Homomorphic Encryption Technologies for Cloud Computing

Khowla Khaliq,Muhammad Usman Bilal,Rimsha Khalid,Muhammad Waseem Iqbal,Muhammad Aqeel,Muhammad Adnan Khan 한국차세대컴퓨팅학회 2022 한국차세대컴퓨팅학회 학술대회 Vol.2022 No.10

Security is the major concern about data especially when we are storing it on the cloud and handing over it to the third force as the cloud resource supplier. We store our important data on the cloud in the shape of cipher-text but we have to convert it to plain text to perform calculations on it, which disturb its security including confidentiality, privacy, authentication, etc. so, our ultimate goal was to introduce some of the best encryption technique for securing data. In this regard, we have discussed Homomorphic Encryption (HE) in our paper. This survey is shown how HE could be used to make secure data on the cloud. HE is a technique in which data (plaintext) is converted in cipher-text (unreadable format). Users can perform required calculations on encrypted data without decrypting it and which does not affect the original form of data. This paper aims to focus on the fully homomorphic encryption technique. For this purpose, many approaches were analyzed and we suggested the best approach at the end of the paper.

Monitoring Effectiveness of Self-Managing System-A Review

Muhammad Usman Bilal,Muhammad Waseem Iqbal,Khowla Khaliq 한국차세대컴퓨팅학회 2022 한국차세대컴퓨팅학회 학술대회 Vol.2022 No.10

Software systems are widely spreading throughout and moving towards autonomic environment. Self-managing systems are designed so that they make adaptive decisions and are self-governing, self-directed and self-adapting. Self-managed systems are classified into basic requirements of self-configuration, self-protecting, self-healing and self-optimizing by IBM. Most of fact-findings has been taken out on implementation and benefits of self-managed systems. Some work on the evaluation of self-managed systems has been done. In this re-search work, seven metrics given by Claudia are applied on self-managed operating system proposed by previous researchers and induce a new monitoring module which will help in measuring the effectiveness of self-healing operating system.

Human hand gesture identification framework using SIFT and knowledge-level technique

Muhammad Haroon,Saud Altaf,Zia-ur- Rehman,Muhammad Waseem Soomro,Sofia Iqbal 한국전자통신연구원 2023 ETRI Journal Vol.45 No.6

In this study, the impact of varying lighting conditions on recognition and decision-making was considered. The luminosity approach was presented to increase gesture recognition performance under varied lighting. An efficient framework was proposed for sensor-based sign language gesture identification, including picture acquisition, preparing data, obtaining features, and recognition. The depth images were collected using multiple Microsoft Kinect devices, and data were acquired by varying resolutions to demonstrate the idea. A case study was designed to attain acceptable accuracy in gesture recognition under variant lighting. Using American Sign Language (ASL), the dataset was created and analyzed under various lighting conditions. In ASL-based images, significant feature points were selected using the scale-invariant feature transformation (SIFT). Finally, an artificial neural network (ANN) classified hand gestures using specified characteristics for validation. The suggested method was successful across a variety of illumination conditions and different image sizes. The total effectiveness of NN architecture was shown by the 97.6% recognition accuracy rate of 26 alphabets dataset with just a 2.4% error rate.

Usability Evaluation of Mobile Banking Applications in Digital Business as Emerging Economy

Hamid, Khalid,Iqbal, Muhammad Waseem,Muhammad, Hafiz Abdul Basit,Fuzail, Zubair,Ghafoor, Zahid Tabassum,Ahmad, Sana International Journal of Computer ScienceNetwork S 2022 International journal of computer science and netw Vol.22 No.2

Mobile Banking Applications (MBAPs) is one of the recent fads in mobile trading applications (Apps). MBAPs permit users to execute exchanges of money and many more whenever it might suit them; however, the primary issue for mobile banking Apps is usability. Hardly any investigation analyzes usability issues dependent on user's age, gender, exchanging accomplices, or experience. The purpose of this study is to determine the degree of usability issues, and experience of mobile banking users. The survey employs a quantitative method and performs user experiment on 240 participants with six different tasks on the application's interface. The post experiment survey is done with concerning participants. On the other hand, banking experts and Information Technology (IT) expert's group is also involved after the experiment. Expert's opinions about existing mobile banking Apps and suggestions for improving usability of MBAPs are collected through physical means (like questionnaire and interview) and online means like Google form. After that comparison of the opinions of users and experts about MBAPs is performed. The experimentation measures the tasks usability of various mobile banking apps with respect to its effectiveness, efficiency, trustfulness, learnability, memorability and satisfaction. The usability testing was led at different Universities and the outcomes acquired show that there are privacy and trust issues with their mobile banking apps. There is also a gap between users and experts which should be minimized by applying customized usability models, modes concept like other application software and also by adding complete features of banking in MBAPs. It will benefit mobile banking apps users, developers and usability engineers by providing user-friendly which are up to the mark of user's requirements.

