Prof. Mona Nasr

Helwan University, Faculty of Computers and Information, Faculty Member

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Prof. Nasr is a Professor at Information Systems Department, Faculty of Computers and Artificial Intelligence, Helwan University, Prof. Mona held many positions such as (Chief Information Officer (CIO) for Helwan University HU, Scientific Computing Center Manager at HU, Head of Information Systems Department at Faculty of Computers and Artificial Intelligence HU, Vice Dean for Community Service and Environmental Development at FCAI-HU, Vice Dean at the Canadian International College CIC, El Sheikh Zayed Campus).

She received the M.Sc. degree in information systems from Faculty of Computers and Artificial Intelligence, Helwan University, Egypt, 2000. Ph.D. degree in Information Systems from Faculty of Computers and Artificial Intelligence, Helwan University, Egypt, 2006.

Prof. Nasr is a well-known speaker with a charismatic presence at academic conferences and seminars, university, and public lectures and radio and television programs in his area of expertise. She published many articles in international journals and conferences and she is an active reviewer for numerous international journals.
Prof. Nasr attended Digital Transformation & e-Governance Course(16th Nov. till 9th Dec 2021, Tallinn, Estonia),Organized by e-Governance Academy eGA , UNDP, Lebanon in cooperation with the Estonian e-Governance Academy, sharing the best practices on e-Governance and digitization in general.
Prof. Nasr attended Teaching the Teacher TTT Program in Artificial Intelligence from EPITA , School of Engineering and Computer Science (EPITA-Paris, France) Nov- Dec 2020.
she is a member in many other societies such as (IEDRC, IACSIT, MJC, IAOE, TWOWS/OWSD, CSTA, ArabWIC ABI,...etc).

Prof. Nasr Awarded: -
Selected from the top 50 women achievers in the middle East in 2021 supporting their organizations in the journey for business and Digital Transformation. IDC's list of Female Achievers 2021 in Category "CIO Pioneers" (Women Transforming Technology summit 7th Oct. 2021, Middle East), UAE, Dubai.

Selected from the Top 10 Women in Technology and Business, for female business and IT leaders who have positively impacted the business outcomes, work cultures, and levels of innovation required to drive significant improvements in financial performance @IDC CIO Summit Egypt, 14th June 2021
African Women in Technology Role Model from AFCHIX, 2017
A trophy (The Best Senior Level STEM Executive 2015) from Meera Kaul Foundation. The foundation focuses on women and women led enterprise in STEM (Science, Technology, Engineering, and Mathematics) in North America, Eastern Europe, and selected countries in Middle East, Africa, China and India.
Full fellowship from Bibliotheca Alexandrina(BA) in cooperation with The German Academic Exchange Service through the DAAD Kairo, Alexandria, Egypt.
Full fellowship from Bibliotheca Alexandrina(BA) in cooperation with the Arab Regional Office for the World Academy of Science for the advancement of science in developing countries (TWAS-ARO), Alexandria, Egypt.
Full fellowship from The Cyprus Institute for participating in the Third SESAME-LinkSCEEM Third Cross-sectional HPC Workshop, Cairo, Egypt.
Full fellowship from The Cyprus Institute for participating in the Second SESAME-LinkSCEEM Summer School, Allan-Jordan.
Full fellowship from The Cyprus Institute for participating in the Second LinkSCEEM/V-MUST, Alexandria, Egypt.
Phone: 002-01001779619
Address: Cairo, Egypt

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Papers by Prof. Mona Nasr

Formal security analysis of lightweight authenticated key agreement protocol for IoT in cloud computing

Indonesian Journal of Electrical Engineering and Computer Science, 2021

The internet of things (IoT) and cloud computing are evolving technologies in the information tec... more The internet of things (IoT) and cloud computing are evolving technologies in the information technology field. Merging the pervasive IoT technology with cloud computing is an innovative solution for better analytics and decision-making. Deployed IoT devices offload different types of data to the cloud, while cloud computing converges the infrastructure, links up the servers, analyzes information obtained from the IoT devices, reinforces processing power, and offers huge storage capacity. However, this merging is prone to various cyber threats that affect the IoT-Cloud environment. Mutual authentication is considered as the forefront mechanism for cyber-attacks as the IoT-Cloud participants have to ensure the authenticity of each other and generate a session key for securing the exchanged traffic. While designing these mechanisms, the constrained nature of the IoT devices must be taken into consideration. We proposed a novel lightweight protocol (Light-AHAKA) for authenticating IoT-Cloud elements and establishing a key agreement for encrypting the exchanged sensitive data was proposed. In this paper, the formal verification of (Light-AHAKA) was presented to prove and verify the correctness of our proposed protocol to ensure that the protocol is free from design flaws before the deployment phase. The verification is performed based on two different approaches, the strand space model and the automated validation of internet security protocols and applications (AVISPA) tool.

