scholarly journals A comparative analysis of metaheuristic algorithms in fuzzy modelling for phishing attack detection

Author(s):  
Noor Syahirah Nordin ◽  
Mohd Arfian Ismail ◽  
Tole Sutikno ◽  
Shahreen Kasim ◽  
Rohayanti Hassan ◽  
...  

<div>Phishing attack is a well-known cyber security attack that happens to many people around the world. The increasing and never-ending case of phishing attack has led to more automated approaches in detecting phishing attack. One of the methods is applying fuzzy system. Fuzzy system is a rule-based system that utilize fuzzy sets and fuzzy logic concept to solve problems. However, it is hard to achieve optimal solution when applied to complex problem where the process of identify the fuzzy parameter becomes more complicated. To cater this issue, an optimization method is needed to identify the parameter of fuzzy automatically. The optimization method derives from the metaheuristic algorithm. Therefore, the aim of this study is to make a comparative analysis between the metaheuristic algorithms in fuzzy modelling. The study was conducted to analyse which algorithm performed better when applied in two datasets: website phishing dataset (WPD) and phishing websites dataset (PWD). Then the results were obtained to show the performance of every metaheuristic algorithm in terms of convergence speed and four metrics including accuracy, recall, precision, and f-measure. </div>

Jurnal METRIS ◽  
2020 ◽  
Vol 21 (02) ◽  
pp. 111-115
Author(s):  
Agung Chandra ◽  
Aulia Naro

Metaheuristic algorithm is a state of the art optimization method which suitable for solving large and complex problem. Single solution technique – Smetaheuristic is one of metaheuristic algorithm that search near optimal solution and known as exploitation based. The research conducted to seek a better solution for deliverying goods to 29 destinations by comparing two well known optimization methods that can produce the shortest distance: Simulated Annealing (SA) and Tabu Search (TS). The result shows that TS – 107 KM has a shorter distance than SA – 119 KM. Exploration based method should be conducted for next research to produce information in which one is a better method


2018 ◽  
Vol 7 (3) ◽  
pp. 1804
Author(s):  
M Goudhaman

In recent years, appreciable attention among analysts to take care of the extraordinary enhancement issues utilizing metaheuristic algorithms in the domain area of Swarm Intelligence. Many metaheuristic algorithms have been developed by inspiring various nature phenomena’s. Exploration and exploitation are distinctive capacities and confine each other, along these lines, customary calculations require numerous parameters and bunches of expenses to accomplish the adjust, and furthermore need to modify parameters for various enhancement issues. In this paper, another populace based algorithm, the Cheetah Chase Algorithm (CCA), is presented. Distinctive features of Cheetah and their characteristics has been the essential motivation for advancement of this optimization algorithm. Cheetah Chase Algorithm (CCA) has awesome capacities both in exploitation and exploration, is proposed to address these issues. To start with, CCA endeavours to locate the optimal solution in the assigned hunt territory. It at that point utilizes history data to pursue its prey. CCA can, hence, decide the situation of the worldwide ideal. CCA accomplishes solid exploitation and exploration with these highlights. Additionally, as indicated by various issues, CCA executes versatile parameter change. The self-examination and analysis of this exploration show that each CCA capacity can have different beneficial outcomes, while the execution correlation exhibits CCAs predominance over conventional metaheuristic algorithms. The proposed Cheetah Chase Algorithm is developed by the process of hunting and chasing of Cheetah to capture its prey with the parameters of high speed, velocity and greater accelerations.  


2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Wencheng Yin ◽  
Yunhe Cui ◽  
Qing Qian ◽  
Guowei Shen ◽  
Chun Guo ◽  
...  

Software-defined networking for IoT (SDN-IoT) has become popular owing to its utility in smart applications. However, IoT devices are limited in computing resources, which makes them vulnerable to Low-rate Distributed Denial of Service (LDDoS). It is worth noting that LDDoS attacks are extremely stealthy and can evade the monitoring of traditional detection methods. Therefore, how to choose the optimal features to improve the detection performance of LDDoS attack detection methods is a key problem. In this paper, we propose DIAMOND, a structured coevolution feature optimization method for LDDoS detection in SDN-IoT. DIAMOND is consisted of a reachable count sorting clustering algorithm, a group structuring method, a comutation strategy, and a cocrossover strategy. By analysing the information of SDN-IoT network features in the solution space, the relationship between different SDN-IoT network features and the optimal solution is explored in DIAMOND. Then, the individuals with associated SDN-IoT network features are divided into different subpopulations, and a structural tree is generated. Further, multiple structural trees evolve in concert with each other. The evaluation results show that DIAMOND can effectively select optimal low-dimension feature sets and improve the performance of the LDDoS detection method, in terms of detection precision and response time.


