Intrusion Detection System Techniques A Review

Omar Fitian Rashid; Noor Thamer Mahmood; Zahraa A. H. Alobaidy

Details

Publication Date

Fri Sep 23 2022

Journal Name

Specialusis Ugdymas

Volume

1

Issue Number

43

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Intrusion Detection System Techniques A Review

Anomaly

Artificial neural networks

Bio-inspired computing

Intrusion detection

Misuse

Omar Fitian Rashid

Noor Thamer Mahmood

Zahraa A. H. Alobaidy

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With the high usage of computers and networks in the current time, the amount of security threats is increased. The study of intrusion detection systems (IDS) has received much attention throughout the computer science field. The main objective of this study is to examine the existing literature on various approaches for Intrusion Detection. This paper presents an overview of different intrusion detection systems and a detailed analysis of multiple techniques for these systems, including their advantages and disadvantages. These techniques include artificial neural networks, bio-inspired computing, evolutionary techniques, machine learning, and pattern recognition.

Publication Date

Sat Apr 01 2023

Journal Name

Baghdad Science Journal

Some K-Banhatti Polynomials of First Dominating David Derived Networks

Dominating David Derived networks

F-K Banhatti indices

harmonic K Banhatti indices

K-Banhatti polynomial

K-hyper Banhatti indices

symmetric division K Banhatti indices

Anjaneyulu

Vijaya Chandra Kumar

R.

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Chemical compounds, characteristics, and molecular structures are inevitably connected. Topological indices are numerical values connected with chemical molecular graphs that contribute to understanding a chemical compounds physical qualities, chemical reactivity, and biological activity. In this study, we have obtained some topological properties of the first dominating David derived (DDD) networks and computed several K-Banhatti polynomials of the first type of DDD.

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(1)

Publication Date

Thu Jun 01 2023

Journal Name

Baghdad Science Journal

Topological Indices Polynomials of Domination David Derived Networks

Dominating David Derived networks

F-K Banhatti indices

harmonic K Banhatti indices

K-Banhatti polynomial

K-hyper Banhatti indices

symmetric division K Banhatti indices

Anjaneyulu

Vijaya Chandra Kumar

R.

...Show More Authors

The chemical properties of chemical compounds and their molecular structures are intimately connected. Topological indices are numerical values associated with chemical molecular graphs that help in understanding the physicochemical properties, chemical reactivity and biological activity of a chemical compound. This study obtains some topological properties of second and third dominating David derived (DDD) networks and computes several K Banhatti polynomial of second and third type of DDD.

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(2)

(1)

Publication Date

Thu Mar 18 2010

Journal Name

Spe Projects, Facilities & Construction

Correlating Optimum Stage Pressure for Sequential Separator Systems

separation and treating

PVT measurement

optimization problem

Upstream Oil & Gas

Phase Behavior

objective function

optimum stage pressure

GOR

Artificial Intelligence

Mohammed S.

Omar

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Summary<p>A study to find the optimum separators pressures of separation stations has been performed. Stage separation of oil and gas is accomplished with a series of separators operating at sequentially reduced pressures. Liquid is discharged from a higher-pressure separator into the lower-pressure separator. The set of working separator pressures that yields maximum recovery of liquid hydrocarbon from the well fluid is the optimum set of pressures, which is the target of this work.</p><p>A computer model is used to find the optimum separator pressures. The model employs the Peng-Robinson equation of state (Peng and Robinson 1976) for volatile oil. The application of t</p> ... Show More

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(14)

Publication Date

Thu May 25 2023

Journal Name

Polycyclic Aromatic Compounds

Effect of Modified Nano-Graphene Oxide and Silicon Carbide Nanoparticles on the Mechanical Properties and Durability of Artificial Stone Composites from Waste

Artificial stone composite (ASC)

cement

physiochemical parameters

silicon carbide nanoparticles (SiC-NPs) and nano-graphene oxide (NGO)

sludge stone-cutting (SSC)

Reza

Ameer

Ghufran

Haider

Diyar

Abduladheem Turki

Raed H. C.

