Mısra, Sanjay

Mısra, Sanjay

Name Variants

M.,Sanjay
Misra, Sanjay
Mısra,S.
Mısra, Sanjay
Misra,S.
S.,Misra
Sanjay, Mısra
Sanjay, Misra
S., Misra
S.,Mısra
M., Sanjay
Misra, S.

Job Title

Profesör Doktor

Email Address

sanjay.misra@atilim.edu.tr

Main Affiliation

Computer Engineering

Full item page

Scholarly Output

189

Articles

120

Citation Count

2203

Supervised Theses

1 Scholarly Output Search Results

Now showing 1 - 10 of 189

Citation - WoS: 5
Citation - Scopus: 7
The Role of Leadership Cognitive Complexity in Software Development Projects: an Empirical Assessment for Simple Thinking
(Wiley, 2011) Akman, Ibrahim; Misra, Sanjay; Cafer, Ferid; Computer Engineering
Simple thinking (or simplicity) is a way of coping with complexity. It is especially important in the software development process (SDP), which is an error-prone, time-consuming, and complex activity. This article investigates the role of the thinking style-namely, simple thinking-which has been found effective in solving complicated problems during software development. For this purpose, it reviews and discusses simplicity issues from a general perspective and, then, reports the findings of a survey concerning the assessment of simplicity in SDP. The survey was conducted among information and communication technologies senior professionals and managers from government and private-sector organizations. Relevant hypotheses have been developed under different empirical categories for analysis. Statistical analysis techniques were then used to draw inferences based on these hypotheses. The results have proved simplicity to have a significant role in the SDP to a certain extent. (C) 2011 Wiley Periodicals, Inc.
Citation - WoS: 9
Citation - Scopus: 22
Anomaly Detection Using Fuzzy Q-Learning Algorithm
(Budapest Tech, 2014) Shamshirband, Shahaboddin; Anuar, Nor Badrul; Kiah, Miss Laiha Mat; Misra, Sanjay; Computer Engineering; Computer Engineering
Wireless networks are increasingly overwhelmed by Distributed Denial of Service (DDoS) attacks by generating flooding packets that exhaust critical computing and communication resources of a victim's mobile device within a very short period of time. This must be protected. Effective detection of DDoS attacks requires an adaptive learning classifier, with less computational complexity, and an accurate decision making to stunt such attacks. In this paper, we propose an intrusion detection system called Fuzzy Q-learning (FQL) algorithm to protect wireless nodes within the network and target nodes from DDoS attacks to identify the attack patterns and take appropriate countermeasures. The FQL algorithm was trained and tested to establish its performance by generating attacks from the NSL-KDD and CAIDA DDoS Attack datasets during the simulation experiments. Experimental results show that the proposed FQL IDS has higher accuracy of detection rate than Fuzzy Logic Controller and Q-learning algorithm alone.
Citation - WoS: 10
Citation - Scopus: 16
Prospects of Ocean-Based Renewable Energy for West Africa's Sustainable Energy Future
(Emerald Group Publishing Ltd, 2021) Adesanya, Ayokunle; Misra, Sanjay; Maskeliunas, Rytis; Damasevicius, Robertas; Computer Engineering
Purpose The limited supply of fossil fuels, constant rise in the demand of energy and the importance of reducing greenhouse emissions have brought the adoption of renewable energy sources for generation of electrical power. One of these sources that has the potential to supply the world's energy needs is the ocean. Currently, ocean in West African region is mostly utilized for the extraction of oil and gas from the continental shelf. However, this resource is depleting, and the adaptation of ocean energy could be of major importance. The purpose of this paper is to discuss the possibilities of ocean-based renewable energy (OBRE) and analyze the economic impact of adapting an ocean energy using a thermal gradient (OTEC) approach for energy generation. Design/methodology/approach The analysis is conducted from the perspective of cost, energy security and environmental protection. Findings This study shows that adapting ocean energy in the West Africa region can significantly produce the energy needed to match the rising energy demands for sustainable development of Nigeria. Although the transition toward using OBRE will incur high capital cost at the initial stage, eventually, it will lead to a cost-effective generation, transmission, environmental improvement and stable energy supply to match demand when compared with the conventional mode of generation in West Africa. Originality/value The study will contribute toward analysis of the opportunities for adopting renewable energy sources and increasing energy sustainability for the West Africa coast regions.
Measuring Complexity of Object Oriented Programs
(2008) Misra,S.; Akman,I.; Computer Engineering
In this paper, a metric for object oriented language is formulated and validated. On the contrary of the other metrics used for object oriented programming (OOPs), the proposed metric calculates the complexity of a class at method level and hence considers the internal architecture of the classes, subclasses and member functions. The proposed metric is evaluated against Weyuker's proposed set of measurement principles through examples and validated through experimentation, case study and comparative study with similar measures. The practical usefulness of the metric is evaluated by a practical framework. © 2008 Springer-Verlag Berlin Heidelberg.
