OpenStack Training | OpenStack Tutorial For Beginners | OpenStack Certificati...Edureka!
This Edureka "OpenStack Training" tutorial will help you understand all the basics of OpenStack. We have demonstrated the OpenStack Deployment at PayPal using Cinder which will familiarize you with the Real-life applications of OpenStack. Below are the topics covered in this tutorial:
1. What is OpenStack?
2. OpenStack Architecture
3. OpenStack Components
4. PayPal Case Study
5. PayPal OpenStack System
6. EBay Implementation Model
7. Cinder Deployment at PayPal
Event: Passcamp, 07.12.2017
Speaker: Stefan Kirner
Mehr Tech-Vorträge: https://www.inovex.de/de/content-pool/vortraege/
Mehr Tech-Artikel: https://www.inovex.de/blog
Using ATTACK to Create Cyber DBTS for Nuclear Power PlantsMITRE - ATT&CKcon
From MITRE ATT&CKcon Power Hour December 2020
By Jacob Benjamin, Principal Industrial Consultant Dragos, INL, & University of Idaho
Design Basis Threat (DBT) is concept introduced by the Nuclear Regulatory Commission (NRC). It is a profile of the type, composition, and capabilities of an adversary. DBT is the key input nuclear power plants use for the design of systems against acts of radiological sabotage and theft of special nuclear material. The NRC expects its licensees, nuclear power plants, to demonstrate that they can defend against the DBT. Currently, cyber is included in DBTs simply as a prescribed list of IT centric security controls. Using MITRE’s ATT&CK framework, Cyber DBTs can be created that are specific to the facility, its material, or adversary activities.
OpenStack Training | OpenStack Tutorial For Beginners | OpenStack Certificati...Edureka!
This Edureka "OpenStack Training" tutorial will help you understand all the basics of OpenStack. We have demonstrated the OpenStack Deployment at PayPal using Cinder which will familiarize you with the Real-life applications of OpenStack. Below are the topics covered in this tutorial:
1. What is OpenStack?
2. OpenStack Architecture
3. OpenStack Components
4. PayPal Case Study
5. PayPal OpenStack System
6. EBay Implementation Model
7. Cinder Deployment at PayPal
Event: Passcamp, 07.12.2017
Speaker: Stefan Kirner
Mehr Tech-Vorträge: https://www.inovex.de/de/content-pool/vortraege/
Mehr Tech-Artikel: https://www.inovex.de/blog
Using ATTACK to Create Cyber DBTS for Nuclear Power PlantsMITRE - ATT&CKcon
From MITRE ATT&CKcon Power Hour December 2020
By Jacob Benjamin, Principal Industrial Consultant Dragos, INL, & University of Idaho
Design Basis Threat (DBT) is concept introduced by the Nuclear Regulatory Commission (NRC). It is a profile of the type, composition, and capabilities of an adversary. DBT is the key input nuclear power plants use for the design of systems against acts of radiological sabotage and theft of special nuclear material. The NRC expects its licensees, nuclear power plants, to demonstrate that they can defend against the DBT. Currently, cyber is included in DBTs simply as a prescribed list of IT centric security controls. Using MITRE’s ATT&CK framework, Cyber DBTs can be created that are specific to the facility, its material, or adversary activities.
After anomalous network traffic has been identified there can still be an abundance of results for an analyst to process. This presentation is for data scientist and network security professionals who want to increase the signal-to-noise.
Flare is a network analytic framework designed for data scientists, security researchers, and network professionals. Written in python, flare is designed for rapid prototyping and development of behavioral analytics. Flare comes with a collection of pre-built utility functions useful for performing feature extraction.
Using flare, we'll walk through identifying Domain Generation Algorithms (DGA) commonly used in malware and how to reduce the dataset to a manageable amount for security professionals to process.
We'll also explore flare's beaconing detection which can be used with the output from popular Intrusion Detection System (IDS) frameworks.
More information on flare can be found at https://github.com/austin-taylor/flare
www.austintaylor.io
Microsoft Azure Sentinel is a new Cloud native SIEM service with built-in AI for analytics that removes the cost and complexity of achieving a central and focused near real-time view of the active threats in your environment.
