A BENCHMARK FOR DESIGNING USABLE AND SECURE TEXT-BASED CAPTCHAS

A BENCHMARK FOR DESIGNING USABLE AND SECURE TEXT-BASED CAPTCHAS

Suliman A. Alsuhibany

Computer Science Department, College of Computer, Qassim University, Buridah, Saudi Arabia

ABSTRACT

An automated public Turing test to distinguish between computers and humans known as CAPTCHA is a widely used technique on many websites to protect their online services from malicious users. Two fundamental aspects of captcha considered in various studies in the literature are robustness and usability. A widely accepted standard benchmark, to guide the text-based captcha developers is not yet available. So this paper proposes a benchmark for designing usable-secure text-based captchas based on a community driven evaluation of the usability and security aspects. Based on this benchmark, we develop four new textbased captcha schemes, and conduct two separate experiments to evaluate both the security and usability perspectives of the developed schemes. The result of this evaluation indicates that the proposed benchmark provides a basis for designing usable-secure text-based captchas.

KEYWORDS

Text-Based CAPTCHA, security, usability, benchmark 

ORIGINAL SOURCE URL : http://aircconline.com/ijnsa/V8N4/8416ijnsa04.pdf

http://airccse.org/journal/jnsa16_current.html

PERFORMANCE ANALYSIS OF THE NEIGHBOR WEIGHT TRUST DETERMINATION ALGORITHM IN MANETS

International Journal of Network Security & Its Applications (IJNSA)
ISSN 0974 - 9330 (Online); 0975 - 2307 (Print)
http://airccse.org/journal/ijnsa.html

ARTICLE

PERFORMANCE ANALYSIS OF THE NEIGHBOR WEIGHT TRUST DETERMINATION ALGORITHM IN MANETS

Ali Abu Romman¹ and Hussein Al-Bahadili²

¹ King Hussein Faculty for Computing Sciences, Princess Sumaya University for

Technology, Amman, Jordan

² Faculty of Information Technology, University of Petra, Amman, Jordan

ABSTRACT

Mobile ad-hoc networks (MANETs) are susceptible to attacks by malicious nodes that could easily bring down the whole network. Therefore, it is important to have  a reliable mechanism for detecting and isolating malicious nodes before they can do any harm to the network. One of the possible mechanisms is by using trust-based routing protocols. One of the main requirements of such protocols is to have a cost-effective trust determination algorithm. This paper presents the performance analysis of a recently developed trust determination algorithm, namely, the neighbor-weight trust determination (NWTD) algorithm. The performance of the algorithm is evaluated through simulation using the MANET simulator (MANSim). The simulation results demonstrated the reliability and effectiveness of the algorithm in identifying and isolating any maliciously behaving node(s) in a timely manner.

KEYWORDS

NWTD; trust determination; trust-based routing protocols; malicious node; MANET; MANSim. 

Original Source URL

http://aircconline.com/ijnsa/V8N4/8416ijnsa03.pdf

http://airccse.org/journal/jnsa16_current.html

EMAIL SPAM CLASSIFICATION USING HYBRID APPROACH OF RBF NEURAL NETWORK AND PARTICLE SWARM OPTIMIZATION

EMAIL SPAM CLASSIFICATION USING HYBRID APPROACH OF RBF NEURAL NETWORK AND PARTICLE SWARM OPTIMIZATION

Mohammed Awad1 and Monir Foqaha2

1Department of Computer Systems Engineering, Arab American University-Jenin,Palestine