A New Lightweight Authenticated Key Agreement Protocol for IoT in Cloud Computing

Journal of Engineering Science and Technology, 2021

Internet of Things (IoT) is a pervasive technology that grants authorized users the ability to co... more Internet of Things (IoT) is a pervasive technology that grants authorized users the ability to communicate with sensors and devices. This technology connects millions of devices, exchanges sensitive information with users, and off-loads classified information to the cloud. This technology is evolving to encompass
time-critical applications. In IoT-time critical applications, legitimate users may require accessing the real-time data directly from the IoT devices rather than requesting data stored in the cloud. These IoT devices are prone to distinct threats and security breaches. Authentication mechanisms are substantial to control access to IoT devices in cloud computing, as authorized users and IoT devices should ensure the authenticity of each other and generate a session key for securing the exchanged traffic. As different IoT devices are resourceconstrained, traditional security mechanisms will not be appropriate for these
devices, as they need considerable computational power and consume excessive energy. Cryptographic researchers are exerting a worthy effort to develop lightweight security mechanisms to cope with resource-constrained IoT systems. In this paper, we propose a novel lightweight protocol (LightAHAKA) for authenticating IoT-cloud elements and establishing a key agreement for encrypting the exchanged sensitive data. Security analysis of the (Light-AHAKA) is carried out to assure the protocol immunity to different security attacks.

A Survey on Classification Analysis for Cancer Genomics: Limitations and Novel Opportunity in the Era of Cancer Classification and Target Therapies

ANNALS OF TROPICAL MEDICINE AND HEALTH, 2020

Advanced machine learning approaches are qualified for recognizing the too composite patterns in ... more Advanced machine learning approaches are qualified for recognizing the too composite patterns in the massive datasets.
We provide a perspective technical survey analysis in machine learning (ML), and deep learning (DL) approaches for genome analysis. It's quickly rising applications related to cancer diseases such as cancer diagnosis or subtypes of cancer through omics input data. It discusses effective approaches in the fields of genomics regulatory, pathogenicity, and variant calling. Moreover, the representation of ML's potential benefits due to the several technological platforms involved in its
diagnosis, prognosis, and treatment. We concentrate on the most up-to-date knowledge of cancer classification models, targeted therapy, and define how genetic mutations inspire targeted therapy's responsiveness and highlight the different related issues in this era of precision medicine. Finally, we disuse limitations of the different approaches and hopeful ways of upcoming research in targeted therapy.

Face Recognition System

Int. J. Advanced Networking and Applications, 2020

One of the modern technological techniques in practical application will be discussed in this pap... more One of the modern technological techniques in practical application will be discussed in this paper in broaden manner will be discussed on a large scale.This technique, which is considered a means of technological security to keep personal data away from the hands of snoopers and spies, this technology has occupied the minds of developers in recent years who have ensured its development continuously is a facial recognition technology.

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Natural Language Processing: Text Categorization and Classifications

by Prof. Mona Nasr and Mina Atef

Int. J. Advanced Networking and Applications, 2020

There are huge data from unstructured text obtained daily from various resources like emails, twe... more There are huge data from unstructured text obtained daily from various resources like emails, tweets, social media posts, customer comments, reviews, and reports in many different fields, etc. Unstructured text data can be analyzed to obtain useful information that will be used according to the purpose of the analysis also the domain that the data was obtained from it. Because of the huge amount of the data the human manually analysis of these texts is not possible, so we have to automatic analysis. The topic analysis is the Natural Language Processing (NLP) technology that organizes and understands large collections of text data, by identifying the topics, finding patterns and semantic. There two common approaches for topic analysis, topic modeling, and topic classification each approach has different algorithms to apply that will be discussed.

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A Survey of Psychological Personality Classification Approaches

Future Computing and Informatics Journal (FCIJ),Elsevier,Volume 4, Issue 2, PP 79-89, 2019, 2019

Online social networks (OSNs) have become essential ways for users to socially share information ... more Online social networks (OSNs) have become essential ways for users to socially share information and feelings, communicate, and thoughts with others through online social networks. Online social networks such as Twitter and Facebook are some of the most common OSNs among users. Users’ behaviors on social networks aid researchers for detecting and understanding their online behaviors and personality traits. Personality detection is one of the new difficulties in social networks. Machine learning techniques are used to build models for understanding personality, detecting personality traits, and classifying users into different kinds through user generated content based on different features and measures of psychological models such as PEN (Psychoticism, Extraversion, and Neuroticism) model, DISC (Dominance, Influence, Steadiness, and Compliance) model, and the Big-five model (Openness, Extraversion, Consciousness, Agreeableness, and Neurotic) which is the most accepted model of personality. This survey discusses the existing works on psychological personality classification.

