Smart Investigator is a revolutionary and fully scalable Big Data Security Analytics Platform that unifies data from all networks and systems and offers real-time visibility through contextual dashboards.
SECURE COLLABORATIVE PROCESSING ARCHITECTURE FOR MITB ATTACK DETECTIONIJNSA Journal
In this paper, we take a distributed architecture called Semantic Room (SR) which is capable of correlating events coming from several organizations participating in the SR, developed in the context of the EU Project COMIFIN, and we add privacy capability to the SR.. The SR architecture consists of Edge Gateways deployed at each financial institution and a set of private clouds that form the SR collaborative processing system (CSP). Edge Gateways perform data pre-processing and anonymize data items, as prescribed by the SR contract, using Shamir secret sharing scheme. Anonymous data are sent to the CPS that aggregates information through MapReduce-based computations. The anonymous data resulting from the collaborative computation are revealed to the financial institutions only if suspicious cyber threat activities are detected. In this paper we show how this SR can be leveraged for detecting Man-In-TheBrowser attacks.
Threat Modeling of Cloud based Implementation of Homomorphic Encryptionijcisjournal
Outsourcing of data storage and data processing to cloud-based service providers promises several advantages such as reduced maintenance overhead, elastic performance, high availability, and security. Cloud services offer a variety of functionalities for performing different operations on the data. However, during the processing of data in cloud, security and privacy may be compromised because of inadequate cryptographic implementation. Conventional encryption methods guarantee security during transport (data-in-transit) and storage (data-at-rest), but cannot prevent data leak during an operation on the data (data-in-use). Modern homomorphic encryption methods promise to solve this problem by applying different operations on encrypted data without knowing or deciphering the data. Cloud-based implementation of homomorphic cryptography has
seen significant development in the recent past. However, data security, even with implemented homomorphic cryptography, is still dependant on the users and the application owners. This exposes the risk of introducing new attack surfaces. In this paper, we introduce a novel and one of the early attempts to model such new attack surfaces on the implementation of homomorphic encryption and map them to STRIDE threat model [1] which is proliferously used in the industry.
This chapter is devoted to log mining or log knowledge discovery - a different type of log analysis, which does not rely on knowing what to look for. This takes the “high art” of log analysis to the next level by breaking the dependence on the lists of strings or patterns to look for in the logs.
Big data presentationandoverview_of_couchbaseAMAR NATH
The document discusses current trends in big data, including business scenarios where big data can provide insights. It outlines the differences between engagement databases and transactional databases, and highlights key capabilities of Couchbase like joins, eventing services, and auto failover. The document also covers the four dimensions of big data, a layered framework approach, and popular tools and technologies used for ingestion, storage, processing, and analytics of big data.
Sqrrl Enterprise is a platform that allows users to integrate, explore, and analyze massive amounts of data from any source through a web-based interface. It uses linked data analysis to identify hidden opportunities and threats in data by linking important assets and events. This accelerates insight for analysts by allowing them to visually explore relationships between entities and drill down to underlying data. Sqrrl Enterprise also enables secure collaboration and tracking of analysis workflows.
The Matrix Mapper (MM) - This is a product for which the Aarktech - KBCRF consortium is looking for any of several options to develop the product that would mirror the capabilities of the Analysts' Notebook (AN), an application created by i2, an IBM subsidiary, which cannot be sold anywhere outside the US and Russia and is subject to stringent US Export Control (EC) regulations.
The AN is the most sought after (but not readily available) tool, worldwide, by global businesses as also the crime fighting, counter terrorist, counter insurgency and financial intelligence agencies of numerous countries. It has the capability to integrate mountains of text, video, audio, graphic and image data and to employ Big Data Analytics, Semantics, Social Network Analysis (SNA) and Knowledge Discovery methods to delineate the existence, incidence, pattern and correlation of linkages in order to throw up actionable and predictive results.
The tsunami of data being generated globally threatens to submerge and seriously impair the interests of government agencies as well businesses worldwide unless powerful tools are available to intelligently comprehend diverse data types like alpha-numeric, voice, video and graphic; analyse these tidal waves of data; decipher patterns as well as connections and arrive at inferences and conclusions that provide a firm basis for next steps be they brick and mortar or in cyber space.
Matrix Mapper would serve as the ultimate tool for very large scale, cross platform, data collation, mining, comprehension, analysis, networking/ pattern identification and prediction/ direction determination using knowledge discovery methods. The Matrix Mapper would, thus, prove indispensable to businesses in sectors as diverse as mining, oil & gas, power (generation & distribution), airlines, land and water transport, shipping, chain stores, agriculture/ food distribution, warehousing, courier concerns, accounting, banking and insurance. Government agencies/ departments which would find Matrix Mapper to be a kind of force multiplier include the defence forces, police, forest conservation, counter terrorism units, municipalities, railways and a variety of Public Sector Undertakings.