Yasser

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Sludge from stone-cutting (SSC) factories and stone mines cannot be used as decorative stones, stone powder, etc. These substances are left in the environment and cause environmental problems. This study aim is to produce artificial stone composite (ASC) using sludge from stone cutting factories, cement, unsaturated resin, water, silicon carbide nanoparticles (SiC-NPs), and nano-graphene oxide (NGO) as fillers. Nano graphene oxide has a hydrophobic plate structure that water is not absorbed due to the lack of surface tension on these plates. NGO has a significant effect on the properties of artificial stone due to its high specific surface area and low density in the composite. Its uniform distribution in ASC is very low due to its hydropho

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(4)

(3)

Publication Date

Fri Jan 01 2016

Journal Name

Journal Of Engineering

Mobile position estimation using artificial neural network in CDMA cellular systems

feed forward neural network

time of arrival

received signal strength

back propagation

optimal positioning method

and average positioning method

Sally

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Using the Neural network as a type of associative memory will be introduced in this paper through the problem of mobile position estimation where mobile estimate its location depending on the signal strength reach to it from several around base stations where the neural network can be implemented inside the mobile. Traditional methods of time of arrival (TOA) and received signal strength (RSS) are used and compared with two analytical methods, optimal positioning method and average positioning method. The data that are used for training are ideal since they can be obtained based on geometry of CDMA cell topology. The test of the two methods TOA and RSS take many cases through a nonlinear path that MS can move through that region. The result

Publication Date

Fri Jan 01 2016

Journal Name

Journal Of Engineering

Mobile Position Estimation using Artificial Neural Network in CDMA Cellular Systems

feed forward neural network

time of arrival

received signal strength

back propagation

optimal positioning method

and average positioning method.

Omar Waleed

Sally Antoin

...Show More Authors

Using the Neural network as a type of associative memory will be introduced in this paper through the problem of mobile position estimation where mobile estimate its location depending on the signal strength reach to it from several around base stations where the neural network can be implemented inside the mobile. Traditional methods of time of arrival (TOA) and received signal strength (RSS) are used and compared with two analytical methods, optimal positioning method and average positioning method. The data that are used for training are ideal since they can be obtained based on geometry of CDMA cell topology. The test of the two methods TOA and RSS take many cases through a nonlinear path that MS can move through tha

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Publication Date

Sun Jan 10 2016

Journal Name

British Journal Of Applied Science & Technology

The Effect of Classification Methods on Facial Emotion Recognition ‎Accuracy

Facial emotions

feature selection

data clustering

modified K-Means clustering algorithm

LDA algorithm

Statistical classifier

Neural Network

Support Vector Machine (SVM)

Suhaila N.

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The interests toward developing accurate automatic face emotion recognition methodologies are growing vastly, and it is still one of an ever growing research field in the region of computer vision, artificial intelligent and automation. However, there is a challenge to build an automated system which equals human ability to recognize facial emotion because of the lack of an effective facial feature descriptor and the difficulty of choosing proper classification method. In this paper, a geometric based feature vector has been proposed. For the classification purpose, three different types of classification methods are tested: statistical, artificial neural network (NN) and Support Vector Machine (SVM). A modified K-Means clustering algorithm

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Publication Date

Sat May 31 2025

Journal Name

3rd International Scientific Conference For Human And Social Studies And Epistemological Challenges

Frankenstein Complex in Daniel H. Wilson's Robopocalypse ( ): Artificial Intelligence Conspiracies

With the advent of technology

the fear of losing control has consistently accompanied humanity. While humans have discovered

invented

and created many remarkable things

they have also been haunted by the possibility of their creations turning against them. This fear

often referred to as the Frankenstein Complex

derives its name from Mary Shelley's Frankenstein (􀀔􀀛􀀔􀀛)

in which Dr. Frankenstein's creation ultimately destroys its maker. The Frankenstein Complex embodies the subconscious fear of artificial intelligence (AI) surpassing and potentially dominating humankind. This apprehension has inspired numerous literary works

including Daniel H. Wilson’s novels. The present study examines the widespread fear of AI

which has fueled conspiracy theories in literature. These theories have not only amplified public anxiety but also hindered understanding among those with limited knowledge of AI and robotics. Dr. Wilson

a robotics expert

uses his imagination as a driving force for both his writing and his inventions. The research focuses on incidents leading to the rise of robots

the concept of the New War

how it was fought

and how it concluded. By comparing

contrasting

and analyzing literary elements and devices with prominent conspiracy theories

the study highlights the interplay between fiction and scientific development. The researchers conclude that while many conspiracy theories contain elements of truth

they often inspire scientists to explore them further. Additionally

some conspiracy theories warrant serious consideration. The study recommends acknowledging the Frankenstein Complex while maintaining faith in the potential benefits of artificial intelligence.

Ansam

Mayada

Zahraa

...Show More Authors

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