuroshio Shot Hole Borer (KSHB, Euwallacea kuroshio; Coleoptera: Scolytinae) in the bark of Goodding’s black willow (Salix gooddingii), one of the KSHB’s most-preferred hosts. The study was conducted in the Tijuana River Valley, California, in 2016–17, during the peak of the KSHB infestation there. Using detailed measurements of bark samples cut from 27 infested trees, we tested and found support fo
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Eskalen, Akif, Richard Stouthamer, Shannon Colleen Lynch, et al. "Host Range of Fusarium Dieback and Its Ambrosia Beetle (Coleoptera: Scolytinae) Vector in Southern California." Plant Disease 97, no. 7 (2013): 938–51. http://dx.doi.org/10.1094/pdis-11-12-1026-re.

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The polyphagous shot hole borer (PSHB) is an invasive ambrosia beetle that forms a symbiosis with a new, as-yet-undescribed Fusarium sp., together causing Fusarium dieback on avocado and other host plants in California and Israel. In California, PSHB was first reported on black locust in 2003 but there were no records of fungal damage until 2012, when a Fusarium sp. was recovered from the tissues of several backyard avocado trees infested with PSHB in Los Angeles County. The aim of this study was to determine the plant host range of the beetle–fungus complex in two heavily infested botanical g
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Lakshmi Narayanan, K., and R. Naresh. "Detection and Prevention of Black Hole Attack using Tree Hierarchical Deep Convolutional Neural Network and Enhanced Identity-based Encryption in Vehicular Ad Hoc Network." IEIE Transactions on Smart Processing & Computing 13, no. 1 (2024): 41–50. http://dx.doi.org/10.5573/ieiespc.2024.13.1.41.

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Rani, Pooja, Kavita, Sahil Verma, et al. "Robust and Secure Data Transmission Using Artificial Intelligence Techniques in Ad-Hoc Networks." Sensors 22, no. 1 (2021): 251. http://dx.doi.org/10.3390/s22010251.

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The paper presents a new security aspect for a Mobile Ad-Hoc Network (MANET)-based IoT model using the concept of artificial intelligence. The Black Hole Attack (BHA) is considered one of the most affecting threats in the MANET in which the attacker node drops the entire data traffic and hence degrades the network performance. Therefore, it necessitates the designing of an algorithm that can protect the network from the BHA node. This article introduces Ad-hoc On-Demand Distance Vector (AODV), a new updated routing protocol that combines the advantages of the Artificial Bee Colony (ABC), Artif
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Luo, Ke. "A distributed SDN-based intrusion detection system for IoT using optimized forests." PLOS ONE 18, no. 8 (2023): e0290694. http://dx.doi.org/10.1371/journal.pone.0290694.

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Along with the expansion of Internet of Things (IoT), the importance of security and intrusion detection in this network also increases, and the need for new and architecture-specific intrusion detection systems (IDS) is felt. In this article, a distributed intrusion detection system based on a software defined networking (SDN) is presented. In this method, the network structure is divided into a set of sub-networks using the SDN architecture, and intrusion detection is performed in each sub-network using a controller node. In order to detect intrusion in each sub-network, a decision tree opti
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Dissertations / Theses on the topic "Black-hole attack Tree"

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Sai, Keerthi T. Divya. "Designing Solutions to Counter the Attacks in Mobile Ad hoc Networks." Thesis, 2018. https://etd.iisc.ac.in/handle/2005/5315.

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The open medium, dynamic topology and distributed operation in Mobile Ad hoc Networks (MANET) leads to high risks. Many solutions are proposed to protect a MANET from attacks, ranging from attack identification to prevention. Although these solutions reduce and avoid the attacks in a MANET, sometimes they identify many false attacks as real ones which may cause huge loss of resources. For example, a sudden route breakdown can cause delay in packet delivery; differentiating such a delay from the delay caused by an attacker is difficult. Further, an intelligent attacker could also cause fa
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Book chapters on the topic "Black-hole attack Tree"

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Rahman, F., and Priti Sharma. "Designing an Intrusion Detection System to Identify Black Hole Attacks in Wireless Ad-hoc Networks using Support Vector Machines, with a comparison to Decision Trees." In Recent Developments in Microbiology, Biotechnology and Pharmaceutical Sciences. CRC Press, 2025. https://doi.org/10.1201/9781003618140-52.

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Conference papers on the topic "Black-hole attack Tree"

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Korsapati, Amulya, and T. J. Nagalakshmi. "Design of intrusion detection system to detect black hole attack using principal component analysis in wireless ad-hoc network comparing with decision tree classifier." In THE 12TH ANNUAL INTERNATIONAL CONFERENCE (AIC) 2022: The 12th Annual International Conference on Sciences and Engineering (AIC-SE) 2022. AIP Publishing, 2024. http://dx.doi.org/10.1063/5.0186368.

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Korsapati, Amulya, and T. J. Nagalakshmi. "Design of intrusion detection system to detect black hole attack using random forest technique in wireless ad hoc network comparing with decision tree algorithm." In THE 12TH ANNUAL INTERNATIONAL CONFERENCE (AIC) 2022: The 12th Annual International Conference on Sciences and Engineering (AIC-SE) 2022. AIP Publishing, 2024. http://dx.doi.org/10.1063/5.0186398.

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Korsapati, Amulya, and T. J. Nagalakshmi. "Design of intrusion detection system to detect black hole attack using k-means cluster in a wireless ad-hoc network and comparing with decision tree algorithm." In THE 12TH ANNUAL INTERNATIONAL CONFERENCE (AIC) 2022: The 12th Annual International Conference on Sciences and Engineering (AIC-SE) 2022. AIP Publishing, 2024. http://dx.doi.org/10.1063/5.0186399.

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Wahane, Gayatri, Ashok M. Kanthe, and Dina Simunic. "Technique for detection of cooperative black hole attack using true-link in Mobile Ad-hoc Networks." In 2014 37th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO). IEEE, 2014. http://dx.doi.org/10.1109/mipro.2014.6859791.

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Journal articles
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