International Journal of Computer (IJC)

To have an Idea on NoSQL Databases

Bruno SADEG, Claude DUVALLET — Tue, 03 Sep 2019 00:00:00 +0000

NoSQL databases (initially non-SQL, then Not Only SQL) are specifically designed to handle large amounts of data. They have been developed since the 1970s, but they have gained the interest of academia and industry for about two decades. This is because of their powerful characteristics and lack of relational databases, which are the most widely used data sources around the world. Indeed, these databases are based on the relational model, which is materialized by a relational database management system (RDBMS). Although RDBMS efficiently manage data (tables), they have many drawbacks that make them unsuitable for managing current data, which come mainly from Internet applications. They are called Big Data and they are used for example by Twitter, FaceBook, LinkedIn, .... They are very numerous and tend to change quickly. In fact, among the disadvantages of relational databases, we can mention: non-flexibility, non-scalability, ... On the contrary, NoSQL databases evolve very well (scaling) and almost all NoSQL databases are schema-free (we can add or delete an entity or a relationship at any time during execution). In this article, we begin by giving an overview of relational databases and their characteristics. We then describe the NoSQL databases and their main characteristics, knowing that there are as many different characteristics as "NoSQL databases" products. We then give the taxonomy of NoSQL databases, which distinguishes four main types of NoSQL databases: key-value, wide-column, document and graphical databases. We will then give some elements of each type of database through the use of a product, an implementation of a kind of such a database.

Bilinear Pairing Based Encryption for Sensor Network

Kelechi Emerole, Maurice Anyaehie, Stanley Nwadike — Tue, 03 Sep 2019 06:39:59 +0000

In this letter, we review some research efforts in the area of Pairing based encryption for data transmission and storage taking note of the computational overhead and consequently present a simple encryption scheme to buttress our initiative further.

Detection of Android Malware based on Sequence Alignment of Permissions

Franklin Tchakounté, Albert Djakene Wandala, Yélémou Tiguiane — Tue, 17 Sep 2019 08:27:42 +0000

Permissions control accesses to critical resources on Android. Any weaknesses from their exploitation can be of great interest to attackers. Investigation about associations of permissions can reveal some patterns against attacks. In this regards, this paper proposes an approach based on sequence alignment between requested permissions to identify similarities between applications. Permission patterns for malicious and normal samples are determined and exploited to evaluate a similarity score. The nature of an application is obtained based on a threshold, judiciously computed. Experiments have been realized with a dataset of 534 malicious samples (300 training and 234 testing) and 534 normal samples (300 training and 234 testing). Our approach has been able to recognize testing samples (either malware or normal) with an accuracy of 79%, an average precision of 76% and an average recall of 75%. This research reveals that sequence alignment can improve malware detection research.

An Architecture for Misconfiguration Patching of Web Services: A Case Study of Apache Server

Franklin Tchakounté, Jean Marie Kuate Fotso, Vivient Corneille Kamla — Tue, 17 Sep 2019 08:44:12 +0000

Services are usually left configured by default and therefore subjects to vulnerabilities because they are not security enforced. Web services are so popular that they are targets of attacks to intrusions related to vulnerabilities discovered by attackers. This work proposes an architecture for patching Web service misconfigurations related to existing vulnerabilities. The approach underlying this architecture first retrieves and structures anti-vulnerability measures published by the official service manufacturers. Second, it evaluates the risk level using Common Vulnerability Scoring System (CVSS) on the current state of configurations. The proposed approach has been applied on Apache server on four vulnerabilities: version discovery, XSS, SQL injection and deny of service. Experimental results on a vulnerable environment demonstrate that the proposed approach considerably reduces vulnerabilities compared to similar solutions.

Burst Loss Reduction Using Fuzzy-Based Adaptive Burst Length Assembly Technique for Optical Burst Switched Networks

Abubakar Muhammad Umaru — Sat, 28 Sep 2019 02:21:12 +0000

The optical burst switching (OBS) paradigm is perceived as an intermediate switching technology prior to the realization of an all-optical network. Burst assembly is the first process that takes place at the edge of an OBS network. It is crucial to the performance of an OBS network because it greatly influences loss and delay on such networks. Burst assembly is an important process while burst loss ratio (BLR) and delay are important issues in OBS. In this paper, an intelligent burst assembly algorithm called a Fuzzy-based Adaptive Length Burst Assembly (FALBA) algorithm that is based on fuzzy logic and tuning of fuzzy logic parameters is proposed for OBS network. FALBA was evaluated against itself and the fuzzy adaptive threshold (FAT) burst assembly algorithm using 12 configurations via simulation. The 12 configurations were derived from three rule sets (denoted 0,1,2), two defuzzification techniques (Centroid [C]and Largest of Maximum[L]) and two aggregation methods (Max[M] and Sum[S]) of fuzzy logic. Simulation results have shown that FALBA_0LM has the best BLR performance when compared to its other configurations and the FAT. However, with respect to delay, FAT only outperforms all configurations of FALBA at low loads (0.0-0.4) but the performance of FAT also decreases as the load (0.4-1.0) increases. Therefore, at high loads (0.4-1.0) FALBA_2CS has the best delay performance. Our results deduce that FALBA_0LMcan be used