2Department of Computer Science, Arab American University-Jenin, Palestine

ABSTRACT

Email is one of the most popular communication media in the current century; it has become an effective and fast method to share and information exchangeall over the world. In recent years, emails users are facing problem which is spam emails. Spam emails are unsolicited, bulk emails are sent by spammers. It consumes storage of mail servers, waste of time and consumes network bandwidth.Many methods used for spam filtering to classify email messages into two groups spam and non-spam. In general, one of the most powerful tools used for data classification is Artificial Neural Networks (ANNs); it has the capability of dealing a huge amount of data with high dimensionality in better accuracy. One important type of ANNs is the Radial Basis Function Neural Networks (RBFNN) that will be used in this work to classify spam message. In this paper, we present a new approach of spam filtering technique which combinesRBFNN and Particles Swarm Optimization (PSO) algorithm (HC-RBFPSO). The proposed approach uses PSO algorithm to optimize the RBFNN parameters, depending on the evolutionary heuristic search process of PSO. PSO use to optimize the best position of the RBFNN centers c. The Radii r optimize using K-Nearest Neighbors algorithmand the weights w optimize using Singular Value Decomposition algorithm within each iterative process of PSO depending the fitness (error) function. The experiments are conducted on spam dataset namely SPAMBASE downloaded from UCI Machine Learning Repository. The experimental results show that our approach is performed in accuracy compared with other approaches that use the same dataset.

KEYWORDS

Email Spam, Classification, Radial Basis Function Neural Networks, Particles Swarm Optimization. 

ORIGINAL SOURCE URL : http://aircconline.com/ijnsa/V8N4/8416ijnsa02.pdf

http://airccse.org/journal/jnsa16_current.html

PROACTIVE DETECTION OF DDOS ATTACKS IN PUBLISH-SUBSCRIBE NETWORKS

PROACTIVE DETECTION OF DDOS ATTACKS IN PUBLISH-SUBSCRIBE NETWORKS

Bander Alzahrani1, Vassilios Vassilakis2, Mohammed Alreshoodi3, Fawaz Alarfaj4 and Ahmed Alhindi5

1Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah,Saudi Arabia

2School of Computing, Engineering and Mathematics, University of Brighton, Brighton,United Kingdom

3College of Computer, Qassim University, Buraydah, Saudi Arbaia

4Al Imam Mohammad Ibn Saud Islamic University (IMSIU), Saudi Arabia

5College of Computers and Information Systems, Umm Al-Qura University, Makkah,Saudi Arabia

ABSTRACT

Information centric networking (ICN) using architectures such as Publish-Subscribe Internet Routing Paradigm (PSIRP) or Publish-Subscribe Internet Technology (PURSUIT) has been proposed as an important candidate for the Internet of the future. ICN is an emerging research area that proposes a transformation of the current host centric Internet architecture into an architecture where information items are of primary importance. This change allows network functions such as routing and locating to be optimized based on the information items themselves. The Bloom filter based content delivery is a sourcerouting scheme that is used in the PSIRP/PURSUIT architectures. Although this mechanism solves many issues of today’s Internet such as the growth of the routing table and the scalability problems, it is vulnerable to distributed denial-of-service (DDoS) attacks. In this paper, we present a new content delivery scheme that has the advantages of Bloom filter based approach while at the same time being able to prevent DDoS attacks on the forwarding mechanism. Our security analysis suggests that with the proposed approach, the forwarding plane is able to resist attacks such as DDoS with very high probability.

KEYWORDS

Distributed denial-of-service attack; information centric network; Bloom filter. 

ORIGINAL SOURCE URL : http://aircconline.com/ijnsa/V8N4/8416ijnsa01.pdf

http://airccse.org/journal/jnsa16_current.html

COLOR IMAGE ENCRYPTION BASED ON MULTIPLE CHAOTIC SYSTEMS

COLOR IMAGE ENCRYPTION BASED ON MULTIPLE CHAOTIC SYSTEMS

Yuting Xi, Xing Zhang and Ruisong Ye

Department of Mathematics, Shantou University Shantou, Guangdong, 515063, P. R. China