How to Swiftly Operationalize the Data Lake for Advanced Analytics Using a Lo...Denodo
Watch full webinar here: https://bit.ly/3mfFJqb
Presented at Chief Data Officer Live Series 2021, ASEAN (August Edition)
While big data initiatives have become necessary for any business to generate actionable insights, big data fabric has become a necessity for any successful big data initiative. The best-of-breed big data fabrics should deliver actionable insights to the business users with minimal effort, provide end-to-end security to the entire enterprise data platform, and provide real-time data integration while delivering a self-service data platform to business users.
Watch this on-demand session to learn how big data fabric enabled by Data Virtualization:
- Provides lightning fast self-service data access to business users
- Centralizes data security, governance, and data privacy
- Fulfills the promise of data lakes to provide actionable insights
Data Sharing with Sensitive Information Hiding in Data Storage using Cloud Co...ijtsrd
With cloud storage services, users can remotely store their data to the cloud and realize the data sharing with others. Remote data integrity auditing scheme is proposed to guarantee the integrity of the data stored in the cloud. In some common cloud storage systems such as the Electronic Health Records EHRs system, the cloud file might contain some sensitive information. The sensitive information should not be exposed to others when the cloud file is shared. Encrypting the whole shared file can realize the sensitive information hiding, but will make this shared file unable to be used by others. How to realize data sharing with sensitive information hiding in remote data integrity auditing still has not been explored up to now. In order to address this problem, we propose a remote data integrity auditing scheme that realizes data sharing with sensitive information hiding in this system. Paruvathavarthini M | Prasuna K S | Sermakani. A. M ""Data Sharing with Sensitive Information Hiding in Data Storage using Cloud Computing"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-2 , February 2020,
URL: https://www.ijtsrd.com/papers/ijtsrd30007.pdf
Paper Url : https://www.ijtsrd.com/engineering/information-technology/30007/data-sharing-with-sensitive-information-hiding-in-data-storage-using-cloud-computing/paruvathavarthini-m
SECURE COLLABORATIVE PROCESSING ARCHITECTURE FOR MITB ATTACK DETECTIONIJNSA Journal
In this paper, we take a distributed architecture called Semantic Room (SR) which is capable of correlating events coming from several organizations participating in the SR, developed in the context of the EU Project COMIFIN, and we add privacy capability to the SR.. The SR architecture consists of Edge Gateways deployed at each financial institution and a set of private clouds that form the SR collaborative processing system (CSP). Edge Gateways perform data pre-processing and anonymize data items, as prescribed by the SR contract, using Shamir secret sharing scheme. Anonymous data are sent to the CPS that aggregates information through MapReduce-based computations. The anonymous data resulting from the collaborative computation are revealed to the financial institutions only if suspicious cyber threat activities are detected. In this paper we show how this SR can be leveraged for detecting Man-In-TheBrowser attacks.
Threat Modeling of Cloud based Implementation of Homomorphic Encryptionijcisjournal
Outsourcing of data storage and data processing to cloud-based service providers promises several advantages such as reduced maintenance overhead, elastic performance, high availability, and security. Cloud services offer a variety of functionalities for performing different operations on the data. However, during the processing of data in cloud, security and privacy may be compromised because of inadequate cryptographic implementation. Conventional encryption methods guarantee security during transport (data-in-transit) and storage (data-at-rest), but cannot prevent data leak during an operation on the data (data-in-use). Modern homomorphic encryption methods promise to solve this problem by applying different operations on encrypted data without knowing or deciphering the data. Cloud-based implementation of homomorphic cryptography has
seen significant development in the recent past. However, data security, even with implemented homomorphic cryptography, is still dependant on the users and the application owners. This exposes the risk of introducing new attack surfaces. In this paper, we introduce a novel and one of the early attempts to model such new attack surfaces on the implementation of homomorphic encryption and map them to STRIDE threat model [1] which is proliferously used in the industry.
This chapter is devoted to log mining or log knowledge discovery - a different type of log analysis, which does not rely on knowing what to look for. This takes the “high art” of log analysis to the next level by breaking the dependence on the lists of strings or patterns to look for in the logs.
Big data presentationandoverview_of_couchbaseAMAR NATH
The document discusses current trends in big data, including business scenarios where big data can provide insights. It outlines the differences between engagement databases and transactional databases, and highlights key capabilities of Couchbase like joins, eventing services, and auto failover. The document also covers the four dimensions of big data, a layered framework approach, and popular tools and technologies used for ingestion, storage, processing, and analytics of big data.
Sqrrl Enterprise is a platform that allows users to integrate, explore, and analyze massive amounts of data from any source through a web-based interface. It uses linked data analysis to identify hidden opportunities and threats in data by linking important assets and events. This accelerates insight for analysts by allowing them to visually explore relationships between entities and drill down to underlying data. Sqrrl Enterprise also enables secure collaboration and tracking of analysis workflows.