Automatic Number Plate Recognition (ANPR) and Automatic License Plate Recognition (ALPR) System using ANN

Arif Wicaksono Septyanto,Muhammad Usman Bilal,Khowla Khaliq,Muhammad Waseem Iqbal,Rimsha Khalid,Irfan Ullah 한국차세대컴퓨팅학회 2022 한국차세대컴퓨팅학회 학술대회 Vol.2022 No.10

This research work demonstrates surveillance of traffic on roads and streets which is used by private companies and public organizations and government institutions. The primary purpose is the well-organized management of the transport system and public safety on highways and in civil areas. This paper used the technique to well-structured localize the LP and segmentation of captured images is done by the ALPR system. We explained the localization of license plates by using the integrated segmentation method. ALPR system contains several well-observed skeletons like security administration, parking, vehicle identification, streets and road activity management, schedule of toll collecting framework, and so forth. There are various frameworks are present which are used for License plate capturing. The most important part of the ALPR framework is the accurate confinement of different number plates, recognition, and segmentation. By ALPR systems we can easily identify the number of vehicle plates. ANPR system also plays a crucial part in vehicle plate capturing and identification. This system helps in monitoring and tracking automobiles. In this paper, we have tried numerous techniques for traffic control and monitoring purposes which are works based on various techniques and methodologies. But ANPR primarily did their work for accuracy and template matching of vehicle number plates.

Brain Tumor Prediction through Behavior Analysis of Cells Growth Using Machine Learning Techniques

Nouh Sabri Elmitwally,Muhammad Aqib Freed,Muhammad Waseem Iqbal,Aasma Ashraf,Farukh Muneem,Muhammad Aqeel 한국차세대컴퓨팅학회 2022 한국차세대컴퓨팅학회 학술대회 Vol.2022 No.10

Brain tumor is a very terrible disease. Brain tumor is caused by an increased number of cells. The presence of the skull layer around the brain makes it tough in studying the behavior of growth cells. It also raises the complication for the identification of disease. The initial discovery of a brain tumor is necessary to defend the survival of patients. Frequently, the brain cancer segmentation, and classification through the MRI images technique. Though, the radiologists are not providing actual visualization of brain cells in MRI images due to the irregular growth of cells, which forms of cells are growing rapidly and slow at some stage in brain tumors in the brain. So, automatic strategies are required to evaluate thoughts tumors exactly from MRI images in this research automatic, MRI brain tumors are used for classification, segmentation, and Behavior analysis of cell growth. The problem of visualization of cell growth and behavior analysis of brain cells is solved through MRI images which enhance the detection of cancer. To analyze the behavior of cell growth, which forms of cells are growing rapidly and slow at some stage in brain tumors, and analyze the area of images in which type of cells is affected. Single models are less efficient. We will use ensemble models which would also be helpful for better performance and accuracy.

BIG DATA Challenges, Tools and Techniques

Rimsha Khalid,Khowla Khaliq,Muhammad Waseem Iqbal,Muhammad Saleem Butt,Muhammad Usman Bilal 한국차세대컴퓨팅학회 2022 한국차세대컴퓨팅학회 학술대회 Vol.2022 No.10

Data is growing day by day all over the world. The word ''Big-data'' refers to a collection of data sets that are huge and complicated. The data is usually measured in Petabyte or Exabyte. Big data is one of the most talked-about topics in the field of IT. Its role in the future will be very considerable. The massive use of the internet, smartphones and social media has resulted in an increase in data. The usage of such gadgets and the internet not only increases the volume of data but also increases market velocity by allowing into to be moved and shared at light speed across optical fiber and wireless networks. Numerous problems arise as a result of the rapid creation of a large amount of data. So, we presented important concepts of Big-data in this paper. The basic purpose of this paper was to explore Big-data, challenges, and different tools related to it. We studied the previous work in which all writers have well-described big data, its challenges, and how to deal with them. And we have achieved our goal by providing a platform that explored big data challenges and tools for big data storage in detail. Moreover, we have compared these tools by identifying their parameters. In the future, we will find out solutions for these challenges. Furthermore, this paper will open new doors for researchers to explore Big-data, and develop solutions for challenges and unsolved research questions.

Agent-Based Context Awareness Platform For IoT-A Survey

Nouh Sabri Elmitwally,Rimsha Khalid,Muhammad Saleem Butt,Waseem Iqbal,Khowla Khaliq,Farukh Muneem 한국차세대컴퓨팅학회 2022 한국차세대컴퓨팅학회 학술대회 Vol.2022 No.10

Within cyber-physical networks, the Internet of Things is a futuristic idea, rich in promise as well as multifaceted requirements and implementation issues. Agent-Based Computing represents suitable and effective modeling, programming, and simulation paradigm for properly addressing them and fully supporting IoT system creation. Agent metaphors, principles, strategies, processes, and tools have all been used extensively in the development of IoT systems. In this paper, we have presented surveys and reports on the most recent contributions in this field.