A Comparative Study for Methodologies and Algorithms Used In Colon Cancer Diagnoses and Detection

Future Computing and Informatics Journal (FCIJ), ElSevier, Volume 4, Issue 2, PP 113-128, 2019, 2019

Colon cancer is also referred to as colorectal cancer, a kind of cancer that starts with colon da... more Colon cancer is also referred to as colorectal cancer, a kind of cancer that starts with colon damage to the large intestine in the last section of the digestive tract. Elderly people typically suffer from colon cancer, but this may occur at any age.It normally starts as little, noncancerous (benign) mass of cells named polyps that structure within the colon. After a period of time these polyps can turn into advanced malignant tumors that attack the human body and some of these polyps can become colon cancers. So far, no concrete causes have been identified and the complete cancer treatment is very difficult to be detected by doctors in the medical field. Colon cancer often has no symptoms in early stage so detecting it at this stage is curable but colorectal cancer diagnosis in the final stages (stage IV), gives it the opportunity to spread to different pieces of the body, difficult to treat successfully, and the person's chances of survival are much lower. False diagnosis of colorectal cancer which mean wrong treatment for patients with long-term infections and they are suffering from colon cancer this causing the death for these patients. Also, the cancer treatment needs more time and a lot of money. This paper provides a comparative study for methodologies and algorithms used in colon cancer diagnoses and detection this can help for proposing a prediction for risk levels of colon cancer disease using CNN algorithm of the deep learning (Convolutional Neural Networks Algorithm).

Detection outliers on internet of things using big data technology

Egyptian Informatics Journal, 2020

Internet of Things (IoT) is a fundamental concept of a new technology that will be promising and ... more Internet of Things (IoT) is a fundamental concept of a new technology that will be promising and significant in various fields. IoT is a vision that allows things or objects equipped with sensors, actuators, and processors to talk and communicate with each other over the internet to achieve a meaningful goal. Unfortunately, one of the major challenges that affect IoT is data quality and uncertainty, as data volume increases noise, inconsistency and redundancy increases within data and causes paramount issues for IoT technologies. And since IoT is considered to be a massive quantity of heterogeneous networked embedded devices that generate big data, then it is very complex to compute and analyze such massive data. So this paper introduces a new model named NRDD-DBSCAN based on DBSCAN algorithm and using resilient distributed datasets (RDDs) to detect outliers that affect the data quality of IoT technologies. NRDD-DBSCAN has been applied on three different datasets of N-dimensions (2-D, 3-D, and 25-D) and the results were promising. Finally, comparisons have been made between NRDD-DBSCAN and previous models such as RDD-DBSCAN model and DBSCAN algorithm, and these comparisons proved that NRDD-DBSCAN solved the low dimensionality issue of RDD-DBSCAN model and also solved the fact that DBSCAN algorithm cannot handle IoT data. So the conclusion is that NRDD-DBSCAN proposed model can detect the outliers that exist in the datasets of N-dimensions by using resilient distributed datasets (RDDs), and NRDD-DBSCAN can enhance the quality of data exists in IoT applications and technologies.

E-PAYMENT SYSTEMS RISKS, OPPORTUNITIES, AND CHALLENGES FOR IMPROVED RESULTS IN E-BUSINESS

by Prof. Mona Nasr and Mohamed Hassan Nasr

International Journal of Intelligent Computing and Information Sciences, 2020

E-payment is the key function for any e-business as it is rising exponentially in today's busines... more E-payment is the key function for any e-business as it is rising exponentially in today's business world as e-business grows. E-payments made it easier for people to survive and helped them save a lot of money and time. Using various forms and devices, our payments are more exciting and convenient to press on your mobile phone and pay for your orders. In order to obtain better results in e-business, it must be linked to e-payments. E-payments have many systems and opportunities in the field of e-business, but it is facing many risks and challenges that need to be highlighted in order to find solutions to it. This paper presents an overview study for e-payments opportunities, challenges, and different risks for e-payments especially fraud as it is one of the most critical threats to the e-payments field and it is causing huge losses. Paper also discusses different types of e-payments, benefits, and the future of e-payment.