The Matrix Mapper (MM) - This is a product for which the Aarktech - KBCRF consortium is looking for any of several options to develop the product that would mirror the capabilities of the Analysts' Notebook (AN), an application created by i2, an IBM subsidiary, which cannot be sold anywhere outside the US and Russia and is subject to stringent US Export Control (EC) regulations.
The AN is the most sought after (but not readily available) tool, worldwide, by global businesses as also the crime fighting, counter terrorist, counter insurgency and financial intelligence agencies of numerous countries. It has the capability to integrate mountains of text, video, audio, graphic and image data and to employ Big Data Analytics, Semantics, Social Network Analysis (SNA) and Knowledge Discovery methods to delineate the existence, incidence, pattern and correlation of linkages in order to throw up actionable and predictive results.
The tsunami of data being generated globally threatens to submerge and seriously impair the interests of government agencies as well businesses worldwide unless powerful tools are available to intelligently comprehend diverse data types like alpha-numeric, voice, video and graphic; analyse these tidal waves of data; decipher patterns as well as connections and arrive at inferences and conclusions that provide a firm basis for next steps be they brick and mortar or in cyber space.
Matrix Mapper would serve as the ultimate tool for very large scale, cross platform, data collation, mining, comprehension, analysis, networking/ pattern identification and prediction/ direction determination using knowledge discovery methods. The Matrix Mapper would, thus, prove indispensable to businesses in sectors as diverse as mining, oil & gas, power (generation & distribution), airlines, land and water transport, shipping, chain stores, agriculture/ food distribution, warehousing, courier concerns, accounting, banking and insurance. Government agencies/ departments which would find Matrix Mapper to be a kind of force multiplier include the defence forces, police, forest conservation, counter terrorism units, municipalities, railways and a variety of Public Sector Undertakings.
How to Swiftly Operationalize the Data Lake for Advanced Analytics Using a Lo...Denodo
Watch full webinar here: https://bit.ly/3mfFJqb
Presented at Chief Data Officer Live Series 2021, ASEAN (August Edition)
While big data initiatives have become necessary for any business to generate actionable insights, big data fabric has become a necessity for any successful big data initiative. The best-of-breed big data fabrics should deliver actionable insights to the business users with minimal effort, provide end-to-end security to the entire enterprise data platform, and provide real-time data integration while delivering a self-service data platform to business users.
Watch this on-demand session to learn how big data fabric enabled by Data Virtualization:
- Provides lightning fast self-service data access to business users
- Centralizes data security, governance, and data privacy
- Fulfills the promise of data lakes to provide actionable insights
Data Sharing with Sensitive Information Hiding in Data Storage using Cloud Co...ijtsrd
With cloud storage services, users can remotely store their data to the cloud and realize the data sharing with others. Remote data integrity auditing scheme is proposed to guarantee the integrity of the data stored in the cloud. In some common cloud storage systems such as the Electronic Health Records EHRs system, the cloud file might contain some sensitive information. The sensitive information should not be exposed to others when the cloud file is shared. Encrypting the whole shared file can realize the sensitive information hiding, but will make this shared file unable to be used by others. How to realize data sharing with sensitive information hiding in remote data integrity auditing still has not been explored up to now. In order to address this problem, we propose a remote data integrity auditing scheme that realizes data sharing with sensitive information hiding in this system. Paruvathavarthini M | Prasuna K S | Sermakani. A. M ""Data Sharing with Sensitive Information Hiding in Data Storage using Cloud Computing"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-2 , February 2020,
URL: https://www.ijtsrd.com/papers/ijtsrd30007.pdf
Paper Url : https://www.ijtsrd.com/engineering/information-technology/30007/data-sharing-with-sensitive-information-hiding-in-data-storage-using-cloud-computing/paruvathavarthini-m
Watch full webinar here: https://bit.ly/2SaBj5l
You will often hear that "data is the new gold". In this context, data management is one of the areas that has received more attention by the software community in recent years. From Artificial Intelligence and Machine Learning to new ways to store and process data, the landscape for data management is in constant evolution. From the privileged perspective of an enterprise middleware platform, we at Denodo have the advantage of seeing many of these changes happen.
In this webinar we will discuss the technology trends that will drive the enterprise data strategies in the years to come. Don't miss it if you want to keep yourself informed about how to convert your data to strategic assets in order to complete the data-driven transformation in your company.
Join us for an exciting session that will cover:
- The most interesting trends in data management
- How to build a logical data fabric architecture?
- How to manage your data integration strategy in the new hybrid world?
- Our predictions on how those trends will change the data management world
- How can companies monetize the data through data-as-a-service infrastructure?
- What is the role of the voice computing in the future of data analytics?
IRJET- Mutual Key Oversight Procedure for Cloud Security and Distribution of ...IRJET Journal
The document proposes a mutual key oversight procedure for cloud security and distribution of data based on a hierarchy method. It discusses using attribute-based encryption to encrypt data before outsourcing it to the cloud. The proposed scheme uses a hierarchical structure with a cloud authority, domain authorities, and users to provide security and scalability. It allows both private and public uploading and sharing of files within this hierarchy.