Falcon OverWatch Experts Hunt 24/7 To Stop Incidents Before They Become Breaches
Is your IT security team suffering from alert fatigue? For many organizations, chasing down every security alert can tax an already overburdened IT department, often resulting in a breach that might have been avoided. Adding to this challenge is an increase in sophisticated threats that strike so fast and frequently, traditional methods of investigation and response can’t offer adequate protection.
A new webcast from CrowdStrike, “Proactive Threat Hunting: Game-Changing Endpoint Protection Above and Beyond Alerting,” discusses why so many organizations are vulnerable to unseen threats and alert fatigue, and why having an approach that is both reactive and proactive is key. You’ll also learn about Falcon OverWatch™, CrowdStrike’s proactive threat hunting service that investigates and responds to threats immediately, dramatically increasing your ability to react before a damaging breach occurs.
Download the webcast slides to learn:
--How constantly reacting to alerts prevents you from getting ahead of the potentially damaging threats designed to bypass standard endpoint security
--Why an approach that includes proactive threat hunting, sometimes called Managed Detection and Response, is key to increasing protection against new and advanced threats
--How CrowdStrike Falcon OverWatch can provide 24/7 managed threat hunting, augmenting your security efforts with a team of cyber intrusion detection analysts and investigators who proactively identify and prioritize incidents before they become damaging breaches
Extended Detection and Response (XDR) An Overhyped Product Category With Ulti...Raffael Marty
Extended Detection and Response, or XDR for short, is one of the acronyms that are increasingly used by cybersecurity vendors to explain their approach to solving the cyber security problem. We have been spending trillions of dollars on approaches to secure our systems and data, with what success? Cybersecurity is still one of the biggest and most challenging areas that companies, small and large, are dealing with. XDR is another approach driven by security vendors to solve this problem. The challenge is that every vendor defines XDR slightly differently and makes it fit their own “challenge du jour” for marketing and selling their products.
In this presentation we will demystify the XDR acronym and put a working model behind it. Together, we will explore why XDR is a fabulous concept, but also discover that it’s nothing revolutionarily new. With an MSP lens, we will explore what the XDR benefits are for small and medium businesses and what it means to the security strategy of both MSPs and their clients. The audience will leave with a clear understanding of what XDR is, how the technology matters to them, and how XDR will ultimately help them secure their customers and enable trusted commerce.
Building an Intelligence-Driven Security Operations CenterEMC
This white paper describes how an intelligence-driven security operations center (SOC) improves threat detection and response by helping organizations use all available security-related information from both internal and external sources to detect hidden threats and even predict new ones.
Upgrade Your SOC with Cortex XSOAR & Elastic SIEMElasticsearch
Together, Cortex XSOAR and Elastic SIEM deliver a flexible and effective solution for today's security operations teams. Combining Cortex XSOAR's robust orchestration, automation, and case management capabilities with Elastic's open collection, search, and analytics abilities provides the comprehensive end-to-end strategy SOC teams need to gain visibility to stop threats.
John Shaw, VP of Product management at Sophos, introduced us to the world of Project Galileo. What is Sophos doing to bring Network Security and Endpoint security together? How do we make these two pillars of IT security work together?
Splunk for Enterprise Security and User Behavior AnalyticsSplunk
This session will review Splunk’s two premium solutions for information security organizations: Splunk for Enterprise Security (ES) and Splunk User Behavior Analytics (UBA). Splunk ES is Splunk's award-winning security intelligence solution that brings immediate value for continuous monitoring across SOC and incident response environments – allowing you to quickly detect and respond to external and internal attacks, simplifying threat management while decreasing risk. Splunk UBA is a new technology that applies unsupervised machine learning and data science to solving one of the biggest problems in information security today: insider threat. You’ll learn how Splunk UBA works in tandem with ES, or third-party data sources, to bring significant automated analytical power to your SOC and Incident Response teams. We’ll discuss each solution and see them integrated and in action through detailed demos.
Building the High Speed Cybersecurity Data Pipeline Using Apache NiFiDataWorks Summit
Cybersecurity requires an organization to collect data, analyze it, and alert on cyber anomalies in near real-time. This is a challenging endeavor when considering the variety of data sources which need to be collected and analyzed. Everything from application logs, network events, authentications systems, IOT devices, business events, cloud service logs, and more need to be taken into consideration. In addition, multiple data formats need to be transformed and conformed to be understood by both humans and ML/AI algorithms.