2018 ◽  
pp. 48-52
Author(s):  
S. V. Popov ◽  
G. N. Devyatkov

When designing radioelectronic devices, that are included in the composition of various systems, it is important to solve broadband matching problem and filtering problem. However, usually these problems are separated and not considered together. Moreover, the synthesis of filters does not take into account the behavior of impedances of the generator and the load in the stopbands. The solution of the complex problem is actual, since it allows expanding the functionality of the device, which can greatly simplify the construction of the radio engineering product. It should be noted that in the known literature solution of this problem in such a formulation is not considered. The aim of the work is to develop a synthesis method and algorithm of broadband devices that connect arbitrary immitances of the generator and the load, and these devices should perform simultaneously functions of both matching and filtering in reactive lumped electric element base and in distributed electric element base, limited only by transmission lines with T-waves. In this paper, a two-stage automated method of synthesis presented here stage allows at the first to adequately find a good initial solution to the posed problem (determining structure and parameters of the broadband matching and filtering quadrupole), in the second stage this approach allows to find the optimal solution to the complex problem, taking into account the constraints on physical and circuit realizability. In this work, the synthesis of broadband matching and filtering devices in lumped and distributed electrical element basis is carried out, and these devices connect complex impedances of the source and the load. The characteristics of the devices obtained after the synthesis show that the solution of the complex problem of matching and filtering gives a significant improvement in filtering properties with small losses in the level of transmitted power.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
H. Hassani ◽  
J. A. Tenreiro Machado ◽  
Z. Avazzadeh ◽  
E. Safari ◽  
S. Mehrabi

AbstractIn this article, a fractional order breast cancer competition model (F-BCCM) under the Caputo fractional derivative is analyzed. A new set of basis functions, namely the generalized shifted Legendre polynomials, is proposed to deal with the solutions of F-BCCM. The F-BCCM describes the dynamics involving a variety of cancer factors, such as the stem, tumor and healthy cells, as well as the effects of excess estrogen and the body’s natural immune response on the cell populations. After combining the operational matrices with the Lagrange multipliers technique we obtain an optimization method for solving the F-BCCM whose convergence is investigated. Several examples show that a few number of basis functions lead to the satisfactory results. In fact, numerical experiments not only confirm the accuracy but also the practicability and computational efficiency of the devised technique.


Energies ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2963
Author(s):  
Melinda Timea Fülöp ◽  
Miklós Gubán ◽  
György Kovács ◽  
Mihály Avornicului

Due to globalization and increased market competition, forwarding companies must focus on the optimization of their international transport activities and on cost reduction. The minimization of the amount and cost of fuel results in increased competition and profitability of the companies as well as the reduction of environmental damage. Nowadays, these aspects are particularly important. This research aims to develop a new optimization method for road freight transport costs in order to reduce the fuel costs and determine optimal fueling stations and to calculate the optimal quantity of fuel to refill. The mathematical method developed in this research has two phases. In the first phase the optimal, most cost-effective fuel station is determined based on the potential fuel stations. The specific fuel prices differ per fuel station, and the stations are located at different distances from the main transport way. The method developed in this study supports drivers’ decision-making regarding whether to refuel at a farther but cheaper fuel station or at a nearer but more expensive fuel station based on the more economical choice. Thereafter, it is necessary to determine the optimal fuel volume, i.e., the exact volume required including a safe amount to cover stochastic incidents (e.g., road closures). This aspect of the optimization method supports drivers’ optimal decision-making regarding optimal fuel stations and how much fuel to obtain in order to reduce the fuel cost. Therefore, the application of this new method instead of the recently applied ad-hoc individual decision-making of the drivers results in significant fuel cost savings. A case study confirmed the efficiency of the proposed method.


Author(s):  
Patrick Nwafor ◽  
Kelani Bello

A Well placement is a well-known technique in the oil and gas industry for production optimization and are generally classified into local and global methods. The use of simulation software often deployed under the direct optimization technique called global method. The production optimization of L-X field which is at primary recovery stage having five producing wells was the focus of this work. The attempt was to optimize L-X field using a well placement technique.The local methods are generally very efficient and require only a few forward simulations but can get stuck in a local optimal solution. The global methods avoid this problem but require many forward simulations. With the availability of simulator software, such problem can be reduced thus using the direct optimization method. After optimization an increase in recovery factor of over 20% was achieved. The results provided an improvement when compared with other existing methods from the literatures.


2013 ◽  
Vol 21 (5) ◽  
pp. 1679-1693 ◽  
Author(s):  
Saurabh Amin ◽  
Xavier Litrico ◽  
S. Shankar Sastry ◽  
Alexandre M. Bayen

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