Ahmed H. Madkour

Menoufia University

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i-10 index

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Hatem Abdelkader

Menoufia University

Asmaa H. Elsaid

Menoufia University

Hatem A. Salem

Mansoura University

Manar G. Helal

Mansoura University

Asmaa Ali

Menoufia University

Eman Said

Mansoura University

Amgad M. Mohammed

Menoufia University

Cooperative Institutions

Menoufia University

Mansoura University

Ministry of Health and Population

Zagazig University

Isra University

Rutgers New Jersey Medical School

Rutgers, The State University of New Jersey

Cooper Institute

Cairo University

Benha University

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Dynamic Classification Ensembles for Handling Imbalanced Multiclass Drifted Data Streams

Information Sciences (2024)

Ahmed H. Madkour Hatem Abdelkader Amgad M. Mohammed

Concept Drift

Benchmark (surveying)

Multiclass classification

Oversampling

Ensemble Learning

10.1016/j.ins.2024.120555

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Citations (1)

Lightweight Algorithm for Preventing Intentional Fork in the Bitcoin Environment

Ahmed H. Madkour Asmaa H. Elsaid Hatem Abdelkader

Most Bitcoin systems use blockchain technology to store all historical transaction data. Blockchain is a linked list structure but may be changed to a fork structure; a useful fork or an intentional fork. The useful fork may occur when the rules of the block are updated. On the other side, the intentional fork occurs when a miner has supercomputer properties that generate a set of blocks as a branch and does not publish this branch to the blockchain until the length of that branch is greater than the length of the main branch. When this fork occurs in the system, a set of blockchain transactions will be rollbacked, user waiting times increases, and miner rewards increases illegally. In this paper, the Lightweight algorithm is proposed to avoid the intentional fork issue and therefore rollback issue, users waiting time is reduced in the transaction process. The proposed algorithm is to make a single publisher in the system and divides the block construction into two phases. In the first phase, a miner generates a block and sends it to the memory pool. In the second phase, the memory pool will publish the block to the blockchain. The results show that the proposed algorithm has a good ability to avoid the intentional fork issue in the blockchain and the rollback issue thus minimize user waiting times.

Fork (system call)

Rollback

Publication

10.1109/icces51560.2020.9334563

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Dose-dependent renoprotective impact of Lactoferrin against glycerol-induced rhabdomyolysis and acute kidney injury

Life Sciences (2022)

Ahmed H. Madkour Manar G. Helal Eman Said Hatem A. Salem

Blood urea nitrogen

10.1016/j.lfs.2022.120646

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Citations (12)

Historical Isolated Forest for detecting and adaptation concept drifts in nonstationary data streaming

IJCI International Journal of Computers and Information (2023)

Ahmed H. Madkour

Concept drift refers to sudden changes in the fundamental structure of the streaming data distribution over time. The core objective of concept drift research is to develop techniques and strategies for detect, understand, and adapt data streaming drifts. Data research has shown that if concept drift is not handled properly, machine learning in such an environment would provide subpar learning outcomes. In this paper, a historical Isolated Forest (HIF) is presented that depends on a decision tree, which split the data streaming into chunks and each chuck considers a region in the tree. HIF is employed to detect concept drifts and adapt this region with current changes. Which HIF stores previously generated models and employs the most similar model of each concept drift distribution as the current model until generate the best performance model. HIF doesn't stop the main system model when retraining a new model, which HIF is divided into three primary parallel blocks: detection block, similarity block (online block), and retraining block (offline block). For several authentic data sets (three data sets), our suggested algorithm was verified and contrasted. the accuracy and execution speed were specifically assessed, and memory usage. The experimental results demonstrate that our modifications use fewer resources and have comparable or greater detection accuracy than the original IForestASD.

Concept Drift

Streaming Data

Tree (set theory)

Retraining

10.21608/ijci.2023.185429.1095

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Citations (2)

Memory Pool Publisher Algorithm for Preventing Malicious Fork in the Bitcoin Environment

IJCI International Journal of Computers and Information (2021)

Ahmed H. Madkour Hatem Abdelkader Asmaa Ali

Recently, blockchain is considered the most reliable data storage technology that stores data in blocks.Many cryptocurrency frameworks such as Bitcoin, therefore, utilize blockchain technologies to preserve all past details on blocks.These blocks are related as a chronological link list and can be changed to a fork structure.Which there are two types of fork: accident fork which appears when two blocks are published in the blockchain at the same time.On the other hand, there are selfish miner attackers who have supercomputer properties to generate illegal blocks and maximizing their illicit reward (intentional fork).A set of blockchain transactions will be rollbacked when the malicious fork appears in the Bitcoin environment, therefore, user waiting times and illicit miner rewards will increase.In this paper, The proposed algorithm is a lightweight algorithm (Memory pool publisher) that has used the Bitcoin memory pool as a publisher of blocks to prevent the Bitcoin environment's malicious fork and rollbacked transaction.The findings show that the major cause of the malicious fork is the multiplicity of blockchain publishers of blocks in the bitcoin environment.The proposed algorithm success to solve the limitation of the previous fork.Which has a strong potential to prevent the intentional and accident fork problem, and the rollback problem.Therefore minimize user waiting times from 60 minutes to 10 minutes by makes one block publisher to the blockchain.

Fork (system call)

10.21608/ijci.2021.52568.1035

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Lightweight Algorithm for Preventing Malicious Fork in the Bitcoin Environment

Ahmed H. Madkour Hatem Abdelkader Asmaa H. Elsaid

Blockchain is considered the most secure technology in data storing, which stores data in blocks. Therefore. Blockchain is a linked list structure but may be changed to a fork structure; a usefulfork or a malicious fork. The usefulfork may occur when the rules of the block are updated. On the other side, the malicious fork occurs when a miner has supercomputer properties that generate a set of blocks as a branch and does not publish this branch to the blockchain until the length of that branch is greater than the length of the main branch, or when two blocks saved at the same time in the blockchain. TVhen theseforks occur in the systenb a set of blockchain transactions will be rollbacked, user waiting times increases, and miner rewards increases illegally. In this paper, a Lightweight algorithm is proposed to avoid the malicious fork issue, and therefore rollback issue, users waiting time is reduced in the transaction process. The proposed algorithm is to make a single publisher in the system and divides the block construction into two phases. In the first phase, a miner generates a block and sends it to the memory pool. In the second phase, the memory pool will publish the block to the blockchain. The results show that the proposed algorithm has a good ability to avoid the malicious fork issue in the blockchain and the rollback issue thus minimize user waiting times.

Fork (system call)

Publication

Rollback

Reset (finance)

10.1109/iccta52020.2020.9477688

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Citations (0)