IRJET- A Novel and Secure Approach to Control and Access Data in Cloud St...IRJET Journal
This document proposes a novel approach to securely control and access data stored in the cloud using Ciphertext-Policy Attribute-Based Encryption (CP-ABE). The approach aims to address abuse of access credentials by tracing malicious insiders and revoking their access. It presents two new CP-ABE frameworks that allow traceability of malicious cloud clients, identification of misbehaving authorities, and auditing without requiring extensive storage. The frameworks provide fine-grained access control and can revoke credentials of traced attackers.
Partner Keynote: How Logical Data Fabric Knits Together Data Visualization wi...Denodo
Watch full webinar here: https://bit.ly/3aALFEC
Data Visualization and Data Virtualization are complementary technologies. But how do they come together under a common data fabric? This presentation will discuss how organizations are advancing their data fabric capabilities leveraging innovations in these two technologies in areas of self-service, data catalog, cloud, and AI/ML.
“A Distributed Operational and Informational Technological Stack” Stratio
This document describes a distributed operational and informational technological stack. It provides a unique datacentric suite that includes a multidatastore for operational and analytical applications, data fusion and intelligence layers, and the Stratio EOS platform. The roadmap focuses on further developing the multidatastore, data intelligence capabilities like artificial intelligence, and security and governance functions.
This document summarizes the key features of HPE Universal Discovery software. It discovers assets, applications, and infrastructure dependencies across physical, virtual, and cloud environments and maps them automatically. It integrates with the HPE Universal CMDB to provide a comprehensive and continuously updated view of the IT environment that supports incident and change management. Discovery is automated, agent-based, agentless, and passive to provide complete visibility.
Edge computing and the Internet of Things bring great promise, but often just getting data from the edge requires moving mountains. Let's learn how to make edge data ingestion and analytics easier using StreamSets Data Collector edge, an ultralight, platform independent and small-footprint Open Source solution written in Go for streaming data from resource-constrained sensors and personal devices (like medical equipment or smartphones) to Apache Kafka, Amazon Kinesis and many others. This talk includes an overview of the SDC Edge main features, supported protocols and available processors for data transformation, insights on how it solves some challenges of traditional approaches to data ingestion, pipeline design basics, a walk-through some practical applications (Android devices and Raspberry Pi) and its integration with other technologies such as Streamsets Data Collector, Apache Kafka, Apache Hadoop, InfluxDB and Grafana. The goal here is to make attendees ready to quickly become IoT data intake and SDC Edge Ninjas.
Speaker
Guglielmo Iozzia, Big Data Delivery Manager, Optum (United Health)
Cloud Analytics Ability to Design, Build, Secure, and Maintain Analytics Solu...YogeshIJTSRD
Cloud Analytics is another area in the IT field where different services like Software, Infrastructure, storage etc. are offered as services online. Users of cloud services are under constant fear of data loss, security threats, and availability issues. However, the major challenge in these methods is obtaining real time and unbiased datasets. Many datasets are internal and cannot be shared due to privacy issues or may lack certain statistical characteristics. As a result of this, researchers prefer to generate datasets for training and testing purposes in simulated or closed experimental environments which may lack comprehensiveness. Advances in sensor technology, the Internet of things IoT , social networking, wireless communications, and huge collection of data from years have all contributed to a new field of study Big Data is discussed in this paper. Through this analysis and investigation, we provide recommendations for the research public on future directions on providing data based decisions for cloud supported Big Data computing and analytic solutions. This paper concentrates upon the recent trends in Big Data storage and analysing, in the clouds, and also points out the security limitations. Rajan Ramvilas Saroj "Cloud Analytics: Ability to Design, Build, Secure, and Maintain Analytics Solutions on the Cloud" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-5 , August 2021, URL: https://www.ijtsrd.com/papers/ijtsrd43728.pdf Paper URL: https://www.ijtsrd.com/other-scientific-research-area/other/43728/cloud-analytics-ability-to-design-build-secure-and-maintain-analytics-solutions-on-the-cloud/rajan-ramvilas-saroj
This document outlines how DataStax Enterprise can be used to implement key components of Microsoft's Azure IoT reference architecture. Specifically, it describes how DSE can provide the scalability, resilience, and analytics capabilities needed for implementing the device registry store, device state store, and real-time and batch analytics components. DSE is presented as a good fit due to its ability to linearly scale throughput, tolerate failures across data centers and racks, and provide integrated graph databases, search, and machine learning functionality.
Trisul Network Analytics 6.5 is a network security monitoring and traffic analytics platform that provides real-time visibility and historical analytics of network traffic. It uses streaming analytics algorithms to extract over 200 metrics from full packet captures or netflow in real-time. The platform includes traffic and bandwidth metrics, flow analysis, security analytics by integrating with IDS, metadata extraction, packet analytics, and extensibility through a Lua API. It can be deployed in a distributed architecture with probe and hub nodes.
