http://localhost:80/xmlui/handle/123456789/693 2026-04-29T08:48:25Z 2026-04-29T08:48:25Z ZAMAN, SAKHI SIRAJ-UL-ISLAM http://localhost:80/xmlui/handle/123456789/828 2019-11-04T07:16:24Z 2016-01-01T00:00:00Z

Title: Numerical Approximation of Rapidly Oscillatory Bessel Integral Transforms Authors: ZAMAN, SAKHI; SIRAJ-UL-ISLAM Abstract: We present a new procedure of Levin type which is based on Gaussian radial basis function for evaluation of rapidly oscillating integrals that contains first kind of the Bessel function 􀜬􀯩(􀟱􀝔). Multi-resolution quadrature rules like hybrid and Haar functions are used in the context of Bessel oscillatory integrals as well. Numerical test problems are solved to verify the accuracy and efficiency of the new methods.

2016-01-01T00:00:00Z ABID, SARISH MANZOOR, BASHARAT ASLAM, WAQAR RAZAQ, SAFEENA http://localhost:80/xmlui/handle/123456789/827 2019-11-04T07:15:48Z 2016-01-01T00:00:00Z

Title: Comparative Analysis of Machine Learning Algorithms for Binary Classification SARISH Authors: ABID, SARISH; MANZOOR, BASHARAT; ASLAM, WAQAR; RAZAQ, SAFEENA Abstract: Machine learning algorithms are applied in all domains to achieve classification tasks. Machine Learning is applicable to several real life problems. Aim of this paper is highly accurate predictions in test data sets using machine learning methods and comparison of these methods to select appropriate method for a particular data set for binary classifications. Three machine learning methods Artificial Neural Network (Multi-Layer Perceptron with Back Propagation Neural Network), Support Vector Machine and K-Nearest Neighbor are used in this research work. The data sets are taken from UCI website. A comparative study is carried out to evaluate the performance of the classifiers using statistical measures e.g. accuracy, specificity and sensitivity. These results are also compared with previous studies. Experimental outcomes show that the Artificial Neural Network method provides better performance, and it is strongly suggested that the Multi-Layer Perceptron with Back Propagation Neural Network method is reasonably operational for the task of binary classification followed by Support Vector Machine and K-Nearest Neighbor.

2016-01-01T00:00:00Z SIDDIQI, MURTAZA AHMED MUGHERI, AZIZ OAD, KANWAL http://localhost:80/xmlui/handle/123456789/826 2019-11-04T07:15:16Z 2016-01-01T00:00:00Z

Title: Advance Persistent Threat Defense Techniques: A Review Authors: SIDDIQI, MURTAZA AHMED; MUGHERI, AZIZ; OAD, KANWAL Abstract: The evolution of internet in the age of information is very rapid. With the rapid development of the internet, significance of privacy and security is also becoming a key concern. This growing security concern is not only limited to multinational organizations and government’s high value data, but also for the mass users. During the last few years, there have been a number of network breaches with aims of espionage or sabotage, using an advanced and lethal methodology known as Advanced Persistent Threat. Keeping in view the damage done by such attacks, this paper based on literature review is intended to provide readers with intensive knowledge of an APT attack with its common phases. Later sections of the paper highlights the existing security methods currently in use or proposed by different researchers and security organizations to counter APT attacks. Statistical data on known APT attacks conducted over the last few years is also included in the paper to give the readers a clear idea of devastation caused by APT attacks. At the end of the paper conclusion and future work is emphasized, which include the crucial steps that can be employed to fight against APT attacks. Data analysed in this paper is extracted from annual reports published by well-known security implementation groups and reports released by organizations that have been targeted or victim of APT attacks.

2016-01-01T00:00:00Z AHMAD, MUHAMMAD RIZWAN SALEEM, YASIR ASGHAR, SARFRAZ http://localhost:80/xmlui/handle/123456789/825 2019-11-04T07:14:18Z 2016-01-01T00:00:00Z

Title: A Study of Issues and Challenges in Cloud Computing Authors: AHMAD, MUHAMMAD RIZWAN; SALEEM, YASIR; ASGHAR, SARFRAZ Abstract: Information technology is growing precipitately that is increasingly changing every aspect of our life. Cloud Computing is a growing technology for delivering services through internet. It is a technology archetype that helps businesses and individuals to share various services in a consistent and cost-effective manner. In a cloud computing environment, one works with data and applications that are maintained and stored on shared machines that exists in a web-based environment rather than physically located in the home of a user or a corporate environment. This paper attempts to investigate the crucial threats and issues faced in cloud computing and to have better understanding of it along with a glimpse of challenges.

2016-01-01T00:00:00Z