ABSTRACT

This paper proposed a novel color image encryption scheme based on multiple chaotic systems. The ergodicity property of chaotic system is utilized to perform the permutation process; a substitution operation is applied to achieve the diffusion effect. In permutation stage, the 3D color plain-image matrix is converted to a 2D image matrix, then two generalized Arnold maps are employed to generate hybrid chaotic sequences which are dependent on the plain-image’s content. The generated chaotic sequences are then applied to perform the permutation process. The encryption’s key streams not only depend on the cipher keys but also depend on plain-image and therefore can resist chosen-plaintext attack as well as known-plaintext attack. In the diffusion stage, four pseudo-random gray value sequences are generated by another generalized Arnold map. The gray value sequences are applied to perform the diffusion process by bitxoring operation with the permuted image row-by-row or column-by-column to improve the encryption rate. The security and performance analysis have been performed, including key space analysis, histogram analysis, correlation analysis, information entropy analysis, key sensitivity analysis, differential analysis etc. The experimental results show that the proposed image encryption scheme is highly secure thanks to its large key space and efficient permutation-substitution operation, and therefore it is suitable for practical

image and video encryption.

KEYWORDS

Generalized Arnold Map, Permutation, Substitution, Chaotic System, Image Encryption 

ORIGINAL SOURCE URL : http://aircconline.com/ijnsa/V8N5/8516ijnsa03.pdf

http://airccse.org/journal/jnsa16_current.html

International Journal of Network Security & Its Applications (IJNSA)

International Journal of Network Security & Its Applications (IJNSA)         

       

ISSN 0974 - 9330 (Online); 0975 - 2307 (Print)      

 http://airccse.org/journal/ijnsa.html

International Journal of Network Security & Its Applications (IJNSA)

International Journal of Network Security & Its Applications (IJNSA)

--- UGC Listed, ERA Indexed----

ISSN 0974 - 9330 (Online); 0975 - 2307 (Print)

http://airccse.org/journal/ijnsa.html

                

Scope & Topics

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.

Topics of Interest include, but are not limited to, the following:

• Network and Wireless Network Security
• Mobile, Ad Hoc and Sensor Network Security
• Peer-to-Peer Network Security
• Database and System Security
• Intrusion Detection and Prevention
• Internet Security & Applications
• Security & Network Management
• E-mail security, Spam, Phishing, E-mail fraud
• Virus, worms, Trojan Protection
• Security threats & countermeasures (DDoS, MiM, Session Hijacking, Replay attack etc,)
• Ubiquitous Computing Security
• Web 2.0 security
• Cryptographic protocols
• Performance Evaluations of Protocols & Security Application

Paper submission

Authors are invited to submit papers for this journal through e-mail ijnsa@airccse.org or Submission System.  Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this Journal.

Important Dates

• Submission Deadline   : July 06, 2019
• Notification                   :  August 06, 2019
• Final Manuscript Due   :  August 14, 2019
• Publication Date           :  Determined by the Editor-in-Chief

For other details please visit http://airccse.org/journal/ijnsa.html 

ENHANCE RFID SECURITY AGAINST BRUTE FORCE ATTACK BASED ON PASSWORD STRENGTH AND MARKOV MODEL

ENHANCE RFID SECURITY AGAINST BRUTE FORCE ATTACK BASED ON PASSWORD STRENGTH AND MARKOV MODEL

Dr. Adwan Yasin1 and Fadi AbuAlrub2

1,2Computer Science Department, Arab American University Jenin - Palestine

ABSTRACT

RFID systems are one of the important techniques that have been used in modern technologies; these systems rely heavily on default and random passwords. Due to the increasing use of RFID in various industries, security and privacy issues should be addressed carefully as there is no efficient way to achieve security in this technology. Some active tags are low cost and basic tags cannot use standard cryptographic operations where the uses of such techniques increase the cost of these cards. This paper sheds light on the weaknesses of RFID system and identifies the threats and countermeasures of possible attacks. For the sake of this paper, an algorithm was designed to ensure and measure the strength of passwords used in the authentication process between tag and reader to enhance security in their communication and defend against brute-force attacks. Our algorithm is design by modern techniques based on entropy, password length, cardinality, Markov-model and Fuzzy Logic.

