The International Journal of Network Security & Its Applications (IJNSA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the computer Network Security & its applications. The journal focuses on all technical and practical aspects of security and its applications for wired and wireless networks. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern security threats and countermeasures, and establishing new collaborations in these areas.

1. Top 10 Cited
Network Security
Research Articles
2021 - 2022
International Journal of Network
Security & Its Applications (IJNSA)
ERA, WJCI Indexed
ISSN: 0974 - 9330 (Online); 0975 - 2307 (Print)
https://airccse.org/journal/ijnsa.html
Citations, h-index, i10-index
Citations 9398 h-index 45 i10-index 182

2. 1. PERFORMANCE EVALUATION OF MACHINE LEARNING TECHNIQUES FOR
DOS DETECTION IN WIRELESS SENSOR NETWORK
Lama Alsulaiman and Saad Al-Ahmadi, King Saud University, Saudi Arabia
https://aircconline.com/ijnsa/V13N2/13221ijnsa02.pdf
March 2021 | Cited by 18
ABSTRACT
The nature of Wireless Sensor Networks (WSN) and the widespread of using WSN introduce
many security threats and attacks. An effective Intrusion Detection System (IDS) should be used
to detect attacks. Detecting such an attack is challenging, especially the detection of Denial of
Service (DoS) attacks. Machine learning classification techniques have been used as an approach
for DoS detection. This paper conducted an experiment using Waikato Environment for
Knowledge Analysis (WEKA) to evaluate the efficiency of five machine learning algorithms for
detecting flooding, grayhole, blackhole, and scheduling at DoS attacks in WSNs. The evaluation
is based on a dataset, called WSN-DS. The results showed that the random forest classifier
outperforms the other classifiers with an accuracy of 99.72%.
KEYWORDS
Wireless Sensor Networks, Machine Learning, Denial of Service

3. 2. ANALYSIS OF MACHINE LEARNING ALGORITHMS WITH FEATURE
SELECTION FOR INTRUSION DETECTION USING UNSW-NB15 DATASET
Geeta Kocher1
and Gulshan Kumar2
, 1
MRSPTU, India, 2
SBSSTC, India
https://aircconline.com/ijnsa/V13N1/13121ijnsa02.pdf
January 2021 | Cited by 17
ABSTRACT
In recent times, various machine learning classifiers are used to improve network intrusion
detection. The researchers have proposed many solutions for intrusion detection in the literature.
The machine learning classifiers are trained on older datasets for intrusion detection, which
limits their detection accuracy. So, there is a need to train the machine learning classifiers on the
latest dataset. In this paper, UNSW-NB15, the latest dataset is used to train machine learning
classifiers. The selected classifiers such as K-Nearest Neighbors (KNN), Stochastic Gradient
Descent (SGD), Random Forest (RF), Logistic Regression (LR), and Naïve Bayes (NB)
classifiers are used for training from the taxonomy of classifiers based on lazy and eager
learners. In this paper, Chi-Square, a filter-based feature selection technique, is applied to the
UNSW-NB15 dataset to reduce the irrelevant and redundant features. The performance of
classifiers is measured in terms of Accuracy, Mean Squared Error (MSE), Precision, Recall, F1-
Score, True Positive Rate (TPR) and False Positive Rate (FPR) with or without feature selection
technique and comparative analysis of these machine learning classifiers is carried out.
KEYWORDS
Intrusion Detection System, MSE, SGD, UNSW-NB15, Machine Learning Algorithms

4. 3. DESIGNING A CYBER-SECURITY CULTURE ASSESSMENT SURVEY
TARGETING CRITICAL INFRASTRUCTURES DURING COVID-19 CRISIS
Anna Georgiadou, Spiros Mouzakitis and Dimitris Askounis, National Technical University of
Athens, Greece
https://aircconline.com/ijnsa/V13N1/13121ijnsa03.pdf
January 2021 | Cited by 11
ABSTRACT
The paper at hand presents the design of a survey aiming at the cyber-security culture assessment
of critical infrastructures during the COVID-19 crisis, when living reality was heavily disturbed
and working conditions fundamentally affected. The survey is rooted in a security culture
framework layered into two levels, organizational and individual, further analyzed into 10
different security dimensions consisted of 52 domains. An in-depth questionnaire building
analysis is presented focusing on the aims, goals, and expected results. It concludes with the
survey implementation approach while underlining the framework’s first application and its
revealing insights during a global crisis.
KEYWORDS
Cybersecurity Culture, Assessment Survey, COVID-19 Pandemic, Critical Infrastructures