Benchmarking Meta-heuristic Optimization

Int. J. Advanced Networking and Applications, 2020

Solving an optimization task in any domain is a very challenging problem, especially when dealing... more Solving an optimization task in any domain is a very challenging problem, especially when dealing with nonlinear problems and non-convex functions. Many meta-heuristic algorithms are very efficient when solving nonlinear functions. A meta-heuristic algorithm is a problem-independent technique that can be applied to a broad range of problems. In this experiment, some of the evolutionary algorithms will be tested, evaluated, and compared with each other. We will go through the Genetic Algorithm, Differential Evolution, Particle Swarm Optimization Algorithm, Grey Wolf Optimizer, and Simulated Annealing. They will be evaluated against the performance from many points of view like how the algorithm performs throughout generations and how the algorithm's result is close to the optimal result. Other points of evaluation are discussed in depth in later sections.

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Realtime Multi-Person 2D Pose Estimation

by Prof. Mona Nasr and Adriana Mounir

Int. J. Advanced Networking and Applications, 2020

This paper explains how to detect the 2D pose of multiple people in an image. We use in this pape... more This paper explains how to detect the 2D pose of multiple people in an image. We use in this paper Part Affinity Fields for Part Association (It is non-parametric representation), Confidence Maps for Part Detection, Multi-Person Parsing using PAFs, Simultaneous Detection and Association, this method achieve high accuracy and performance regardless the number of people in the image. This architecture placed first within the inaugural COCO 2016 key points challenge. Also, this architecture exceeds the previous state-of-the-art result on the MPII Multi-Person benchmark, both in performance and efficiency.

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An Intelligent Approach to Mitigate Effects of Climate Change and Insects on Crops

by Prof. Mona Nasr and Ayman M O H A M E D Mohamed

International Journal of Computer Science and Information Security, IJCSIS, 2020

Climate change is a major challenge for agriculture and food security, Climate change may cause s... more Climate change is a major challenge for agriculture and food security, Climate change may cause sudden reductions in agricultural productivity. Egypt is considered as a one of the worst-weather countries which is affected by the climate change: including high rising temperatures, erratic rainfall, sandstorms and extreme heat. The production of the strategic crops will suffer from significant reduction from 10% to 60% by the middle of the century (2050) due to temperature increases. Intelligent Decision Support System IDSS provides the good solution to minimize the effects of climate change in an intelligent manner and provides the required solutions to successfully penetrate this highly competitive and regulatory challenging environment. These solutions depends on GIS to determine location and its properties, climate prediction model, knowledge base model in agricultural domain as plants, insects and diseases using domain expert knowledge extraction, data mining, machine learning and fuzzy logic to obtain a fast and high accuracy solutions.

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Efficiency Improvement Approach of Deep Web Data Extraction

2019 14th International Conference on Computer Engineering and Systems (ICCES), p214-221 Published at the IEEE Xplore® Digital Library: Conference Proceedings, 2020

Deep Web is an important topic of research. According to the deep web pages' complicated structur... more Deep Web is an important topic of research. According to the deep web pages' complicated structure, extracting content is a very challenging issue. In this paper a framework for efficiently discovery deep web data records is proposed. The proposed framework is able to perform crawling and fetching relevant pages related to user's text query. To retrieve the relevant pages this paper proposes a similarity method based on the improved weighting function (ITF-IDF). This framework utilizes the web page's visual features to obtain data records rather than analyze the source code of HTML. To accurately retrieve the data records, an approach called layout tree is exploited. The proposed framework uses Noise Filter (NSFilter) algorithm to eliminate all noise like header, footer, ads and unnecessary content. Data records are defined as a similar layout visual blocks. To cluster the visual blocks with similar layout, this paper proposes a method based on appearance similarity and similar shape and coordinate feature (SSC). The experiment results illustrate that the framework being proposed is better than previous data extraction works.