KEYWORDS

RFID, brute-force attack, Markov-model, entropy, fuzzy logic. 

ORIGINAL SOURCE URL : http://aircconline.com/ijnsa/V8N5/8516ijnsa02.pdf

http://airccse.org/journal/jnsa16_current.html

A HYBRID APPROACH COMBINING RULE-BASED AND ANOMALY-BASED DETECTION AGAINST DDOS ATTACKS

A HYBRID APPROACH COMBINING RULE-BASED AND ANOMALY-BASED DETECTION AGAINST DDOS ATTACKS

Chin-Ling Chen1  and Hsin-Chiao Chen2

1Department of Information Management, National Pingtung University, Pingtung,Taiwan, 900

2Department of Information Management, National Pingtung Institute of Commerce,Pingtung, Taiwan, 900

ABSTRACT

We have designed a hybrid approach combining rule-based and anomaly-based detection against DDoS attacks. In the approach, the rule-based detection has established a set of rules and the anomaly-based detection use one-way ANOVA test to detect possible attacks. We adopt TFN2K (Tribe Flood, the Net 2K) as an attack traffic generator and monitor the system resource of the victim like throughput, memory utilization, CPU utilization consumed by attack traffic. Target users of the proposed scheme are data center administrators. The types of attack traffic have been analysed and by that we develop a defense scheme. The experiment has demonstrated that the proposed scheme can effectively detect the attack traffic.

KEYWORDS

Distributed denial of service, firewall, detection 

ORIGINAL SOURCE URL : http://aircconline.com/ijnsa/V8N5/8516ijnsa01.pdf

http://airccse.org/journal/jnsa16_current.html

A BASTION MOBILEID-BASED AUTHENTICATION TECHNIQUE (BMBAT)

A BASTION MOBILEID-BASED AUTHENTICATION TECHNIQUE (BMBAT)

Abdelmunem Abuhasan1 and Adwan Yasin2

1,2Department of Computer Science, Arab American University, Jenin, Palestine

ABSTRACT

Despite their proven security breaches, text passwords have been dominating all other methods of human authentication over the web for tens of years, however, the frequent successful attacks that exploit the passwords vulnerable model raises the need to enhance web authentication security. This paper proposes BMBAT; a new authentication technique to replace passwords, that leverages the pervasive user mobile devices, QR codes and the strength of symmetric and asymmetric cryptography. In BMBAT, the user’s mobile device acts as a user identity prover and a verifier for the server; it employs a challenge-response model with a dual mode of encryption using AES and RSA keys to mutually authenticate the client to the server and vice-versa. BMBAT combats a set of attack vectors including phishing attacks, man in the  middle attacks, eavesdropping and session hijacking. A prototype of BMBAT has been developed and evaluated; the evaluation results show that BMBAT is a feasible and competitive alternative to passwords.

KEYWORDS

Web Authentication, Mobile Authentication, phishing, User Identity, Password.

OPEN SOURCE URL : http://aircconline.com/ijnsa/V8N6/8616ijnsa03.pdf

http://airccse.org/journal/jnsa16_current.html

A MECHANISM FOR EARLY DETECTING DDOS ATTACKS BASED ON M/G/R PS QUEUE

A MECHANISM FOR EARLY DETECTING DDOS ATTACKS BASED ON M/G/R PS QUEUE

Nguyen Hong Son

Department of Information and Communication Technology, Post and Telecommunication Institute of Technology, Ho Chi Minh City, Viet Nam

ABSTRACT

When service system is under DDoS attacks, it is important to detect anomaly signature at starting time of attack for timely applying prevention solutions. However, early DDoS detection is difficult task because the velocity of DDoS attacks is very high. This paper proposes a DDoS attack detection method by modeling service system as M/G/R PS queue and calculating monitoring parameters based on the model in odder to early detect symptom of DDoS attacks. The proposed method is validated by experimental system and it gives good results.