The document discusses data center micro-segmentation using a software defined data center (SDDC) approach with VMware NSX network virtualization. Key points:
- SDDC with NSX allows fine-grained network segmentation down to individual VMs through automated provisioning of security policies. This micro-segmentation improves security but was previously difficult to implement.
- NSX provides isolation of virtual networks by default without configuration. It also allows segmentation within a virtual network through distributed firewalling to separate network tiers like web, app, and database.
- NSX firewalling performance of 20Gbps per host meets the needs of micro-segmentation, and automation addresses the operational challenges of managing thousands of policies
Design patterns provide reusable solutions to common problems in software design. The Gang of Four patterns include creational, structural, and behavioral patterns that address problems like object creation, composition, and communication. Cryptography uses encryption algorithms and keys to secure data transmission and storage. Symmetric encryption uses a single private key while asymmetric encryption uses public/private key pairs. Common algorithms like AES and RSA are available in .NET.
The Hive Think Tank - The Microsoft Big Data Stack by Raghu Ramakrishnan, CTO...The Hive
Until recently, data was gathered for well-defined objectives such as auditing, forensics, reporting and line-of-business operations; now, exploratory and predictive analysis is becoming ubiquitous, and the default increasingly is to capture and store any and all data, in anticipation of potential future strategic value. These differences in data heterogeneity, scale and usage are leading to a new generation of data management and analytic systems, where the emphasis is on supporting a wide range of very large datasets that are stored uniformly and analyzed seamlessly using whatever techniques are most appropriate, including traditional tools like SQL and BI and newer tools, e.g., for machine learning and stream analytics. These new systems are necessarily based on scale-out architectures for both storage and computation.
Hadoop has become a key building block in the new generation of scale-out systems. On the storage side, HDFS has provided a cost-effective and scalable substrate for storing large heterogeneous datasets. However, as key customer and systems touch points are instrumented to log data, and Internet of Things applications become common, data in the enterprise is growing at a staggering pace, and the need to leverage different storage tiers (ranging from tape to main memory) is posing new challenges, leading to caching technologies, such as Spark. On the analytics side, the emergence of resource managers such as YARN has opened the door for analytics tools to bypass the Map-Reduce layer and directly exploit shared system resources while computing close to data copies. This trend is especially significant for iterative computations such as graph analytics and machine learning, for which Map-Reduce is widely recognized to be a poor fit.
While Hadoop is widely recognized and used externally, Microsoft has long been at the forefront of Big Data analytics, with Cosmos and Scope supporting all internal customers. These internal services are a key part of our strategy going forward, and are enabling new state of the art external-facing services such as Azure Data Lake and more. I will examine these trends, and ground the talk by discussing the Microsoft Big Data stack.
This document summarizes a presentation given by Rohan Nandi on security in embedded systems. The presentation covered what embedded systems are, an introduction to network security, why embedded system security is currently lacking and vulnerabilities. It also discussed countermeasures to avoid attacks, a proposed hardware-software solution, comparisons to existing software-only solutions, challenges, future scope, and references.
Magiclock: Scalable Detection of Potential Deadlocks in Large-Scale Multithre...KaashivInfoTech Company
The document presents Magiclock, a technique for detecting potential deadlocks in large multithreaded programs. Magiclock analyzes execution traces without any actual deadlocks occurring. It iteratively eliminates unnecessary lock dependencies and partitions lock dependencies by thread to efficiently detect potential deadlock chains without examining duplicate permutations. The experimental results showed Magiclock is more scalable and efficient than existing dynamic detectors.
The document discusses the NetWitness network security platform. It provides situational awareness and deep visibility into network activity to detect advanced threats. When deployed, NetWitness immediately provides insight into what is happening on a network through its NextGen platform. This platform records all network data, filters it, and organizes it into a searchable framework to enable analysis, reporting, and visualization of network traffic. It uses various components and applications to interrogate the data, detect anomalies, and gain intelligence about security issues.
Denodo DataFest 2017: Lowering IT Costs with Big Data and Cloud ModernizationDenodo
Watch the live presentation on-demand now: https://goo.gl/QanW35
Organizations are fast adapting cloud to lower the IT costs, and increase agility.
Watch this Denodo DataFest 2017 session to discover:
• How Logitech migrated their on-premise data warehouse and big data systems to the cloud and minimizing costs and immensely improved their time-to-market.
• The four main challenges Logitech faced when moving their data to the cloud.
• The benefits of adding a data virtualization layer to your data architecure.
This document provides an overview of designing Internet of Things (IoT) systems. It begins with definitions and then describes the key components of an IoT architecture including devices, communication protocols, platforms, and programming languages. Example open source platforms are also discussed. The presentation aims to provide a general understanding of creating IoT prototypes and selecting suitable technologies. Security, analytics, cognitive capabilities and solutions templates are also reviewed at a high level. The overall goal is to help understand the big picture of designing IoT systems and connect concepts to daily work.