To solve this problem, the Aetna Global Security team developed the Unified Data Platform based on Apache NiFi, which allows them to remain agile and adapt to new security threats and the onboarding of new technologies in the Aetna environment. The platform currently has over 60 different data flows with 95% doing real-time ETL and handles over 20 billion events per day. In this session learn from Aetna’s experience building an edge to AI high-speed data pipeline with Apache NiFi.
Tech talk on what Azure Databricks is, why you should learn it and how to get started. We'll use PySpark and talk about some real live examples from the trenches, including the pitfalls of leaving your clusters running accidentally and receiving a huge bill ;)
After this you will hopefully switch to Spark-as-a-service and get rid of your HDInsight/Hadoop clusters.
This is part 1 of an 8 part Data Science for Dummies series:
Databricks for dummies
Titanic survival prediction with Databricks + Python + Spark ML
Titanic with Azure Machine Learning Studio
Titanic with Databricks + Azure Machine Learning Service
Titanic with Databricks + MLS + AutoML
Titanic with Databricks + MLFlow
Titanic with DataRobot
Deployment, DevOps/MLops and Operationalization
Azure Sentinel is Microsoft cloud-native SIEM and SOAR. Say goodbye to 6 months SIEM solution setup and architecture - get started with visibility on you environement just now, and use the rich ecosystem of connectors to extend intelligence to your complete security suite.
Realizing the Full Potential of Cloud-Native Application SecurityOry Segal
The talk that was presented at the APISecure 2022 conference, in which I discuss why I believe that 'API Security' is merely a small portion of the actual problem space, which is application security, and how you can leverage multi-layer protection using a single unified CNAPP platform to achieve smart defense in depth.
This example based session educates you on how to develop and run your .Net applications on AWS. Through demos, provide a walkthrough on how to deploy .NET applications using various AWS services including Amazon EC2, Amazon ECS and AWS Lambda (Serverless). Additionally, showcase how to accelerate the release of your applications with the combination of your existing toolsets like Microsoft Visual Studio Team Services and AWS’s CI/CD toolchain, with services such as AWS CodeCommit and AWS CodeBuild.
Scaling Security on 100s of Millions of Mobile Devices Using Apache Kafka® an...confluent
Watch this talk here: https://www.confluent.io/online-talks/scaling-security-on-100s-of-millions-of-mobile-devices-using-kafka-and-scylla-on-demand
Join mobile cybersecurity leader Lookout as they talk through their data ingestion journey.
Lookout enables enterprises to protect their data by evaluating threats and risks at post-perimeter endpoint devices and providing access to corporate data after conditional security scans. Their continuous assessment of device health creates a massive amount of telemetry data, forcing new approaches to data ingestion. Learn how Lookout changed its approach in order to grow from 1.5 million devices to 100 million devices and beyond, by implementing Confluent Platform and switching to Scylla.
After anomalous network traffic has been identified there can still be an abundance of results for an analyst to process. This presentation is for data scientist and network security professionals who want to increase the signal-to-noise.
Flare is a network analytic framework designed for data scientists, security researchers, and network professionals. Written in python, flare is designed for rapid prototyping and development of behavioral analytics. Flare comes with a collection of pre-built utility functions useful for performing feature extraction.
Using flare, we'll walk through identifying Domain Generation Algorithms (DGA) commonly used in malware and how to reduce the dataset to a manageable amount for security professionals to process.
We'll also explore flare's beaconing detection which can be used with the output from popular Intrusion Detection System (IDS) frameworks.
More information on flare can be found at https://github.com/austin-taylor/flare
www.austintaylor.io
Microsoft Azure Sentinel is a new Cloud native SIEM service with built-in AI for analytics that removes the cost and complexity of achieving a central and focused near real-time view of the active threats in your environment.
Falcon OverWatch Experts Hunt 24/7 To Stop Incidents Before They Become Breaches
Is your IT security team suffering from alert fatigue? For many organizations, chasing down every security alert can tax an already overburdened IT department, often resulting in a breach that might have been avoided. Adding to this challenge is an increase in sophisticated threats that strike so fast and frequently, traditional methods of investigation and response can’t offer adequate protection.
A new webcast from CrowdStrike, “Proactive Threat Hunting: Game-Changing Endpoint Protection Above and Beyond Alerting,” discusses why so many organizations are vulnerable to unseen threats and alert fatigue, and why having an approach that is both reactive and proactive is key. You’ll also learn about Falcon OverWatch™, CrowdStrike’s proactive threat hunting service that investigates and responds to threats immediately, dramatically increasing your ability to react before a damaging breach occurs.
