Layered Approach Using Conditional Random Fields for Intrusion Detection

Intrusion detection faces a number of challenges; an intrusion detection system must reliably detect malicious activities in a network and must perform efficiently to cope with the large amount of network traffic. In this paper, we address these two issues of Accuracy and Efficiency using Conditional Random Fields and Layered Approach. We demonstrate that high attack detection accuracy can be achieved by using Conditional Random Fields and high efficiency by implementing the Layered Approach. Experimental results on the benchmark KDD '99 intrusion data set show that our proposed system based on Layered Conditional Random Fields outperforms other well-known methods such as the decision trees and the naive Bayes. The improvement in attack detection accuracy is very high, particularly, for the U2R attacks (34.8 percent improvement) and the R2L attacks (34.5 percent improvement). Statistical Tests also demonstrate higher confidence in detection accuracy for our method. Finally, we show that our system is robust and is able to handle noisy data without compromising performance.     

Differential regulation of redox proteins and chaperones in HbEβ-thalassemia erythrocyte proteome

Purpose: In (hemoglobin, Hb) HbEβ‐thalassemia, HbE (β‐26 Glu→Lys) interacts with β‐thalassemia to produce clinical manifestation of varying severity. This is the first proteomic effort to study changes in protein levels of erythrocytes isolated from HbEβ‐thalassemic patients compared to normal. Experimental design: We have used 2‐DE and MALDI‐MS/MS‐based techniques to investigate the differential proteome profiling of membrane and Hb‐depleted fraction of cytosolic proteins of erythrocytes isolated from the peripheral blood samples of HbEβ‐thalassemia patients and normal volunteers. Results: Our study showed that redox regulators such as peroxiredoxin 2, Cu‐Zn superoxide dismutase and thioredoxin and chaperones such as α‐hemoglobin stabilizing protein and HSP‐70 were upregulated in HbEβ‐thalassemia. We have also observed larger amounts of membrane associated globin chains and indications of disruption of spectrin‐based junctional complex in the membrane skeleton of HbEβ‐thalassemic erythrocytes upon detection of low molecular weight fragments of β‐spectrin and decrease in β‐actin and dematin content. Conclusion and clinical relevance: We have observed interesting changes in the proteomic levels of redox regulators and chaperons in the thalassemic hemolysates and have observed strong correlation or association of the extent of such proteomic changes with HbE levels. This could be important in understanding the role of HbE in disease progression and pathophysiology.     

Identifying and overcoming the challenges of implementing a project management office

With the ongoing challenge of successfully managing information technology (IT) projects, organizations are recognizing the need for greater project management discipline. For many organizations, this has meant ratcheting up project management skills, processes, and governance structures by implementing a project management office (PMO). While anecdotal evidence suggests that implementing a PMO can be quite difficult, few studies discuss the specific challenges involved, and how organizations can overcome them. To address this gap in existing knowledge, we conducted a Delphi study to (1) identify the challenges of implementing a PMO for managing IT projects, (2) rank these challenges in order of importance, (3) discover ways in which some organizations have overcome the top-ranked challenges, and (4) understand the role of PMO structure, metrics, and tools in the implementation of a PMO.We identified 34 unique challenges to implementing a PMO and refined this list to 13 challenges that our Delphi panelists considered most important. The top-three challenges were (1) rigid corporate culture and failure to manage organizational resistance to change, (2) lack of experienced project managers (PMs) and PMO leadership, and (3) lack of appropriate change management strategy. Through follow-up interviews with selected panelists, we identified a series of actions that can be taken to overcome these challenges including having a strong PMO champion, starting small and demonstrating the value of the PMO, obtaining support from opinion leaders, hiring an experienced program manager who understands the organization, bringing the most talented PMs into the PMO implementation team, adopting a flexible change management strategy, and standardizing processes prior to PMO implementation. The interviews were also used to better understand the role of PMO structure, metrics, and tools. In terms of PMO structure, we found that ‘light’ PMOs were more likely to be implemented successfully. Most organizations eschew formal metrics, instead relying on subjective indicators of PMO success. Lastly, it appears that PMO tools are difficult to implement unless a project management culture has been established.     

Learning Sparse Feature Representations Using Probabilistic Quadtrees and Deep Belief Nets

Learning sparse feature representations is a useful instrument for solving an unsupervised learning problem. In this paper, we present three labeled handwritten digit datasets, collectively called n-MNIST by adding noise to the MNIST dataset, and three labeled datasets formed by adding noise to the offline Bangla numeral database. Then we propose a novel framework for the classification of handwritten digits that learns sparse representations using probabilistic quadtrees and Deep Belief Nets. On the MNIST, n-MNIST and noisy Bangla datasets, our framework shows promising results and outperforms traditional Deep Belief Networks.     

DeepKnuckle: revealing the human identity

Multimedia Tools and Applications - Identification and authentication are ubiquitous questions which pan across various systems. In certain domains, they are of paramount importance. Like, security...     

Porous Titania Thin Films Grown by Anodic Oxidation for Hydrogen Sensors

Porous titanium dioxide (Titania) thin films were grown by anodic oxidation using high purity (99.7%) titanium foil in a dilute sulphuric acid (1 M) medium. The anodization process was carried out for 30 minutes with 20 mA/cm² and 50 mA/cm² current densities. The samples were characterized by XRD, SEM, and AFM techniques. It was found that the grown porous titania films were less sensitive to 500 ppm hydrogen in air ambient below 300°C; however, the sensitivity and response behavior of the film at 300°C are very much dependent on the growth conditions. Particularly, the films grown at current density 50 mA/cm² and 1 M acid concentration exhibited the lowest response time of 151 sec at 300°C.     

Nano and micro structural studies of thin films of ZnO

Zinc oxide thin films grown by sol–gel and RF sputtering methods have been characterized. The characterization techniques used involve ellipsometry, optical absorption, scanning tunneling microscopy, scanning and transmission electron microscopy. The films grown by sol–gel spin method which followed zinc acetate route exhibited a smoother texture than the films, which were deposited by using zinc nitrate route. The later type of films showed a dendritic character. Nano-structured fine grains of size ranging from 20 to 60 nm were observed with zinc nitrate precursor film. Individual grains show a sharp contrast with different facets and boundaries. Crystal planes and lattice parameters calculated by electron diffraction and X-ray diffraction are quite close and in agreement with the reported values in literature. Scanning tunneling microscopy has been used for measuring the average roughness of the surface and estimating the lattice constants. The STM studies of RF sputtered films, although showing a ZnO structure, exhibited a disturbed lattice. This was presumably due to the fact that after deposition the films were not annealed. Nanographs of 2D and 3D view of atomic positions of ZnO have been presented by using scanning tunneling microscopy.