Zapata Technology provides advanced technology solutions and expertise to US government agencies and the defense sector. It develops customized systems, software, and tools to support critical missions around the world. Some of its key products and services include data ingestion tools, monitoring systems, object recognition software, report generation AI, and engineering and testing support. Zapata works on various contracts with organizations like the DoD, Army, Navy, and intelligence community.
Next-Gen Cloud Analytics with AWS, Big Data and Data VirtualizationDenodo
Watch Tekin's keynote presentation from Fast Data Strategy Virtual Summit here: https://goo.gl/RJon7n
The Denodo Platform for AWS enabled Logitech's cloud journey with minimal impact on business operations. The Denodo Platform acts a big data fabric layer and sources data for all of Logitech's analytics initiatives from descriptive to prescriptive to predictive analytics including NLP processing engines.
Attend this session to learn how Logitech:
• Reduced TCO such as infrastructure and operational expenses
• Empowered their business users with advanced analytics capabilities
• Uses AWS and Denodo as their innovation engine
Watch full webinar here: https://bit.ly/2SaBj5l
You will often hear that "data is the new gold". In this context, data management is one of the areas that has received more attention by the software community in recent years. From Artificial Intelligence and Machine Learning to new ways to store and process data, the landscape for data management is in constant evolution. From the privileged perspective of an enterprise middleware platform, we at Denodo have the advantage of seeing many of these changes happen.
In this webinar we will discuss the technology trends that will drive the enterprise data strategies in the years to come. Don't miss it if you want to keep yourself informed about how to convert your data to strategic assets in order to complete the data-driven transformation in your company.
Join us for an exciting session that will cover:
- The most interesting trends in data management
- How to build a logical data fabric architecture?
- How to manage your data integration strategy in the new hybrid world?
- Our predictions on how those trends will change the data management world
- How can companies monetize the data through data-as-a-service infrastructure?
- What is the role of the voice computing in the future of data analytics?
IRJET- Mutual Key Oversight Procedure for Cloud Security and Distribution of ...IRJET Journal
The document proposes a mutual key oversight procedure for cloud security and distribution of data based on a hierarchy method. It discusses using attribute-based encryption to encrypt data before outsourcing it to the cloud. The proposed scheme uses a hierarchical structure with a cloud authority, domain authorities, and users to provide security and scalability. It allows both private and public uploading and sharing of files within this hierarchy.
IRJET- A Novel and Secure Approach to Control and Access Data in Cloud St...IRJET Journal
This document proposes a novel approach to securely control and access data stored in the cloud using Ciphertext-Policy Attribute-Based Encryption (CP-ABE). The approach aims to address abuse of access credentials by tracing malicious insiders and revoking their access. It presents two new CP-ABE frameworks that allow traceability of malicious cloud clients, identification of misbehaving authorities, and auditing without requiring extensive storage. The frameworks provide fine-grained access control and can revoke credentials of traced attackers.
Partner Keynote: How Logical Data Fabric Knits Together Data Visualization wi...Denodo
Watch full webinar here: https://bit.ly/3aALFEC
Data Visualization and Data Virtualization are complementary technologies. But how do they come together under a common data fabric? This presentation will discuss how organizations are advancing their data fabric capabilities leveraging innovations in these two technologies in areas of self-service, data catalog, cloud, and AI/ML.
“A Distributed Operational and Informational Technological Stack” Stratio
This document describes a distributed operational and informational technological stack. It provides a unique datacentric suite that includes a multidatastore for operational and analytical applications, data fusion and intelligence layers, and the Stratio EOS platform. The roadmap focuses on further developing the multidatastore, data intelligence capabilities like artificial intelligence, and security and governance functions.
This document summarizes the key features of HPE Universal Discovery software. It discovers assets, applications, and infrastructure dependencies across physical, virtual, and cloud environments and maps them automatically. It integrates with the HPE Universal CMDB to provide a comprehensive and continuously updated view of the IT environment that supports incident and change management. Discovery is automated, agent-based, agentless, and passive to provide complete visibility.
Edge computing and the Internet of Things bring great promise, but often just getting data from the edge requires moving mountains. Let's learn how to make edge data ingestion and analytics easier using StreamSets Data Collector edge, an ultralight, platform independent and small-footprint Open Source solution written in Go for streaming data from resource-constrained sensors and personal devices (like medical equipment or smartphones) to Apache Kafka, Amazon Kinesis and many others. This talk includes an overview of the SDC Edge main features, supported protocols and available processors for data transformation, insights on how it solves some challenges of traditional approaches to data ingestion, pipeline design basics, a walk-through some practical applications (Android devices and Raspberry Pi) and its integration with other technologies such as Streamsets Data Collector, Apache Kafka, Apache Hadoop, InfluxDB and Grafana. The goal here is to make attendees ready to quickly become IoT data intake and SDC Edge Ninjas.
