PIN∆LΞ : FUSE based Filesystem and Folder Syncer

In this digital world the data is organized by an entity called a file system. In desktop operating systems the file manager manages the local data. But with cloud technologies, reliance on online storage has increased since the past decade, which demands a hybrid file managing solution. The proposed file system using FUSE and application give the functionalities such as support for multiple cloud storages on local file manager, automated syncing of folders on different devices.

Automating Cataloging Workflow of Library Traditional Materials

This paper describes the author’s experience with automating and streamlining cataloging workflows of traditional materials at the Florida International University Libraries using a combination of various cataloging tools, including MarcEdit, a local batch loading tool GenLoad, as well as OCLC services including WorldCat Updates service, OCLC Connexion’s batch process searches and Local File Manager. The paper addresses the old cataloging processes of these traditional materials, the developing process of new workflows and their impacts, and concludes with lessons learned and success factors. The new workflows have improved work efficiency and metadata control. The hope is that this paper will be of interest to libraries desiring to automate their cataloging workflow of traditional materials.

Deep Dive into Directory Traversal and File Inclusion Attacks leads to Privilege Escalation

In Modern Web application directory traversal vulnerability that can potentially allow an attacker to view arbitrary files and some sensitive files. They can exploit identified vulnerabilities or misconfigurations to obtain root privileges. When building the web application, ensure that some arbitrary file is not publicly available via the production server. when an attacker can include. Traversal vulnerabilities this vulnerability exploits the dynamic file include a mechanism that exists in programming frameworks a local file inclusion happens when uncontrolled user input such as form values or headers for example are used to construct a file include paths. By exploiting directory traversal attacks in web servers, they can do anything and with chaining with code injection they can upload a shell into a web server and perform a website defacement attack. Path-traversal attacks take advantage of vulnerable Website parameters by including a URL reference to remotely hosted malicious code, allowing remote code execution and leads to privilege escalation attack.

Striped Data Analysis Framework

A columnar data representation is known to be an efficient way for data storage, specifically in cases when the analysis is often done based only on a small fragment of the available data structures. A data representation like Apache Parquet is a step forward from a columnar representation, which splits data horizontally to allow for easy parallelization of data analysis. Based on the general idea of columnar data storage, working on the [LDRD Project], we have developed a striped data representation, which, we believe, is better suited to the needs of High Energy Physics data analysis. A traditional columnar approach allows for efficient data analysis of complex structures. While keeping all the benefits of columnar data representations, the striped mechanism goes further by enabling easy parallelization of computations without requiring special hardware. We will present an implementation and some performance characteristics of such a data representation mechanism using a distributed no-SQL database or a local file system, unified under the same API and data representation model. The representation is efficient and at the same time simple so that it allows for a common data model and APIs for wide range of underlying storage mechanisms such as distributed no-SQL databases and local file systems. Striped storage adopts Numpy arrays as its basic data representation format, which makes it easy and efficient to use in Python applications. The Striped Data Server is a web service, which allows to hide the server implementation details from the end user, easily exposes data to WAN users, and allows to utilize well known and developed data caching solutions to further increase data access efficiency. We are considering the Striped Data Server as the core of an enterprise scale data analysis platform for High Energy Physics and similar areas of data processing. We have been testing this architecture with a 2TB dataset from a CMS dark matter search and plan to expand it to multiple 100 TB or even PB scale. We will present the striped format, Striped Data Server architecture and performance test results.

Elite Sequence Mining of Big Data using Hadoop Mapreduce

Text mining can deal with unstructured information. The proposed work extricates content from a PDF report is changed over to plain content configuration; at that point record is tokenized and serialized. Record grouping and classification is finished by discovering similarities between reports put away in cloud. Comparable archives are distinguished utilizing Singular Value Decomposition (SVD) strategy in Latent Semantic Indexing (LSI). At that point comparative records are assembled together as a group. A similar report is done between LFS (Local File System) and HDFS (HADOOP DISTRIBUTED FILE SYSTEM) as for rate and dimensionality. The System has been assessed on genuine records and the outcomes are classified.