Citation - WoS: 0
Citation - Scopus: 0
Weak Measurement Theory and Modified Cognitive Complexity Measure
(insticc-inst Syst Technologies information Control & Communication, 2007) Misra, Sanjay; Kilic, Huerevren; Computer Engineering; Computer Engineering
Measurement is one of the problems in the area of software engineering. Since traditional measurement theory has a major problem in defining empirical observations on software entities in terms of their measured quantities, Morasca has tried to solve this problem by proposing Weak Measurement theory. In this paper, we tried to evaluate the applicability of weak measurement theory by applying it on a newly proposed Modified Cognitive Complexity Measure (MCCM). We also investigated the applicability of Weak Extensive Structure for deciding on the type of scale for MCCM. It is observed that the MCCM is on weak ratio scale.
Citation - WoS: 2
Citation - Scopus: 2
Impact of Mobile Received Signal Strength (rss) on Roaming and Non-Roaming Mobile Subscribers
(Springer, 2023) Karanja, Hinga Simon; Misra, Sanjay; Atayero, A. A. A.; Computer Engineering
Mobile phones have transitioned from voice-centric devices to smart devices supporting functionalities like high-definition video and games, web browsers, radio reception, and video conferencing. Mobile phones are used in telemedicine, health monitoring applications, navigation tools, and gaming devices, among other applications. Given the above, Mobile broadband connectivity affects mobile access to the internet and voice communications. This paper assesses the impact of the Reference Signal Received Power (RSRP) and broadband connectivity around Covenant University. LTE, GSM, and HSPA mobile signal measurement campaigns were conducted around Covenant University in Ota, Ogun state, Nigeria. To investigate the best optimized mobile network for mobile subscribers on roaming services and subscriber's high performance and data rates. After the experiment, exploratory data analysis was used to visualize the best mobile network; GSM proved as stable than LTE and HSPA.
Citation - WoS: 28
Citation - Scopus: 53
A Review of Soft Techniques for Sms Spam Classification: Methods, Approaches and Applications
(Pergamon-elsevier Science Ltd, 2019) Abayomi-Alli, Olusola; Misra, Sanjay; Abayomi-Alli, Adebayo; Odusami, Modupe; Computer Engineering
Background: The easy accessibility and simplicity of Short Message Services (SMS) have made it attractive to malicious users thereby incurring unnecessary costing on the mobile users and the Network providers' resources. Aim: The aim of this paper is to identify and review existing state of the art methodology for SMS spam based on some certain metrics: AI methods and techniques, approaches and deployed environment and the overall acceptability of existing SMS applications. Methodology: This study explored eleven databases which include IEEE, Science Direct, Springer, Wiley, ACM, DBLP, Emerald, SU, Sage, Google Scholar, and Taylor and Francis, a total number of 1198 publications were found. Several screening criteria were conducted for relevant papers such as duplicate removal, removal based on irrelevancy, abstract eligibility based on the removal of papers with ambiguity (undefined methodology). Finally, 83 papers were identified for depth analysis and relevance. A quantitative evaluation was conducted on the selected studies using seven search strategies (SS): source, methods/ techniques, AI approach, architecture, status, datasets and SMS spam mobile applications. Result: A Quantitative Analysis (QA) was conducted on the selected studies and the result based on existing methodology for classification shows that machine learning gave the highest result with 49% with algorithms such as Bayesian and support vector machines showing highest usage. Unlike statistical analysis with 39% and evolutionary algorithms gave 12%. However, the QA for feature selection methods shows that more studies utilized document frequency, term frequency and n-grams techniques for effective features selection process. Result based on existing approaches for content-based, non-content and hybrid approaches is 83%, 5%, and 12% respectively. The QA based on architecture shows that 25% of existing solutions are deployed on the client side, 19% on server-side, 6% collaborative and 50% unspecified. This survey was able to identify the status of existing SMS spam research as 35% of existing study was based on proposed new methods using existing algorithms and 29% based on only evaluation of existing algorithms, 20% was based on proposed methods only. Conclusion: This study concludes with very interesting findings which shows that the majority of existing SMS spam filtering solutions are still between the "Proposed" status or "Proposed and Evaluated" status. In addition, the taxonomy of existing state of the art methodologies is developed and it is concluded that 8.23% of Android users actually utilize this existing SMS anti-spam applications. Our study also concludes that there is a need for researchers to exploit all security methods and algorithm to secure SMS thus enhancing further classification in other short message platforms. A new English SMS spam dataset is also generated for future research efforts in Text mining, Tele-marketing for reducing global spam activities.