Speaker
Guglielmo Iozzia, Big Data Delivery Manager, Optum (United Health)
Cloud Analytics Ability to Design, Build, Secure, and Maintain Analytics Solu...YogeshIJTSRD
Cloud Analytics is another area in the IT field where different services like Software, Infrastructure, storage etc. are offered as services online. Users of cloud services are under constant fear of data loss, security threats, and availability issues. However, the major challenge in these methods is obtaining real time and unbiased datasets. Many datasets are internal and cannot be shared due to privacy issues or may lack certain statistical characteristics. As a result of this, researchers prefer to generate datasets for training and testing purposes in simulated or closed experimental environments which may lack comprehensiveness. Advances in sensor technology, the Internet of things IoT , social networking, wireless communications, and huge collection of data from years have all contributed to a new field of study Big Data is discussed in this paper. Through this analysis and investigation, we provide recommendations for the research public on future directions on providing data based decisions for cloud supported Big Data computing and analytic solutions. This paper concentrates upon the recent trends in Big Data storage and analysing, in the clouds, and also points out the security limitations. Rajan Ramvilas Saroj "Cloud Analytics: Ability to Design, Build, Secure, and Maintain Analytics Solutions on the Cloud" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-5 , August 2021, URL: https://www.ijtsrd.com/papers/ijtsrd43728.pdf Paper URL: https://www.ijtsrd.com/other-scientific-research-area/other/43728/cloud-analytics-ability-to-design-build-secure-and-maintain-analytics-solutions-on-the-cloud/rajan-ramvilas-saroj
This document outlines how DataStax Enterprise can be used to implement key components of Microsoft's Azure IoT reference architecture. Specifically, it describes how DSE can provide the scalability, resilience, and analytics capabilities needed for implementing the device registry store, device state store, and real-time and batch analytics components. DSE is presented as a good fit due to its ability to linearly scale throughput, tolerate failures across data centers and racks, and provide integrated graph databases, search, and machine learning functionality.
Trisul Network Analytics 6.5 is a network security monitoring and traffic analytics platform that provides real-time visibility and historical analytics of network traffic. It uses streaming analytics algorithms to extract over 200 metrics from full packet captures or netflow in real-time. The platform includes traffic and bandwidth metrics, flow analysis, security analytics by integrating with IDS, metadata extraction, packet analytics, and extensibility through a Lua API. It can be deployed in a distributed architecture with probe and hub nodes.
The document discusses data center micro-segmentation using a software defined data center (SDDC) approach with VMware NSX network virtualization. Key points:
- SDDC with NSX allows fine-grained network segmentation down to individual VMs through automated provisioning of security policies. This micro-segmentation improves security but was previously difficult to implement.
- NSX provides isolation of virtual networks by default without configuration. It also allows segmentation within a virtual network through distributed firewalling to separate network tiers like web, app, and database.
- NSX firewalling performance of 20Gbps per host meets the needs of micro-segmentation, and automation addresses the operational challenges of managing thousands of policies
Design patterns provide reusable solutions to common problems in software design. The Gang of Four patterns include creational, structural, and behavioral patterns that address problems like object creation, composition, and communication. Cryptography uses encryption algorithms and keys to secure data transmission and storage. Symmetric encryption uses a single private key while asymmetric encryption uses public/private key pairs. Common algorithms like AES and RSA are available in .NET.
The Hive Think Tank - The Microsoft Big Data Stack by Raghu Ramakrishnan, CTO...The Hive
Until recently, data was gathered for well-defined objectives such as auditing, forensics, reporting and line-of-business operations; now, exploratory and predictive analysis is becoming ubiquitous, and the default increasingly is to capture and store any and all data, in anticipation of potential future strategic value. These differences in data heterogeneity, scale and usage are leading to a new generation of data management and analytic systems, where the emphasis is on supporting a wide range of very large datasets that are stored uniformly and analyzed seamlessly using whatever techniques are most appropriate, including traditional tools like SQL and BI and newer tools, e.g., for machine learning and stream analytics. These new systems are necessarily based on scale-out architectures for both storage and computation.
Hadoop has become a key building block in the new generation of scale-out systems. On the storage side, HDFS has provided a cost-effective and scalable substrate for storing large heterogeneous datasets. However, as key customer and systems touch points are instrumented to log data, and Internet of Things applications become common, data in the enterprise is growing at a staggering pace, and the need to leverage different storage tiers (ranging from tape to main memory) is posing new challenges, leading to caching technologies, such as Spark. On the analytics side, the emergence of resource managers such as YARN has opened the door for analytics tools to bypass the Map-Reduce layer and directly exploit shared system resources while computing close to data copies. This trend is especially significant for iterative computations such as graph analytics and machine learning, for which Map-Reduce is widely recognized to be a poor fit.