Distributed Denial of Service Attack Challenges in Cloud Computing: A Review

Adesegun O. A., Izang A. A, Nzenwata J. Uchenna, Udosen Alfred Akpan — Thu, 31 Oct 2019 10:35:59 +0000

Cloud computing as an ever-evolving technology has appeared to be a new discovery, with a history that can be traced to the 1960s, yet the computing paradigm has not been fully adopted till date. This is due to the security and trust management issues associated with the paradigm. Studies so far have shown remarkable efforts in the area of cloud computing security but has paid little attention to the area of application-based denial of service and its distributed variant. To this end, this paper highlights the Extensive Mark-up Language Denial of Service (XDoS) and the Extensive Mark-up Language Distributed Denial of Service (XDDoS) as one of the security challenges that inhibit the adoption of cloud computing. So many researchers in this field have proposed different solutions to this issues, however, it was observed that there is a need for an efficient and more effective counter-measures solution against XDoS and its distributed variant XDDoS which are application based denial of service that can be found in software as a service (SaaS) cloud computing service model.

The Fight against Cybercrime in Cameroon

Prof. André Boraine, Dr Ngaundje Leno Doris — Mon, 04 Nov 2019 21:28:24 +0000

With the on-going Anglophone crisis in the two English-speaking regions of Cameroon, individuals, businesses and the government are increasingly becoming at risk of being targeted by cyber criminals. Amid this challenge, Cameroon has enacted a law relating to Cyber Security and Cyber Criminality (hereinafter referred to as the Cyber law) and trained personels to fight cybercrime. In spite of these measures, cybercrime is still rampant and the question is why? This contribution therefore examines the measures put in place to combat cybercrime with the aim of showing that the measures are inadequate. Also, the contribution explains why cybercrime is prevalent in Cameroon and concludes with measures to prevent and minimise the impacts of cybercrime (recommendations). This paper aims to raise awareness and improve knowledge of data protection rules, especially among investigating officers, students, specialists and non-specialist legal practitioners who have to deal with data protection issues in their work.

Development of a Myers-Briggs Type Indicator Based Personalised E-Learning System

Olumide Adewale, Oluwatoyin Agbonifo, Ojoma Osajiuba — Wed, 13 Nov 2019 00:00:00 +0000

The major challenge of the traditional learning system is space-time restriction and it is teacher-centred. The emergence of Information Technology gave rise for e-learning systems which are characterized with the components of teacher-centred and one-size-fits-all strategy. Subsequently, the concept of personalisation with learning technology was introduced that provides adaptation of learning contents to learning requirements of the learners. Hence, this research paper develops a personalised e-learning system that matches teaching strategy with learners’ learning style using Myers-Briggs Type Indicator (MBTI). The emphasis is laid on adaptive teaching strategy and revising the teaching strategy for the purpose of increasing learners’ learning performance. The mathematical model is developed for profiling learners to determine their learning style based on the MBTI questionnaire and Dynamic Bayesian Network is applied to revise the teaching strategy. The system is implemented using PHP and Wamp server and the database is designed using Structured Query Language (SQL). The developed system is tested using Undergraduate students studying Information Technology at Federal University of Technology, Minna. The percentage analysis of the students’ scores shows that 78% of students passed and the remaining 22% passed when the strategy was revised. The performance evaluation of the system is carried out and from the analysis it can be concluded that the Myers-Briggs Type Indicator Based Personalised E-learning System developed is appealing to students and the performance of students improved significantly.

Critical Review in Computer Science: Identification of the Relationship of the Social and Human Factors Related to Teamwork with Software Development Team’s Productivity

Muhammad Fachrul Hasan Mujtahid — Sun, 24 Nov 2019 07:38:46 +0000

This research aims to explore crucial matters related to software development team collaboration that affects productivity. The collaboration component will be discussed in this research including attitude competencies, skill competencies, and knowledge competencies. The results of this study indicate that the components and relationships and human factors influence the productivity of the software development team.