KEYWORDS

DDoS, Detection, M/G/R Processor Sharing queue

OPEN SOURCE URL : http://aircconline.com/ijnsa/V8N6/8616ijnsa02.pdf

http://airccse.org/journal/jnsa16_current.html

STEGANALYSIS ALGORITHM FOR PNG IMAGES BASED ON FUZZY LOGIC TECHNIQUE

STEGANALYSIS ALGORITHM FOR PNG IMAGES BASED ON FUZZY LOGIC TECHNIQUE

Jawaher alqahtani, Daniyal Alghazzawi1 and Li Cheng2

1Department of Information Systems, King Abdulaziz University, Jeddah, Saudi Arabia

2Xinjiang Technical Institute of Physics & Chemistry, Chinese Academy of Sciences,China

ABSTRACT

Embedding a message in media files, also known as steganography, is a common approach to hide secret information. It has been exploited by some criminals to confidentially exchange messages. As a countermeasure, tools have been developed in order to detect hidden information form digital media such as text, image, audio or video files. However the efficiency and performance of previous approaches still have room for improvement. In this research, we focus on algorithm design for better efficiency of hidden message detection from PNG files. We employ three classic AI approaches including neural network, fuzzy logic, and genetic algorithm and evaluate their efficiency and performance in controlled experiments. Finally we introduce our message detection system for PNG files based on LSB approach and present its

usability in different case scenarios.

KEYWORDS

Steganography, Steganalysis, Artificial Intelligence, fuzzy logic. 

OPEN SOURCE URL : http://aircconline.com/ijnsa/V8N6/8616ijnsa01.pdf

http://airccse.org/journal/jnsa16_current.html

A COMBINATION OF TEMPORAL SEQUENCE LEARNING AND DATA DESCRIPTION FOR ANOMALYBASED NIDS

A COMBINATION OF TEMPORAL SEQUENCE LEARNING AND DATA DESCRIPTION FOR ANOMALYBASED NIDS

Nguyen Thanh Van1,2, Tran Ngoc Thinh1, Le Thanh Sach1

1Faculty of Computer Science and Engineering. Ho Chi Minh City University of Technology, VNUHCM, VietNam.

2Ho Chi Minh City University of Technology and Education, VietNam.

ABSTRACT

Through continuous observation and modelling of normal behavior in networks, Anomaly-based Network Intrusion Detection System (A-NIDS) offers a way to find possible threats via deviation from the normal model. The analysis of network traffic based on time series model has the advantage of exploiting the relationship between packages within network traffic and observing trends of behaviors over a period of time. It will generate new sequences with good features that support anomaly detection in network traffic and provide the ability to detect new attacks. Besides, an anomaly detection technique, which focuses on the normal data and aims to build a description of it, will be an effective technique for anomaly detection in imbalanced data. In this paper, we propose a combination model of Long Short Term Memory (LSTM) architecture for processing time series and a data description Support Vector Data Description (SVDD) for anomaly detection in A-NIDS to obtain the advantages of them. This model helps parameters in LSTM and SVDD are jointly trained with joint optimization method. Our experimental results with KDD99 dataset show that the proposed combined model obtains high performance in intrusion detection, especially DoS and Probe attacks with 98.0% and 99.8%, respectively.

KEYWORDS

Anomaly-based network intrusion detection system, temporal sequence, data description 

ORIGINAL SOURCE URL : http://aircconline.com/ijnsa/V11N3/11319ijnsa07.pdf

http://airccse.org/journal/jnsa19_current.html

XDOSER, A BENCHMARKING TOOL FOR SYSTEM LOAD MEASUREMENT USING DENIAL OF SERVICE FEATURES

XDOSER, A BENCHMARKING TOOL FOR SYSTEM LOAD MEASUREMENT USING DENIAL OF SERVICE FEATURES

AKM Bahalul Haque, Rabeya Sultana, Mohammad Sajid Fahad , MD Nasif Latif and Md. Amdadul Bari