Download the webcast slides to learn:
--How constantly reacting to alerts prevents you from getting ahead of the potentially damaging threats designed to bypass standard endpoint security
--Why an approach that includes proactive threat hunting, sometimes called Managed Detection and Response, is key to increasing protection against new and advanced threats
--How CrowdStrike Falcon OverWatch can provide 24/7 managed threat hunting, augmenting your security efforts with a team of cyber intrusion detection analysts and investigators who proactively identify and prioritize incidents before they become damaging breaches
Extended Detection and Response (XDR) An Overhyped Product Category With Ulti...Raffael Marty
Extended Detection and Response, or XDR for short, is one of the acronyms that are increasingly used by cybersecurity vendors to explain their approach to solving the cyber security problem. We have been spending trillions of dollars on approaches to secure our systems and data, with what success? Cybersecurity is still one of the biggest and most challenging areas that companies, small and large, are dealing with. XDR is another approach driven by security vendors to solve this problem. The challenge is that every vendor defines XDR slightly differently and makes it fit their own “challenge du jour” for marketing and selling their products.
In this presentation we will demystify the XDR acronym and put a working model behind it. Together, we will explore why XDR is a fabulous concept, but also discover that it’s nothing revolutionarily new. With an MSP lens, we will explore what the XDR benefits are for small and medium businesses and what it means to the security strategy of both MSPs and their clients. The audience will leave with a clear understanding of what XDR is, how the technology matters to them, and how XDR will ultimately help them secure their customers and enable trusted commerce.
Building an Intelligence-Driven Security Operations CenterEMC
This white paper describes how an intelligence-driven security operations center (SOC) improves threat detection and response by helping organizations use all available security-related information from both internal and external sources to detect hidden threats and even predict new ones.
Upgrade Your SOC with Cortex XSOAR & Elastic SIEMElasticsearch
Together, Cortex XSOAR and Elastic SIEM deliver a flexible and effective solution for today's security operations teams. Combining Cortex XSOAR's robust orchestration, automation, and case management capabilities with Elastic's open collection, search, and analytics abilities provides the comprehensive end-to-end strategy SOC teams need to gain visibility to stop threats.
John Shaw, VP of Product management at Sophos, introduced us to the world of Project Galileo. What is Sophos doing to bring Network Security and Endpoint security together? How do we make these two pillars of IT security work together?
Splunk for Enterprise Security and User Behavior AnalyticsSplunk
This session will review Splunk’s two premium solutions for information security organizations: Splunk for Enterprise Security (ES) and Splunk User Behavior Analytics (UBA). Splunk ES is Splunk's award-winning security intelligence solution that brings immediate value for continuous monitoring across SOC and incident response environments – allowing you to quickly detect and respond to external and internal attacks, simplifying threat management while decreasing risk. Splunk UBA is a new technology that applies unsupervised machine learning and data science to solving one of the biggest problems in information security today: insider threat. You’ll learn how Splunk UBA works in tandem with ES, or third-party data sources, to bring significant automated analytical power to your SOC and Incident Response teams. We’ll discuss each solution and see them integrated and in action through detailed demos.
Building the High Speed Cybersecurity Data Pipeline Using Apache NiFiDataWorks Summit
Cybersecurity requires an organization to collect data, analyze it, and alert on cyber anomalies in near real-time. This is a challenging endeavor when considering the variety of data sources which need to be collected and analyzed. Everything from application logs, network events, authentications systems, IOT devices, business events, cloud service logs, and more need to be taken into consideration. In addition, multiple data formats need to be transformed and conformed to be understood by both humans and ML/AI algorithms.
To solve this problem, the Aetna Global Security team developed the Unified Data Platform based on Apache NiFi, which allows them to remain agile and adapt to new security threats and the onboarding of new technologies in the Aetna environment. The platform currently has over 60 different data flows with 95% doing real-time ETL and handles over 20 billion events per day. In this session learn from Aetna’s experience building an edge to AI high-speed data pipeline with Apache NiFi.
Tech talk on what Azure Databricks is, why you should learn it and how to get started. We'll use PySpark and talk about some real live examples from the trenches, including the pitfalls of leaving your clusters running accidentally and receiving a huge bill ;)
After this you will hopefully switch to Spark-as-a-service and get rid of your HDInsight/Hadoop clusters.
