Ensuring Smartphone Security Through Real-Time Log Analysis

2021 ◽  
Author(s):  
Samruddhi Raut ◽  
S Raja Prabhu ◽  
Animesh Kumar Agrawal
Keyword(s):  
Real Time ◽  
Log Analysis ◽  
Smartphone Security

A Real-Time Log Analyzer Based on MongoDB

2014 ◽  
Vol 571-572 ◽  
pp. 497-501 ◽  
Author(s):  
Qi Lv ◽  
Wei Xie
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Performance Comparison ◽  
Log Analysis ◽  
Data Sets ◽  
Time Data ◽  
Real Time Analysis ◽  
Large Scale Data ◽  
Implementation Approach ◽  
And Performance

Real-time log analysis on large scale data is important for applications. Specifically, real-time refers to UI latency within 100ms. Therefore, techniques which efficiently support real-time analysis over large log data sets are desired. MongoDB provides well query performance, aggregation frameworks, and distributed architecture which is suitable for real-time data query and massive log analysis. In this paper, a novel implementation approach for an event driven file log analyzer is presented, and performance comparison of query, scan and aggregation operations over MongoDB, HBase and MySQL is analyzed. Our experimental results show that HBase performs best balanced in all operations, while MongoDB provides less than 10ms query speed in some operations which is most suitable for real-time applications.

XTemp: Event-driven Testing and Monitoring of Business processes

2011 ◽  
Author(s):  
Jacques Durand ◽  
Hyunbo Cho ◽  
Dale Moberg ◽  
Jungyub Woo
Keyword(s):  
Real Time ◽  
Business Processes ◽  
Log Analysis ◽  
Message Content ◽  
Sequence Of Events ◽  
Event Driven ◽  
Event Models

XML has proved to be a scalable archival format for messages of various kinds (e.g. email with MarkMail). It is also increasingly used as format of choice for several event models and taxonomies (XES, OASIS/SAF, CEE, XDAS) that need be both processable and human readable. As many eBusiness processes are also relying on XML for message content and/or protocol, there is a need to monitor and validate the messages and documents being exchanged as well as their sequences. XTemp is an XML vocabulary and execution language that is event-centric and intended for the analysis of sequence of events that represent traces of business processes. It is designed for both log analysis and real-time execution. It leverages XPath and XSLT.

scholarly journals File Log Server and Application in Server System Privacy

2020 ◽  
Vol 10 (1) ◽  
pp. 83-86
Keyword(s):  
Real Time ◽  
Optimal Choice ◽  
Log Analysis ◽  
Analysis System ◽  
To Receive ◽  
Server System

The article research on file log server and application off file log into operation as well as server system privacy. From that, authorities had conducted log analysis system of which ability of updating data according to real time, helping the log serve analysing find to be easier and more intuitive than Kibana, system helps server privacy be easier when detecting errors and warning immidiately, recognizing abnormal signatures help administrator to receive recommendations in the earliest and most precise way. Comparing to handmade or following to troubles, this is absolutle an optimal choice.

LogLens: A Real-Time Log Analysis System

2018 ◽  
Author(s):  
Biplob Debnath ◽  
Mohiuddin Solaimani ◽  
Muhammad Ali Gulzar Gulzar ◽  
Nipun Arora ◽  
Cristian Lumezanu ◽  
...  
Keyword(s):  
Real Time ◽  
Log Analysis ◽  
Analysis System

A Real-Time Well Site Log Analysis Application Using MRI Logs

2000 ◽  
Author(s):  
Prabhakar Aadireddy ◽  
George Coates
Keyword(s):  
Real Time ◽  
Log Analysis ◽  
Analysis Application

Implementation of Linux Apache Web Server Attack Detection Program through Real-time Log Analysis

2018 ◽  
Vol 24 (4) ◽  
pp. 190-197
Author(s):  
Jaeyeon Park ◽  
Songyeon Lee ◽  
Haeun Lee ◽  
Jongwoo Lee
Keyword(s):  
Real Time ◽  
Web Server ◽  
Attack Detection ◽  
Log Analysis ◽  
Detection Program

scholarly journals Predicting Service Outages using Tweets

2020 ◽  
Vol 8 (6) ◽  
pp. 421-429
Keyword(s):  
Real Time ◽  
Network Models ◽  
Extensive Study ◽  
Log Analysis ◽  
The Internet ◽  
Analysis Model ◽  
Neural Network Models ◽  
Log Data ◽  
Service Failures ◽  
Major Interest

Every user of the internet has high aspirations on its reliability, efficiency, productivity and in many other aspects of the same. Providing an uninterrupted service is of prime importance .The amount of data along with enormous number of residual traces is increasing rapidly and significantly. As a result, analysis of log data has profoundly influenced many aspects of researcher’s domains. Social media being integral part of the Internet, real time blogging services like Twitter are widely used due to their inherent nature of depicting social graph, propagating information and entire social dynamics. Content of tweets are of major interest to researchers as they reflect individuals experiences, real time events. Researchers have explored several applications of tweet analysis. One such application is detecting service outages through a myriad of messages posted by users regarding unavailability. Simple techniques are enough to extract key semantics from tweets as they are faster alerts for warning about service unavailability. Similarly, the outage mailing lists are text-based messages which are rich in semantic information about the underlying outages. Researchers find it a great challenge to automatically parse and process the data through NLP and text mining for service outage detection. An extensive study was conducted, aiming to explore the research directions and opportunities on log analysis, tweet analysis and outage mailing list analysis for the purpose of detecting and predicting service outages. A systematic- frame work is also articulated with a focus on all stages of analytics and we deliberately discussed potential research challenges & paths in the above said analysis. We introduce three major data analysis methods for diagnosing the causes of service failures , detecting service failures prematurely and predicting them. We analyze Syslogs (contain log data generated by the system) for detecting the cause of a failure by automatically learning over millions of logs and analyze the data of a social networking service (namely, Twitter and outage mails) to detect possible service failures by extracting failure related tweets, which account for less than a percent of all tweet in real time with high accuracy. Paper is an effort not only to detect outages but also to forecast them using twitter analysis based on time series and neural network models. We further propose a log analysis model for the same.

scholarly journals Construction of real-time monitoring system for Grid services based on log analysis at the Tokyo Tier-2 center

2018 ◽  
Author(s):  
Tomoe Kishimoto ◽  
Tetsuro Mashimo ◽  
Nagataka Matsui ◽  
Tomoaki Nakamura ◽  
Hiroshi Sakamoto
Keyword(s):  
Real Time ◽  
Monitoring System ◽  
Log Analysis ◽  
Tier 2 ◽  
Grid Services ◽  
Real Time Monitoring
Sign in / Sign up

Export Citation Format

Share Document