5. 4. PROOF-OF-REPUTATION: AN ALTERNATIVE CONSENSUS MECHANISM FOR
BLOCKCHAIN SYSTEMS
Oladotun Aluko1
and Anton Kolonin2
, 1
Novosibirsk State University, Russia, 2
Aigents Group,
Russia
https://aircconline.com/ijnsa/V13N4/13421ijnsa03.pdf
July 2021 | Cited by 6
ABSTRACT
Blockchains combine other technologies, such as cryptography, networking, and incentive
mechanisms, to enable the creation, validation, and recording of transactions between
participating nodes. A consensus algorithm is used in a blockchain system to determine the
shared state among distributed nodes. An important component underlying any blockchain-based
system is its consensus mechanism, which principally determines the performance and security
of the overall system. As the nature of peer-topeer(P2P) networks is open and dynamic, the
security risk within that environment is greatly increased mostly because nodes can join and
leave the network at will. Thus, it is important to have a system that can check against malicious
behaviour. In this work, we propose a reputation-based consensus mechanism for blockchain-
based systems, Proof-of-Reputation(PoR) where the nodes with the highest reputation values
eventually become part of a consensus group that determines the state of the blockchain.
KEYWORDS
Consensus Mechanism, Distributed Ledger Technology, Blockchain, Reputation System, Social
Computing

6. 5. A LITERATURE SURVEY AND ANALYSIS ON SOCIAL ENGINEERING DEFENSE
MECHANISMS AND INFOSEC POLICIES
Dalal Alharthi and Amelia Regan, University of California Irvine, USA
https://aircconline.com/ijnsa/V13N2/13221ijnsa04.pdf
March 2021 | Cited by 5
ABSTRACT
Social engineering attacks can be severe and hard to detect. Therefore, to prevent such attacks,
organizations should be aware of social engineering defense mechanisms and security policies.
To that end, the authors developed a taxonomy of social engineering defense mechanisms,
designed a survey to measure employee awareness of these mechanisms, proposed a model of
Social Engineering InfoSec Policies (SE-IPs), and designed a survey to measure the
incorporation level of these SE-IPs. After analyzing the data from the first survey, the authors
found that more than half of employees are not aware of social engineering attacks. The paper
also analyzed a second set of survey data, which found that on average, organizations
incorporated just over fifty percent of the identified formal SE-IPs. Such worrisome results show
that organizations are vulnerable to social engineering attacks, and serious steps need to be taken
to elevate awareness against these emerging security threats.
KEYWORDS
Cybersecurity, Social Engineering, Employee Awareness, Defense Mechanisms, Security
Policies

7. 6. CRITICAL INFRASTRUCTURE CYBERSECURITY CHALLENGES: IOT IN
PERSPECTIVE
Akwetey Henry Matey1
, Paul Danquah2
, Godfred Yaw Koi-Akrofi1
and Isaac Asampana1
,
1
University of Professional Studies Accra, 2
Heritage Christian University
https://aircconline.com/ijnsa/V13N4/13421ijnsa04.pdf
July 2021 | Cited by 4
ABSTRACT
A technology platform that is gradually bridging the gap between object visibility and remote
accessibility is the Internet of Things (IoT). Rapid deployment of this application can
significantly transform the health, housing, and power (distribution and generation) sectors, etc.
It has considerably changed the power sector regarding operations, services optimization, power
distribution, asset management and aided in engaging customers to reduce energy consumption.
Despite its societal opportunities and the benefits it presents, the power generation sector is
bedeviled with many security challenges on the critical infrastructure. This review discusses the
security challenges posed by IoT in power generation and critical infrastructure. To achieve this,
the authors present the various IoT applications, particularly on the grid infrastructure, from an
empirical literature perspective. The authors concluded by discussing how the various entities in
the sector can overcome these security challenges to ensure an exemplary future IoT
implementation on the power critical infrastructure value chain.
KEYWORDS
Power Distribution, Internet of Things (IoT), Sensors, Technology, Implementation