This is part 1 of an 8 part Data Science for Dummies series:
Databricks for dummies
Titanic survival prediction with Databricks + Python + Spark ML
Titanic with Azure Machine Learning Studio
Titanic with Databricks + Azure Machine Learning Service
Titanic with Databricks + MLS + AutoML
Titanic with Databricks + MLFlow
Titanic with DataRobot
Deployment, DevOps/MLops and Operationalization
Azure Sentinel is Microsoft cloud-native SIEM and SOAR. Say goodbye to 6 months SIEM solution setup and architecture - get started with visibility on you environement just now, and use the rich ecosystem of connectors to extend intelligence to your complete security suite.
Realizing the Full Potential of Cloud-Native Application SecurityOry Segal
The talk that was presented at the APISecure 2022 conference, in which I discuss why I believe that 'API Security' is merely a small portion of the actual problem space, which is application security, and how you can leverage multi-layer protection using a single unified CNAPP platform to achieve smart defense in depth.
This example based session educates you on how to develop and run your .Net applications on AWS. Through demos, provide a walkthrough on how to deploy .NET applications using various AWS services including Amazon EC2, Amazon ECS and AWS Lambda (Serverless). Additionally, showcase how to accelerate the release of your applications with the combination of your existing toolsets like Microsoft Visual Studio Team Services and AWS’s CI/CD toolchain, with services such as AWS CodeCommit and AWS CodeBuild.
Scaling Security on 100s of Millions of Mobile Devices Using Apache Kafka® an...confluent
Watch this talk here: https://www.confluent.io/online-talks/scaling-security-on-100s-of-millions-of-mobile-devices-using-kafka-and-scylla-on-demand
Join mobile cybersecurity leader Lookout as they talk through their data ingestion journey.
Lookout enables enterprises to protect their data by evaluating threats and risks at post-perimeter endpoint devices and providing access to corporate data after conditional security scans. Their continuous assessment of device health creates a massive amount of telemetry data, forcing new approaches to data ingestion. Learn how Lookout changed its approach in order to grow from 1.5 million devices to 100 million devices and beyond, by implementing Confluent Platform and switching to Scylla.
How To Use Kafka and Druid to Tame Your Router Data (Rachel Pedreschi and Eri...confluent
Do you know who is knocking on your network’s door? Have new regulations left you scratching your head on how to a handle what is happening in your network? Network flow data helps answer many questions across a multitude of use cases including network security, performance, capacity planning, routing, operational troubleshooting and more. Today’s modern day streaming data pipelines need to include tools that can scale to meet the demands of these service providers while continuing to provide responsive answers to difficult questions. In addition to stream processing, data needs to be stored in a redundant, operationally focused database to provide fast, reliable answers to critical questions. Together, Kafka and Druid work together to create such a pipeline.
In this talk Eric Graham and Rachel Pedreschi will discuss these pipelines and cover the following topics: Network flow use cases and why this data is important. Reference architectures from production systems at a major international Bank. Why Kafka and Druid and other OSS tools for Network flows. A demo of one such system.
How To Use Kafka and Druid to Tame Your Router Data (Rachel Pedreschi, Imply ...confluent
Do you know who is knocking on your network’s door? Have new regulations left you scratching your head on how to handle what is happening in your network? Network flow data helps answer many questions across a multitude of use cases including network security, performance, capacity planning, routing, operational troubleshooting and more. Today’s modern day streaming data pipelines need to include tools that can scale to meet the demands of these service providers while continuing to provide responsive answers to difficult questions. In addition to stream processing, data needs to be stored in a redundant, operationally focused database to provide fast, reliable answers to critical questions. Together, Kafka and Druid work together to create such a pipeline.
In this talk Eric Graham and Rachel Pedreschi will discuss these pipelines and cover the following topics:
-Network flow use cases and why this data is important.
-Reference architectures from production systems at a major international Bank.
-Why Kafka and Druid and other OSS tools for Network Flows.
-A demo of one such system.
Extreme Network Performance with Hazelcast on ToruswareHazelcast
How can you get:
* Extreme Database Performance
* Extreme In-Memory Transaction Processing
* Extreme Messaging Throughput
Without throwing money at expensive Infiniband, Exadata or Exalogic Elastic Cloud hardware?
