Rehan Ashraf

National Textile University

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Toqeer Mahmood

National Textile University

Sohail Jabbar

Imam Mohammad ibn Saud Islamic University

Nouman Ali

Institute of Space Technology

Mudassar Ahmed

National Textile University

Bushra Zafar

Ayub Medical College

Muhammad Asif Habib

National Textile University

Mudassar Ahmad

National Textile University

Abid Jamil

National University of Computer and Emerging Sciences

Shehzad Khalid

Bahria University

Saba Rashid

University of Agriculture Faisalabad

Cooperative Institutions

National Textile University

University of Agriculture Faisalabad

University of Engineering and Technology Taxila

COMSATS University Islamabad

University of Engineering and Technology Lahore

University of Faisalabad

Government College University, Faisalabad

Lahore Garrison University

Riphah International University

National University of Sciences and Technology

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A Comprehensive Literature Review of Data Encryption Techniques in Cloud Computing and IoT Environment

Muhammad Sheraz Mehmood Muhammad Shahid Abid Jamil Rehan Ashraf Toqeer Mahmood

The internet of thing (IoT) is a network of interconnected physical devices, computer-based system, home-based application, automobiles and other things that are assigned with the unique IP address and devices may have the capability to share the data or information over networks without having any human to machine or human to human interaction. IoT devices generate a large volume of data is named Big data. Therefore, the concept of cloud computing was introduced to overcome storages issues on device. Cloud Computing is the latest emerging field which involves data processing and data storage to access remotely. However, the data on the internet is a risk. The IoT devices are generally small that consume less power and require less computational speed. As we know, the data encryption technique such as advanced encryption standard (AES), data encryption standard (DES) and triple advanced encryption standard (3DES) are complex algorithms. Therefore, these traditional encryption algorithms are not feasible for IoT devices. The issue mentioned above can be resolved by designing a lightweight encryption method to secure data transmission and communication in the IoT environment. The main objective of this research is to conduct a survey related to encryption techniques in cloud and IoT. This study summarize the encryption techniques, issues and variants, used for cloud and IoT. Furthermore, this study also presents the comparison of computational complexity of these techniques.

Disk encryption hardware

10.1109/icict47744.2019.9001945

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Citations (16)

UCM image dataset

Figshare (2018)

Bushra Zafar Rehan Ashraf Nouman Ali Mudassar Ahmed Sohail Jabbar

Source: http://weegee.vision.ucmerced.edu/datasets/landuse.html

10.6084/m9.figshare.6085976.v1

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Citations (0)

A color image encryption technique using exclusive-OR with DNA complementary rules based on chaos theory and SHA-2

Optik (2018)

Aqeel ur Rehman Xiaofeng Liao Rehan Ashraf Saleem Ullah Hueiwei Wang

Exclusive or

Bitwise operation

Key space

Scrambling

10.1016/j.ijleo.2018.01.064

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Citations (155)

Use and Abuse of Sorghum and Jequirity Plants in Cattle

International Journal of Agriculture and Biosciences (2023)

Authors Detail Saba Rashid Rehan Ashraf Fatima Jamil Samreen Sanawar

Sweet sorghum

10.47278/book.oht/2023.95

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Enhancements in data-recovery and re-transmit mechanisms of transmission control protocol enabled medical devices

Junaid Chaudhry Mudassar Ahmad Muhammad Asif Habib Rehan Ashraf Craig Valli

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MPMPA: A Mitigation and Prevention Model for Social Engineering Based Phishing attacks on Facebook

2021 IEEE International Conference on Big Data (Big Data) (2018)

Abid Jamil Kashif Asif Zikra Ghulam Muhammad Kashif Nazir Syed Mudassar Alam

The exponential increase in usage of the Internet can be seen in the present era. The use of social media and cyber-physical systems is rapidly increasing. Social Media platforms like Facebook have become an indispensable part of our lives. A large number of reported Facebook attacks have been observed in past few years. This study presents a novel model to detect and prevent the SEBPA (Social Engineering Based Phishing Attacks) on Facebook. Current research is first attempt to address SEBPA. For the Validation of proposed model four realistic scenarios have been deviced. The results suggest that the proposed model provides comprehensive coverage of nearly all occurrences of SEBPA. Moreover, the proposed model also prefigure the threatening situation to users with different colors during the validation process.

Phishing

Social engineering (security)

Internet users

10.1109/bigdata.2018.8622505

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Citations (32)

An effective hybrid framework for content based image retrieval (CBIR)

Multimedia Tools and Applications (2021)

Umer Ali Khan Ali Javed Rehan Ashraf

Content-Based Image Retrieval

10.1007/s11042-021-10530-x

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Citations (48)

Forensic analysis of copy-move forgery in digital images using the stationary wavelets

IEEE Conference Proceedings (2016)

Toqeer Mahmood Tabassam Nawaz Zahid Mehmood Khan Zakir Shah Mohsin

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15scene.rar

Figshare (2018)

Bushra Zafar Rehan Ashraf Nouman Ali Mudassar Ahmed Sohail Jabbar

Dataset Source: http://www-cvr.ai.uiuc.edu/ponce_grp/data/

10.6084/m9.figshare.6075608.v1

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Student Performance Prediction Using Algorithms of Data Mining

Abid Jamil Muhammad Ahsan Tahir Farooq Amir Hussain Rehan Ashraf

Data mining is mainly used to get information from a large amount of data. Process it to convert this information into understanding form predictions. Data minings algorithms have immense importance and chore in predictions. The data mining methods can uncover the unseen patterns (unsupervised), associations, and oddity from collected data. This information can enhance the decision-making processes for predictions. Data mining can be considered as a most suitable technology for predictions especially in predictions of students performance. The primary aim of this paper is to give a precise review on Applications of algorithms of data mining for prediction of students performance. In this paper, we presented a methodology in which we applied pre-processing on data to select best attributes in order to increase its accuracy then we applied different Algorithms to measure its accuracy and found out that Random Forest algorithm gives best results.

10.1109/icced.2018.00055

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Citations (5)