Department of Electrical and Computer Engineering, North South University, Dhaka, Bangladesh

ABSTRACT

Technology has developed so fast that we feel both safe as well as unsafe in both ways. Systems used today are always prone to attack by malicious users. In most cases, services are hindered because these systems cannot handle the amount of over loads the attacker provides. So, proper service load measurement is necessary. The tool that is being described in this paper for developments is based on the Denial of Service methodologies. This tool, XDoser will put a synthetic load on the servers for testing purpose. The HTTP Flood method is used which includes an HTTP POST method as it forces the website to gather the maximum resources possible in response to every single request. The tool developed in this paper will focus on overloading the backend with multiple requests. So, the tool can be implemented for servers new or old for synthetic test endurance testing.

KEYWORDS

Denial-of-service, attack, unavailability, security, httprequests, OkHttpClient 

Original Source Link : http://aircconline.com/ijnsa/V11N3/11319ijnsa03.pdf

http://airccse.org/journal/jnsa19_current.html

CLASSIFICATION PROCEDURES FOR INTRUSION DETECTION BASED ON KDD CUP 99 DATA SET

CLASSIFICATION PROCEDURES FOR INTRUSION DETECTION BASED ON KDD CUP 99 DATA SET

Shaker El-Sappagh, Ahmed Saad Mohammed, Tarek Ahmed AlSheshtawy

Faculty of Computers & Informatics, Benha University, Egypt.

ABSTRACT

In network security framework, intrusion detection is one of a benchmark part and is a fundamental way to protect PC from many threads. The huge issue in intrusion detection is presented as a huge number of false alerts; this issue motivates several experts to discover the solution for minifying false alerts according to data mining that is a consideration as analysis procedure utilized in a large data e.g. KDD CUP 99. This paper presented various data mining classification for handling false alerts in intrusion detection as reviewed. According to the result of testing many procedure of data mining on KDD CUP 99 that is no individual procedure can reveal all attack class, with high accuracy and without false alerts. The best accuracy in Multilayer Perceptron is 92%; however, the best Training Time in Rule based model is 4 seconds . It is concluded that ,various procedures should be utilized to handle several of network attacks. 

KEYWORDS

Intrusion Detection, Data Mining, KDD CUP 99, False Alarms

Original Source Link : http://aircconline.com/ijnsa/V11N3/11319ijnsa02.pdf

http://airccse.org/journal/jnsa19_current.html

CLASSIFICATION PROCEDURES FOR INTRUSION DETECTION BASED ON KDD CUP 99 DATA SET

CLASSIFICATION PROCEDURES FOR INTRUSION DETECTION BASED ON KDD CUP 99 DATA SET

Shaker El-Sappagh, Ahmed Saad Mohammed, Tarek Ahmed AlSheshtawy

Faculty of Computers & Informatics, Benha University, Egypt.

ABSTRACT

In network security framework, intrusion detection is one of a benchmark part and is a fundamental way to protect PC from many threads. The huge issue in intrusion detection is presented as a huge number of false alerts; this issue motivates several experts to discover the solution for minifying false alerts according to data mining that is a consideration as analysis procedure utilized in a large data e.g. KDD CUP 99. This paper presented various data mining classification for handling false alerts in intrusion detection as reviewed. According to the result of testing many procedure of data mining on KDD CUP 99 that is no individual procedure can reveal all attack class, with high accuracy and without false alerts. The best accuracy in Multilayer Perceptron is 92%; however, the best Training Time in Rule based model is 4 seconds . It is concluded that ,various procedures should be utilized to handle several of network attacks.