In-Memory Data Grid is a proven way to get Elastically Scalable In-Memory compute performance, and unlike Oracle Coherence and other solutions, Hazelcast is able to achieve extreme scale performance on standard (COTS) commodity scale-out hardware and JVMs, without resorting to custom protocols and proprietary hardware such as Exadata. Hazelcast can achieve significant performance boosts by using Torusware, the high-speed middleware by TORUS Software Solutions, a true plug & play product which implements multiple optimizations (optimized NIO sockets epoll, TCP/IP bypass, 10/40 Gbps ROCE, InfiniBand plus RDMA native support). Thus, Torusware improves Hazelcast extreme scalability by running on standard hardware with virtually zero communication overhead.
We’ll cover these topics:
*How Hazelcast and Torusware are 100% compatible
*An overview of performance results of Hazelcast+Torusware
*How Torusware helps Hazelcast to take full advantage of the underlying infrastructure.
*Live Q&A
Presenter:
Guillermo Lopez Taboada, TORUS CEO and Co-founder
*Inventor of Torus Technology, fast communications on low latency networks and servers.
*12 years experience in HPC and Big Data within academia and now at TORUS working in projects for Hewlett-Packard, Amazon WS, NASA, ESA, and the financial, telco and IT industries.
*PhD and BS in Computer Science
InfluxEnterprise Architecture Patterns by Tim Hall & Sam DillardInfluxData
In this InfluxDays NYC 2019 presentation, InfluxData VP of Products Tim Hall and Sales Engineer Sam Dillard discuss architecture patterns with InfluxEnterprise time series platform. They cover an overview of InfluxEnterprise, features, ingestion and query rates, deployment examples, replication patterns, and general advice. Presentation highlights include InfluxEnterprise cluster architecture and how to determine if you're ready for adopting InfluxEnterprise.
InfluxEnterprise Architectural Patterns by Dean Sheehan, Senior Director, Pre...InfluxData
Dean discusses architecture patterns with InfluxDB Enterprise, covering an overview of InfluxDB Enterprise, features, ingestion and query rates, deployment examples, replication patterns, and general advice.
Final project report on grocery store management system..pdfKamal Acharya
In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
In order to develop an e-commerce website, a number of Technologies must be studied and understood. These include multi-tiered architecture, server and client-side scripting techniques, implementation technologies, programming language (such as PHP, HTML, CSS, JavaScript) and MySQL relational databases. This is a project with the objective to develop a basic website where a consumer is provided with a shopping cart website and also to know about the technologies used to develop such a website.
This document will discuss each of the underlying technologies to create and implement an e- commerce website.
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
About
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Technical Specifications
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
Key Features
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface
• Compatible with MAFI CCR system
• Copatiable with IDM8000 CCR
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
Application
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
1. OpenSOC
The Open Security Operations
Center
for
Analyzing 1.2 Million Network Packets per Second
in Real TimeJames Sirota,
Big Data Architect
Cisco Security Solutions Practice
jsirota@cisco.com
Sheetal Dolas
Principal Architect
Hortonworks
sheetal@hortonworks.com
June 3, 2014
2. 2
Problem Statement & Business Case for OpenSOC
Solution Architecture and Design
Best Practices and Lessons Learned
Q & A
Over Next Few Minutes
4. 4
fatalism:
It's no longer if or when you get hacked,
but the assumption is that you've
already been hacked,
with a focus on minimizing the
damage.”