The Future of Internet of Things for Anomalies Detection using Thermography

by Dr. Amira H A S S A N Abed and Prof. Mona Nasr

The Future of Internet of Things for Anomalies Detection using Thermography, 2019

Abnormal temperature of human body is a natural extensive indicator of illness. Infrared thermogr... more Abnormal temperature of human body is a natural extensive indicator of illness. Infrared thermography (IRT) is a fast, non-invasive, non-contact and passive substitution to ordinary medical thermometers for monitoring and observation human body temperature. Aside from, IRT is able to chart body surface heat remotely. Last five decades testified a stationary development in thermal imaging cameras utilization to obtain relations between the thermal physiology and surface temperature. IRT has effectively used in diagnosis and detection of breast cancer, diabetes neuropathy and peripheral vascular disorders. It has been employed to detect issues related to gynecology, dermatology, heart, neonatal physiology, and brain imaging. With the advent of modern infrared cameras, data acquisition and processing techniques, it is now possible to have real time high resolution thermographic images, which is likely to surge further research in this field. The emergent technology known as the Internet of Things (IoT) has guided practitioners, physicians and researchers to design innovative solutions in different environments, particularly in medical and healthcare using smart sensors, computer networks and a remote server. This paper aims to propose IoT-enabled medical system enables diagnostics and detection for several medical anomalies remotely; in real-time and simultaneous depend on combination of IoT and Thermal Infrared imaging techniques. It will detect and diagnostics any abnormal and alert the user through IoT remotely and in real-time.

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Diabetes Disease Detection through Data Mining Techniques

by Dr. Amira H A S S A N Abed and Prof. Mona Nasr

Diabetes Disease Detection through Data Mining Techniques, 2019

Diabetes is a inveterate defect and disturbance resulted from metabolic conk out in carbohydrate ... more Diabetes is a inveterate defect and disturbance resulted from metabolic conk out in carbohydrate metabolism thus it has occupied a globally serious health problem. In general, the detection of diabetes in early stages can greatly has significant impact on the diabetic patients treatment in which lead to drive out its relevant side effects. Machine learning is an emerging technology that providing high importance prognosis and a deeper understanding for different clustering of diseases such as diabetes. And because there is a lack of effective analysis tools to discover hidden relationships and trends in data, so Health information technology has emerged as a new technology in health care sector in a short period by utilizing Business Intelligence 'BI' which is a data-driven Decision Support System. In this study, we proposed a high precision diagnostic analysis by using k-means clustering technique. In the first stage, noisy, uncertain and inconsistent data was detected and removed from data set through the preprocessing to prepare date to implement a clustering model. Then, we apply k-means technique on community health diabetes related indicators data set to cluster diabetic patients from healthy one with high accuracy and reliability results.

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The Future of Internet of Things for Anomalies Detection using Thermography

by Prof. Mona Nasr and Dr. Amira H A S S A N Abed

Int. J. Advanced Networking and Applications , 2019

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Applying Data Mining Techniques for Predicting Diseases

by Prof. Mona Nasr and Basant Ali

Int. J. Advanced Networking and Applications , 2019

The techniques of data mining are very popular of Diseases. The advancement in health analysis ha... more The techniques of data mining are very popular of Diseases. The advancement in health analysis has been improved by technical advances in computation, automation and data mining. Nowadays, data mining is getting used in a vast area .The Nature of the medical field is made with the knowledge wherever there's a spread of data but untapped during a correct. and thus, the foremost serious challenge facing this area is the quality of service provided which suggests to create the diagnose during a correct manner in a timely manner and supply acceptable medications to patients. Thus Health information technology has emerged as a replacement technology within the health care sector in a short amount by utilizing Business Intelligence 'BI' that could be a data-driven Decision Support System. The various techniques of data mining are used and compared during this analysis.

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Diabetes Disease Detection through Data Mining Techniques

Int. J. Advanced Networking and Applications , 2019

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An adaptive technique for cost reduction in cloud data centre environment

January 2019International Journal of Grid and Utility Computing , 2019

Cloud Business Intelligence

International Journal of Advanced Networking and Applications (IJANA), 2019

Using Business Intelligence in the cloud is considered a key factor for success in various fields... more Using Business Intelligence in the cloud is considered a key factor for success in various fields in 2018, about 66 percent of successful organizations in BI already using cloud. 86% of Cloud BI adopters choose Amazon AWS as their first choice, 82% choose Microsoft Azure, 66% choose Google Cloud, and 36% identify IBM Bluemix as their preferred provider of cloud BI services. In recent years, both Business Intelligence and cloud computing have undergone dramatic changes and advancements. The newest capabilities that these recent developments bring forth are introduced. In this paper the latest technologies in the field of Cloud (SaaS) BI is introduced. The paper shows also that many of the current problems in Cloud (SaaS) BI can be solved by enhance the performance and increase the use and acceptance of this technology. Many of the key characteristics of Business Intelligence systems tend to complement those of cloud computing systems and vice versa. Therefore, when integrated properly, these two technologies can be made to strengthen each other's advantages and eliminate each other's weaknesses.

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Prof. Mona Nasr

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