Enhanced classification of network traffic data captured by intrusion prevention systems

A common practice in modern computer networks is the deployment of Intrusion Prevention Systems (IPSs) for the purpose of identifying security threats. Such systems provide alerts on suspicious activities based on a predefined set of rules. These alerts almost always contain high percentages of false positives and false negatives, which may impede the efficacy of their use. Therefore, with the presence of high numbers of false positives and false negatives, the analysis of network traffic data can be ineffective for decision makers which normally require concise, and preferably, visual forms to base their decisions upon. Machine learning techniques can help extract useful information from large datasets. Combined with visualisation, classification could provide a solution to false alerts and text-based outputs of IPSs. This research developed two new classification techniques that outperformed the traditional classification methods in accurate classification of computer network traffic captured by an IPS framework. They are also highly effective. The main purpose of these techniques was the effective identification of malicious network traffic and this was demonstrated via extensive experimental evaluation (where many experiments were conducted and results are reported in this thesis). In addition, an enhancement of the principal component analysis (PCA) was presented as part of this study. This enhancement proved to outperform the classical PCA on classification of IPS data. Details of the evaluation and experiments are provided in this thesis. One of the classification methods described in this thesis achieved accuracy values of 98.51% and 99.76% on two computer network traffic dataset settings, whereas the Class-balanced Similarity Based Instance Transfer Learning (CB-SBIT) algorithm achieves accuracy values of 93.56% and 96.25% respectively on the same dataset settings. This means the proposed method outperforms the state-of-the-art algorithm. As for the PCA enhancement mentioned above, using its resulting principal components as inputs to classifiers leads to improved accuracy when compared to the classical PCA

MPKMS: a Matrix-based Pairwise Key Management Scheme for Wireless Sensor Networks

Due to the sensitivity of the Wireless Sensor Networks (WSN) applications and resource constraints, authentication and key management emerge as a challenging issue for WSN. In general, various approaches have been developed for the key management in WSN. This paper has come up with a new robust key pre-distribution scheme using random polynomial functions and matrix. This new proposed scheme significantly increases the storage efficiency and provides resilience to network against node capture by using random prime numbers, polynomial functions and matrix properties. The effectiveness of the scheme is demonstrated through a security analysis and comparison with the existing schemes

The Exact Solution of the Falling Body Problem in Three-Dimensions: Comparative Study

Very recently, the system of differential equations governing the three-dimensional falling body problem (TDFBP) has been approximately solved. The previously obtained approximate solution was based on the fact that the Earth’s rotation (ER) is quite slow and hence all high order terms of ω in addition to the magnitude ω2R were neglected, where ω is the angular velocity and R is the radius of Earth. However, it is shown in this paper that the ignorance of such magnitudes leads, in many cases, to significant errors in the estimated falling time and other physical quantities. The current results are based on obtaining the exact solutions of the full TDFBP-system and performing several comparisons with the approximate ones in the relevant literature. The obtained results are of great interest and importance, especially for other planets in the Solar System or exterior planets, in which ω and/or ω2R are of considerable amounts and hence cannot be ignored. Therefore, the present analysis is valid in analyzing the TDFBP near to the surface of any spherical celestial body

Mixed Neutral Caputo Fractional Stochastic Evolution Equations with Infinite Delay: Existence, Uniqueness and Averaging Principle

The aim of this article is to consider a class of neutral Caputo fractional stochastic evolution equations with infinite delay (INFSEEs) driven by fractional Brownian motion (fBm) and Poisson jumps in Hilbert space. First, we establish the local and global existence and uniqueness theorems of mild solutions for the aforementioned neutral fractional stochastic system under local and global Carathéodory conditions by using the successive approximations, stochastic analysis, fractional calculus, and stopping time techniques. The obtained existence result in this article is new in the sense that it generalizes some of the existing results in the literature. Furthermore, we discuss the averaging principle for the proposed neutral fractional stochastic system in view of the convergence in mean square between the solution of the standard INFSEEs and that of the simplified equation. Finally, the obtained averaging theory is validated with an example

A Damage-Independent Role for 53BP1 that Impacts Break Order and Igh Architecture during Class Switch Recombination

SummaryDuring class switch recombination (CSR), B cells replace the Igh Cμ or δ exons with another downstream constant region exon (CH), altering the antibody isotype. CSR occurs through the introduction of AID-mediated double-strand breaks (DSBs) in switch regions and subsequent ligation of broken ends. Here, we developed an assay to investigate the dynamics of DSB formation in individual cells. We demonstrate that the upstream switch region Sμ is first targeted during recombination and that the mechanism underlying this control relies on 53BP1. Surprisingly, regulation of break order occurs through residual binding of 53BP1 to chromatin before the introduction of damage and independent of its established role in DNA repair. Using chromosome conformation capture, we show that 53BP1 mediates changes in chromatin architecture that affect break order. Finally, our results explain how changes in Igh architecture in the absence of 53BP1 could promote inversional rearrangements that compromise CSR