Source: Dark Reading / Security’s New
Reality: Assume The Worst
5. 5
Breaches Happen in Hours…
But Go Undetected for Months or Even Years
Source: 2013 Data Breach Investigations
Report
Seconds Minutes Hours Days Weeks Months Years
Initial Attack to Initial
Compromise
10% 75% 12% 2% 0% 1% 1%
Initial Compromise
to Data Exfiltration
8% 38% 14% 25% 8% 8% 0%
Initial Compromise
to Discovery
0% 0% 2% 13% 29% 54% 2%
Discovery to
Containment/
Restoration 0% 1% 9% 32% 38% 17% 4%
Timespan of events by percent of breaches
In 60% of
breaches, data
is stolen in hours
54% of breaches
are not discovered for
months
7. 7
Introducing OpenSOC
Intersection of Big Data and Security Analytics
Multi Petabyte Storage
Interactive Query
Real-Time Search
Scalable Stream
Processing
Unstructured Data
Data Access Control
Scalable Compute
OpenSOC
Real-Time Alerts
Anomaly Detection
Data
Correlation
Rules and Reports
Predictive Modeling
UI and Applications
Big Data
Platform
Hadoop
8. 8
OpenSOC Journey
Sept 2013
First Prototype
Dec 2013
Hortonworks
joins the
project
March 2014
Platform
development
finished
Sept 2014
General
Availability
May 2014
CR Work off
April 2014
First beta test
at customer
site
10. 10
OpenSOC Conceptual Architecture
Raw Network Stream
Network Metadata
Stream
Netflow
Syslog
Raw Application Logs
Other Streaming
Telemetry
HiveHBase
Raw Packet
Store
Long-Term
Store
Elastic Search
Real-Time
Index
Network Packet
Mining and
PCAP
Reconstruction
Log Mining and
Analytics
Big Data
Exploration,
Predictive
Modeling
Applications + Analyst Tools
Parse+Format
Enrich
Alert
Threat Intelligence
Feeds
Enrichment Data
11. 11
Raw Network Packet Capture, Store, Traffic Reconstruction
Telemetry Ingest, Enrichment and Real-Time Rules-Based
Alerts
Real-Time Telemetry Search and Cross-Telemetry Matching
Automated Reports, Anomaly Detection and Anomaly
Alerts
Key Functional Capabilities
12. 12
Fully-Backed by Cisco and Used Internally for Multiple
Customers
Free, Open Source and Apache Licensed
Built on Highly-Scalable and Proven Platforms (Hadoop,
Kafka, Storm)
Extensible and Pluggable Design
Flexible Deployment Model (On-Premise or Cloud)
Centralize your processes, people and data
The OpenSOC Advantage
14. 14
OpenSOC - Stitching Things Together
AccessMessaging SystemData CollectionSource Systems StorageReal Time Processing
StormKafka
B Topic
N Topic
Elastic
Search
Index
Web
Services
Search
PCAP
Reconstruction
HBase
PCAP Table
Analytic
Tools
R / Python
Power Pivot
Tableau
Hive
Raw Data
ORC
Passive
Tap
PCAP Topic
DPI Topic
A Topic
Telemetry
Sources
Syslog
HTTP
File System
Other
Flume
Agent A
Agent B
Agent N
B Topology
N Topology
A Topology
PCAP
Traffic
Replicato
r
PCAP
Topology
DPI Topology
15. 15
OpenSOC - Stitching Things Together
AccessMessaging SystemData CollectionSource Systems StorageReal Time Processing
StormKafka
B Topic
N Topic
Elastic
Search
Index
Web
Services
Search
PCAP
Reconstruction
HBase
PCAP Table
Analytic
Tools
R / Python
Power Pivot
Tableau
Hive
Raw Data
ORC
Passive
Tap
PCAP Topic
DPI Topic
A Topic
Telemetry
Sources
Syslog
HTTP
File System
Other
Flume
Agent A
Agent B
Agent N
B Topology
N Topology
A Topology
PCAP
Traffic
Replicato
r
Deeper
Look
PCAP
Topology
DPI Topology
16. 16
PCAP Topology
StorageReal Time Processing
Storm
Elastic Search
Index
HBase
PCAP Table
Hive
Raw Data
ORC
Kafka
Spout
Parse
r
Bolt
HDFS
Bolt
HBas
e
Bolt
ES
Bolt
17. 17
DPI Topology & Telemetry Enrichment
StorageReal Time Processing
Storm
Elastic Search
Index
HBase
PCAP Table
Hive
Raw Data
ORC
Kafka
Spout
Parse
r Bolt
GEO
Enric
h
Whoi
s
Enric
h
CIF
Enric
h
HDF
S
Bolt
ES
Bolt
18. 18
Enrichments
Parse
r
Bolt
GEO
Enrich
RAW
Message
{
“msg_key1”: “msg value1”,
“src_ip”: “10.20.30.40”,
“dest_ip”: “20.30.40.50”,
“domain”: “mydomain.com”
}
Who
Is
Enrich
"geo":[ {"region":"CA",
"postalCode":"95134",
"areaCode":"408",
"metroCode":"807",
"longitude":-121.946,
"latitude":37.425,
"locId":4522,
"city":"San Jose",
"country":"US"
}]
CIF
Enrich
"whois":[ {
"OrgId":"CISCOS",
"Parent":"NET-144-0-0-0-0",
"OrgAbuseName":"Cisco Systems Inc",
"RegDate":"1991-01-171991-01-17",
"OrgName":"Cisco Systems",
"Address":"170 West Tasman Drive",
"NetType":"Direct Assignment"
} ],
“cif”:”Yes”
Enriched
Message
Cache
MySQL
Geo Lite
Data
Cache
HBase
Who Is Data
Cache
HBase
CIF Data
26. 26
Is Disk I/O heavy
Kafka 0.8+ supports replication and JBOD
Better performance compared to RAID
Parallelism is largely driven by number of disks and partitions per topic
Key configuration parameters:
num.io.threads - Keep it at least equal to number of disks provided to
Kafka
num.network.threads - adjust it based on number of concurrent
producers, consumers and replication factor
Kafka Tuning
31. 31
Row Key design is critical (gets or scans or both?)