8. 7. FUTURE READY BANKING WITH SMART CONTRACTS - CBDC AND IMPACT
ON THE INDIAN ECONOMY
Bibhu Dash1
, Meraj F. Ansari1
, Pawankumar Sharma1
and Swati Swayam siddha2
, 1
School of
Computer and Information Sciences, USA, 2
KIIT University, India
https://aircconline.com/ijnsa/V14N5/14522ijnsa04.pdf
September 2022 | Cited by 3
ABSTRACT
India is significantly diverse in culture and how it promotes business transactions. Though we
are very acquainted with cash, cards, and online mode of payment, the Indian rural economy still
believes in the barter system. At this juncture, India is evolving as a tech power house, and its
economy is thriving to embrace cryptocurrency as a medium of exchange. After the Indian
finance minister declared the same last February that India is working towards building its legal
tender called Central Bank-backed Digital Currency (CBDC), this paper is making an impact in
explaining our strengths, weakness, market readiness, and necessity to adopt a digital rupee when
India's economy is highly regarded as a cashoriented economy. Is our country ready to accept the
new technological shift in smart banking in the form of a digital rupee? The paper highlights the
socioeconomic and technical challenges our planners need to understand before changing the
Central banks' monetary policies. The deployment of fifth-generation (5G) cellular network
technology has sparked renewed interest in the potential of blockchain to automate different
cellular network use cases. 5G is projected to open up new market prospects for small and large
businesses. The article highlights the unique instrument of the digital rupee to enhance peer-to-
peer transactions with the evolution of 5G mobile technology.
KEYWORDS
Smart Banking, Smart Contracts, Blockchain, digital rupee, Central Bank Digital Currency
(CBDC), FinTech, peer-to-peer transactions, security, socioeconomic impact, monetary policy

9. 8. INFORMATION-CENTRIC BLOCKCHAIN TECHNOLOGY FOR THE SMART GRID
Lanqin Sang and Henry Hexmoor, Southern Illinois University, USA
https://aircconline.com/ijnsa/V13N3/13321ijnsa03.pdf
May 2021 | Cited by 3
ABSTRACT
This paper proposes an application of blockchain technology for securing the infrastructure of
the modern power grid - an Information-Centric design for the blockchain network. In this
design, all the transactions in the blockchain network are classified into different groups, and
each group has a group number. A sender’s identity is encrypted by the control centre’s public
key; energy data is encrypted by the subscriber’s public key, and by a receiver’s public key if
this transaction is for a specific receiver; a valid signature is created via a group message and the
group publisher’s private key. Our implementation of the design demonstrated the proposal is
applicable, publisher’s identities are protected, data sources are hidden, data privacy is
maintained, and data consistency is preserved.
KEYWORDS
Information-Centric, Blockchain, Smart Grid, Network Security, Distributed System

10. 9. COMPARISON OF MALWARE CLASSIFICATION METHODS USING
CONVOLUTIONAL NEURAL NETWORK BASED ON API CALL STREAM
Matthew Schofield, Gulsum Alicioglu, Bo Sun, Russell Binaco, Paul Turner, Cameron Thatcher,
Alex Lam and Anthony Breitzman, Rowan University, USA
https://aircconline.com/ijnsa/V13N2/13221ijnsa01.pdf
March 2021 | Cited by 3
ABSTRACT
Malicious software is constantly being developed and improved, so detection and classification
of malwareis an ever-evolving problem. Since traditional malware detection techniques fail to
detect new/unknown malware, machine learning algorithms have been used to overcome this
disadvantage. We present a Convolutional Neural Network (CNN) for malware type
classification based on the API (Application Program Interface) calls. This research uses a
database of 7107 instances of API call streams and 8 different malware types:Adware, Backdoor,
Downloader, Dropper, Spyware, Trojan, Virus,Worm. We used a 1-Dimensional CNN by
mapping API calls as categorical and term frequency-inverse document frequency (TF-IDF)
vectors and compared the results to other classification techniques.The proposed 1-D CNN
outperformed other classification techniques with 91% overall accuracy for both categorical and
TFIDF vectors.
KEYWORDS
Convolutional Neural Network, Malware Classification, N-gram Analysis, Term Frequency-
Inverse Document Frequency Vectors, Windows API Calls

11. 10. GAME THEORY APPLICATION RESOURCES MANAGEMENT AND
DISTRIBUTION IN BLOCKCHAIN NETWORK
Cong Hung Tran1
, Dien Tam Le1, 2
, Thanh Hieu Huynh3
, 1
Posts and Telecommunications
Institute of Technology, Vietnam, 2
Thu Duc Technology College, Vietnam, 3
Saigon University,
Vietnam
https://aircconline.com/ijnsa/V13N1/13121ijnsa05.pdf
January 2021 | Cited by 3
ABSTRACT
The paper illustrated a basic blockchain system, applying game theory to simulate resource
management in blockchain transactions. By the method of illustration, simulation, our team has
demonstrated the effect of game theory transactions, transactions with specific value can
demonstrate the benefits of game theory in co-life. time can be used to manage resources in
blockchain. Based on the proposed algorithm model, we have built a test system with the
maximum number of virtual machines to demonstrate the effectiveness in applying game theory
in managing and distributing resources for transactions in the blockchain network.