KEYWORDS

Intrusion Detection, Data Mining, KDD CUP 99, False Alarms

Original Source Link : http://aircconline.com/ijnsa/V11N3/11319ijnsa02.pdf

http://airccse.org/journal/jnsa19_current.html

ENHANCING THE WORDPRESS SYSTEM:FROM ROLE TO ATTRIBUTE-BASED ACCESS CONTROL

ENHANCING THE WORDPRESS SYSTEM:FROM ROLE TO ATTRIBUTE-BASED ACCESS CONTROL

Lifeng Cao, Jia Ying Ou, Amirhossein Chinaei

EECS Department, York University, Toronto, Canada

ABSTRACT

Role-Based Access Control (RBAC) is the most commonly used model on web applications. The advantages of RBAC are the ease of understanding, applying and managing privileges. The static RBAC model cannot alter access permission in real-time without human involvement and therefore the model suffers from increasing false negative (and/or false positive) outcomes. Hence, the Attribute-Based Access Control (ABAC) model has been proposed to introduce dynamicity and minimize human involvement in order to enhance security. WordPress is a very popular Role-Based content management system. To our best knowledge, no solution to merge from RBAC to ABAC model for WordPress applications has been found. Our contribution is a WordPress plug-in that we have developed to build ABAC upon the existing RBAC setups. In this journey, we have investigated various scenarios by studying different application categories to come up with an enhanced automatic model that adds real-time grant and revoke feature to WordPress.

KEYWORDS

Role-Base-Access-Control, Attribute-Base-Access-Control, WordPress, Content Management, Security

Original Source Link :http://aircconline.com/ijnsa/V11N3/11319ijnsa01.pdf

http://airccse.org/journal/jnsa19_current.html

International Journal of Network Security & Its Applications (IJNSA) - Current Issue - May 2019, Volume 11, Number 3

International Journal of Network Security & Its Applications (IJNSA)

ISSN 0974 - 9330 (Online); 0975 - 2307 (Print)

http://airccse.org/journal/ijnsa.html

Current Issue - May 2019, Volume 11, Number 3

Enhancing the Wordpress System: from Role to Attribute-Based Access Control

Lifeng Cao, Jia Ying Ou and Amirhossein Chinaei, York University, Canada

http://aircconline.com/ijnsa/V11N3/11319ijnsa01.pdf 

Classification Procedures for Intrusion Detection Based on KDD CUP 99 Data Set

Shaker El-Sappagh, Ahmed Saad Mohammed and Tarek Ahmed AlSheshtawy, Benha University, Egypt

http://aircconline.com/ijnsa/V11N3/11319ijnsa02.pdf

Xdoser, A Benchmarking Tool for System Load Measurement Using Denial of Service Features

AKM Bahalul Haque, Rabeya Sultana, Mohammad Sajid Fahad , MD Nasif Latif and Md. Amdadul Bari, North South University, Bangladesh

http://aircconline.com/ijnsa/V11N3/11319ijnsa03.pdf

Multi-Layer Classifier for Minimizing False Intrusion

Shaker El-Sappagh, Ahmed saad Mohammed and Tarek Ahmed AlSheshtawy, Benha University, Egypt

http://aircconline.com/ijnsa/V11N3/11319ijnsa04.pdf

Methods Toward Enhancing RSA Algorithm : A Survey

Shaheen Saad Al-Kaabi and Samir Brahim Belhaouari, Hamad Bin Khalifa University (HBKU), Qatar

http://aircconline.com/ijnsa/V11N3/11319ijnsa05.pdf

Survey on Secure Routing in Vanets

Afef Slama1 and Ilhem Lengliz2, 1University of Manouba, Tunisia and 2Military Academy, Tunisia

http://aircconline.com/ijnsa/V11N3/11319ijnsa06.pdf

A Combination of Temporal Sequence Learning and Data Description for Anomaly - based NIDS

Nguyen Thanh Van1,2, Tran Ngoc Thinh1 and Le Thanh Sach1, 1Ho Chi Minh City University of Technology, VietNam and 2Ho Chi Minh City University of Technology and Education, VietNam

http://aircconline.com/ijnsa/V11N3/11319ijnsa07.pdf

http://airccse.org/journal/jnsa19_current.html