Keys with IP Addresses
Standard IP addresses have only two variations of the first character : 1 & 2
Minimum key length will be 7 characters and max 15 with a typical average of 12
Subnet range scans become difficult – range of 90 to 220 excludes 112
IP converted to hex (10.20.30.40 => 0a141e28)
gives 16 variations of first key character
consistently 8 character key
Easy to search for subnet ranges
Row Key Design
33. 33
Know your data
Auto split under high workload can result into hotspots and split storms
Understand your data and presplit the regions
Identify how many regions a RS can have to perform optimally. Use the
formula below
(RS memory)*(total memstore fraction)/((memstore size)*(# column families))
Region Splits
35. 35
Enable Micro Batching (client side buffer)
Smart shuffle/grouping in storm
Understand your data and situationally exploit various WAL options
Watch for many minor compactions
For heavy ‘write’ workload Increase hbase.hstore.blockingStoreFiles (we
used 200)
Know Your Application
38. 38
Parallelism is controlled by number of partitions per topic
Set Kafka spout parallelism equal to number of partitions in
topic
Other key parameters that drive performance
fetchSizeBytes
bufferSizeBytes
Kafka Spout
40. 40
A bug in Kafka spout that used to miss out some partitions
and loose data
It is now fixed and available from Hortonworks repository (
http://repo.hortonworks.com/content/repositories/releases/org/apache/
storm/storm-Kafka )
Mysteriously Missing Data Root Cause
42. 42
Every small thing counts at scale
Even simple string operations can slowdown throughput when
executed on millions of Tuples
Storm
43. 43
Error handling is critical
Poorly handled errors can lead to topology failure and eventually loss
of data (or data duplication)
Storm
44. 44
Tune & Scale individual spout and bolts before performance
testing/tuning entire topology
Write your own simple data generator spouts and no-op bolts
Making as many things configurable as possible helps a lot
Storm
45. 45
When it comes to Hadoop…partner up
Separate the hype from the opportunity
Start small then scale up
Design Iteratively
It doesn’t work unless you have proven it at scale
Keep an eye on ROI
Lessons Learned
46. 46
How can you contribute?
Technology Partner Program – contribute developers to
join the Cisco and Hortonworks team
Looking for Community Partners
Cisco + Hortonworks + Community Support for OpenSOC
In Storm bolts shuffle group based on regions so that each HBase bolt gets data mostly for one or two regions and minimizes RS trips
In case of DoS attack situations where actual packet are very small 20-60 bytes and individual packets are not very critical for analysis, skip WAL
In Storm bolts shuffle group based on regions so that each HBase bolt gets data mostly for one or two regions and minimizes RS trips
In case of DoS attack situations where actual packet are very small 20-60 bytes and individual packets are not very critical for analysis, skip WAL
Frequent minor compactions reduce the overall throughput of system. For ‘write’ heavy workload reduce frequency of minor compactions by increasing hbase.hstore.blockingStoreFiles (we used 200)
Frequent minor compactions reduce the overall throughput of system. For ‘write’ heavy workload reduce frequency of minor compactions by increasing hbase.hstore.blockingStoreFiles (we used 200)
Frequent minor compactions reduce the overall throughput of system. For ‘write’ heavy workload reduce frequency of minor compactions by increasing hbase.hstore.blockingStoreFiles (we used 200)