Citation - WoS: 74
Citation - Scopus: 93
Co-Fais: Cooperative Fuzzy Artificial Immune System for Detecting Intrusion in Wireless Sensor Networks
(Academic Press Ltd- Elsevier Science Ltd, 2014) Shamshirband, Shahaboddin; Anuar, Nor Badrul; Kiah, Miss Laiha Mat; Rohani, Vala Ali; Petkovic, Dalibor; Misra, Sanjay; Khan, Abdul Nasir; Computer Engineering
Due to the distributed nature of Denial-of-Service attacks, it is tremendously challenging to identify such malicious behavior using traditional intrusion detection systems in Wireless Sensor Networks (WSNs). In the current paper, a bio-inspired method is introduced, namely the cooperative-based fuzzy artificial immune system (Co-FATS). It is a modular-based defense strategy derived from the danger theory of the human immune system. The agents synchronize and work with one another to calculate the abnormality of sensor behavior in terms of context antigen value (CAV) or attackers and update the fuzzy activation threshold for security response. In such a multi-node circumstance, the sniffer module adapts to the sink node to audit data by analyzing the packet components and sending the log file to the next layer. The fuzzy misuse detector module (FMDM) integrates with a danger detector module to identify the sources of danger signals. The infected sources are transmitted to the fuzzy Q-learning vaccination modules (FQVM) in order for particular, required action to enhance system abilities. The Cooperative Decision Making Modules (Co-DMM) incorporates danger detector module with the fuzzy Q-learning vaccination module to produce optimum defense strategies. To evaluate the performance of the proposed model, the Low Energy Adaptive Clustering Hierarchy (LEACH) was simulated using a network simulator. The model was subsequently compared against other existing soft computing methods, such as fuzzy logic controller (FLC), artificial immune system (AIS), and fuzzy Q-learning (FQL), in terms of detection accuracy, counter-defense, network lifetime and energy consumption, to demonstrate its efficiency and viability. The proposed method improves detection accuracy and successful defense rate performance against attacks compared to conventional empirical methods. (C) 2014 Elsevier Ltd. All rights reserved.
Citation - Scopus: 0
An Evaluation on Developer's Perception of Xml Schema Complexity Metrics for Web Services
(2013) Crasso,M.; Mateos,C.; Coscia,J.L.O.; Zunino,A.; Misra,S.; Computer Engineering
Undoubtedly, the Service-Oriented Computing (SOC) is not an incipient computing paradigm anymore, while Web Services technologies is now a very mature stack of technologies. Both have been steadily gaining maturity as their adoption in the software industry grew. Accordingly, several metric suites for assessing different quality attributes of Web Services have been recently proposed. In particular, researchers have focused on measuring services interfaces descriptions, which like any other software artifact, have a measurable size, complexity and quality. This paper presents a study that assesses human perception of some recent services interfaces complexity metrics (Basci and Misra's metrics suite). Empirical evidence suggests that a service interface that it is not complex for a software application, in terms of time and space required to analyze it, will not be necessarily well designed, in terms of best practices for designing Web Services. A Likert-based questionnaire was used to gather individuals opinions about this topic. © 2013 Springer-Verlag Berlin Heidelberg.
Citation - WoS: 31
Citation - Scopus: 35
Large Scale Community Detection Using a Small World Model
(Mdpi, 2017) Behera, Ranjan Kumar; Rath, Santanu Kumar; Misra, Sanjay; Damasevicius, Robertas; Maskeliunas, Rytis; Computer Engineering
In a social network, small or large communities within the network play a major role in deciding the functionalities of the network. Despite of diverse definitions, communities in the network may be defined as the group of nodes that are more densely connected as compared to nodes outside the group. Revealing such hidden communities is one of the challenging research problems. A real world social network follows small world phenomena, which indicates that any two social entities can be reachable in a small number of steps. In this paper, nodes are mapped into communities based on the random walk in the network. However, uncovering communities in large-scale networks is a challenging task due to its unprecedented growth in the size of social networks. A good number of community detection algorithms based on random walk exist in literature. In addition, when large-scale social networks are being considered, these algorithms are observed to take considerably longer time. In this work, with an objective to improve the efficiency of algorithms, parallel programming framework like Map-Reduce has been considered for uncovering the hidden communities in social network. The proposed approach has been compared with some standard existing community detection algorithms for both synthetic and real-world datasets in order to examine its performance, and it is observed that the proposed algorithm is more efficient than the existing ones.

Mısra, Sanjay

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Scholarly Output

189

Articles

120

Citation Count

2203

Supervised Theses

1

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