Preferred Language
Articles
/
YxeTP48BVTCNdQwCGWYB
Multi-Resolution Hierarchical Structure for Efficient Data Aggregation and Mining of Big Data
...Show More Authors

Big data analysis is essential for modern applications in areas such as healthcare, assistive technology, intelligent transportation, environment and climate monitoring. Traditional algorithms in data mining and machine learning do not scale well with data size. Mining and learning from big data need time and memory efficient techniques, albeit the cost of possible loss in accuracy. We have developed a data aggregation structure to summarize data with large number of instances and data generated from multiple data sources. Data are aggregated at multiple resolutions and resolution provides a trade-off between efficiency and accuracy. The structure is built once, updated incrementally, and serves as a common data input for multiple mining and learning algorithms. Data mining algorithms are modified to accept the aggregated data as input. Hierarchical data aggregation serves as a paradigm under which novel …

Scopus Crossref
View Publication
Publication Date
Tue Dec 01 2015
Journal Name
Journal Of Engineering
Data Aggregation in Wireless Sensor Networks Using Modified Voronoi Fuzzy Clustering Algorithm
...Show More Authors

Data centric techniques, like data aggregation via modified algorithm based on fuzzy clustering algorithm with voronoi diagram which is called modified Voronoi Fuzzy Clustering Algorithm (VFCA) is presented in this paper. In the modified algorithm, the sensed area divided into number of voronoi cells by applying voronoi diagram, these cells are clustered by a fuzzy C-means method (FCM) to reduce the transmission distance. Then an appropriate cluster head (CH) for each cluster is elected. Three parameters are used for this election process, the energy, distance between CH and its neighbor sensors and packet loss values. Furthermore, data aggregation is employed in each CH to reduce the amount of data transmission which le

... Show More
View Publication Preview PDF
Publication Date
Sun Jan 01 2023
Journal Name
Aip Conference Proceedings
Mining categorical Covid-19 data using chi-square and logistic regression algorithms
...Show More Authors

View Publication Preview PDF
Scopus Crossref
Publication Date
Wed Jan 01 2020
Journal Name
Journal Of Southwest Jiaotong University
IMPROVED STRUCTURE OF DATA ENCRYPTION STANDARD ALGORITHM
...Show More Authors

The Internet is providing vital communications between millions of individuals. It is also more and more utilized as one of the commerce tools; thus, security is of high importance for securing communications and protecting vital information. Cryptography algorithms are essential in the field of security. Brute force attacks are the major Data Encryption Standard attacks. This is the main reason that warranted the need to use the improved structure of the Data Encryption Standard algorithm. This paper proposes a new, improved structure for Data Encryption Standard to make it secure and immune to attacks. The improved structure of Data Encryption Standard was accomplished using standard Data Encryption Standard with a new way of two key gene

... Show More
Publication Date
Sat Jul 01 2017
Journal Name
2017 Computing Conference
Protecting a sensitive dataset using a time based password in big data
...Show More Authors

View Publication
Crossref (1)
Crossref
Publication Date
Tue Jun 01 2021
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Improved Certificate-Based Encryption Scheme in the Big Data: Combining AES and (ECDSA – ECDH)
...Show More Authors

      Big data usually running in large-scale and centralized key management systems. However, the centralized key management systems are increasing the problems such as single point of failure, exchanging a secret key over insecure channels, third-party query, and key escrow problem. To avoid these problems, we propose an improved certificate-based encryption scheme that ensures data confidentiality by combining symmetric and asymmetric cryptography schemes. The combination can be implemented by using the Advanced Encryption Standard (AES) and Elliptic Curve Diffie-Hellman (ECDH). The proposed scheme is an enhanced version of the Certificate-Based Encryption (CBE) scheme and preserves all its advantages. However

... Show More
View Publication Preview PDF
Crossref (2)
Crossref
Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Intelligent Systems
A study on predicting crime rates through machine learning and data mining using text
...Show More Authors
Abstract<p>Crime is a threat to any nation’s security administration and jurisdiction. Therefore, crime analysis becomes increasingly important because it assigns the time and place based on the collected spatial and temporal data. However, old techniques, such as paperwork, investigative judges, and statistical analysis, are not efficient enough to predict the accurate time and location where the crime had taken place. But when machine learning and data mining methods were deployed in crime analysis, crime analysis and predication accuracy increased dramatically. In this study, various types of criminal analysis and prediction using several machine learning and data mining techniques, based o</p> ... Show More
View Publication
Scopus (9)
Crossref (2)
Scopus Clarivate Crossref
Publication Date
Sat Jan 01 2011
Journal Name
International Journal Of Data Analysis Techniques And Strategies
A class of efficient and modified testimators for the mean of normal distribution using complete data
...Show More Authors

View Publication
Scopus (9)
Crossref (2)
Scopus Crossref
Publication Date
Tue Jan 01 2019
Journal Name
Journal Of Southwest Jiaotong University
Recognizing Job Apathy Patterns of Iraqi Higher Education Employees Using Data Mining Techniques
...Show More Authors

Psychological research centers help indirectly contact professionals from the fields of human life, job environment, family life, and psychological infrastructure for psychiatric patients. This research aims to detect job apathy patterns from the behavior of employee groups in the University of Baghdad and the Iraqi Ministry of Higher Education and Scientific Research. This investigation presents an approach using data mining techniques to acquire new knowledge and differs from statistical studies in terms of supporting the researchers’ evolving needs. These techniques manipulate redundant or irrelevant attributes to discover interesting patterns. The principal issue identifies several important and affective questions taken from

... Show More
View Publication
Crossref (1)
Crossref
Publication Date
Fri Jan 01 2010
Journal Name
International Journal Of Advanced Intelligence Paradigms
Assessing IRPS as an efficient pairwise test data generation strategy
...Show More Authors

View Publication
Scopus (10)
Crossref (9)
Scopus Crossref
Publication Date
Wed Feb 06 2013
Journal Name
Eng. & Tech. Journal
A proposal to detect computer worms (malicious codes) using data mining classification algorithms
...Show More Authors

Malicious software (malware) performs a malicious function that compromising a computer system’s security. Many methods have been developed to improve the security of the computer system resources, among them the use of firewall, encryption, and Intrusion Detection System (IDS). IDS can detect newly unrecognized attack attempt and raising an early alarm to inform the system about this suspicious intrusion attempt. This paper proposed a hybrid IDS for detection intrusion, especially malware, with considering network packet and host features. The hybrid IDS designed using Data Mining (DM) classification methods that for its ability to detect new, previously unseen intrusions accurately and automatically. It uses both anomaly and misuse dete

... Show More