While Hadoop is widely recognized and used externally, Microsoft has long been at the forefront of Big Data analytics, with Cosmos and Scope supporting all internal customers. These internal services are a key part of our strategy going forward, and are enabling new state of the art external-facing services such as Azure Data Lake and more. I will examine these trends, and ground the talk by discussing the Microsoft Big Data stack.
This document summarizes a presentation given by Rohan Nandi on security in embedded systems. The presentation covered what embedded systems are, an introduction to network security, why embedded system security is currently lacking and vulnerabilities. It also discussed countermeasures to avoid attacks, a proposed hardware-software solution, comparisons to existing software-only solutions, challenges, future scope, and references.
Magiclock: Scalable Detection of Potential Deadlocks in Large-Scale Multithre...KaashivInfoTech Company
The document presents Magiclock, a technique for detecting potential deadlocks in large multithreaded programs. Magiclock analyzes execution traces without any actual deadlocks occurring. It iteratively eliminates unnecessary lock dependencies and partitions lock dependencies by thread to efficiently detect potential deadlock chains without examining duplicate permutations. The experimental results showed Magiclock is more scalable and efficient than existing dynamic detectors.
The document discusses the NetWitness network security platform. It provides situational awareness and deep visibility into network activity to detect advanced threats. When deployed, NetWitness immediately provides insight into what is happening on a network through its NextGen platform. This platform records all network data, filters it, and organizes it into a searchable framework to enable analysis, reporting, and visualization of network traffic. It uses various components and applications to interrogate the data, detect anomalies, and gain intelligence about security issues.
Denodo DataFest 2017: Lowering IT Costs with Big Data and Cloud ModernizationDenodo
Watch the live presentation on-demand now: https://goo.gl/QanW35
Organizations are fast adapting cloud to lower the IT costs, and increase agility.
Watch this Denodo DataFest 2017 session to discover:
• How Logitech migrated their on-premise data warehouse and big data systems to the cloud and minimizing costs and immensely improved their time-to-market.
• The four main challenges Logitech faced when moving their data to the cloud.
• The benefits of adding a data virtualization layer to your data architecure.
This document provides an overview of designing Internet of Things (IoT) systems. It begins with definitions and then describes the key components of an IoT architecture including devices, communication protocols, platforms, and programming languages. Example open source platforms are also discussed. The presentation aims to provide a general understanding of creating IoT prototypes and selecting suitable technologies. Security, analytics, cognitive capabilities and solutions templates are also reviewed at a high level. The overall goal is to help understand the big picture of designing IoT systems and connect concepts to daily work.
Zapata Technology provides advanced technology solutions and expertise to US government agencies and the defense sector. It develops customized systems, software, and tools to support critical missions around the world. Some of its key products and services include data ingestion tools, monitoring systems, object recognition software, report generation AI, and engineering and testing support. Zapata works on various contracts with organizations like the DoD, Army, Navy, and intelligence community.
Next-Gen Cloud Analytics with AWS, Big Data and Data VirtualizationDenodo
Watch Tekin's keynote presentation from Fast Data Strategy Virtual Summit here: https://goo.gl/RJon7n
The Denodo Platform for AWS enabled Logitech's cloud journey with minimal impact on business operations. The Denodo Platform acts a big data fabric layer and sources data for all of Logitech's analytics initiatives from descriptive to prescriptive to predictive analytics including NLP processing engines.
Attend this session to learn how Logitech:
• Reduced TCO such as infrastructure and operational expenses
• Empowered their business users with advanced analytics capabilities
• Uses AWS and Denodo as their innovation engine
The document provides an overview of leading big data companies in 2021 and the Apache Hadoop stack, including related Apache software and the NIST big data reference architecture. It lists over 50 big data companies, including Accenture, Actian, Aerospike, Alluxio, Amazon Web Services, Cambridge Semantics, Cloudera, Cloudian, Cockroach Labs, Collibra, Couchbase, Databricks, DataKitchen, DataStax, Denodo, Dremio, Franz, Gigaspaces, Google Cloud, GridGain, HPE, HVR, IBM, Immuta, InfluxData, Informatica, IRI, MariaDB, Matillion, Melissa Data
Extending Cloudera SDX beyond the PlatformCloudera, Inc.
Cloudera SDX is by no means no restricted to just the platform; it extends well beyond. In this webinar, we show you how Bardess Group’s Zero2Hero solution leverages the shared data experience to coordinate Cloudera, Trifacta, and Qlik to deliver complete customer insight.
IRJET- Review on Privacy Preserving on Multi Keyword Search over Encrypte...IRJET Journal
The document summarizes a proposed system for multi-keyword search over encrypted data in cloud computing. It aims to retrieve the top k most relevant documents matching a user's query while preserving data privacy. The system uses Lucene indexing to build an index of keywords extracted from outsourced documents. When documents are added or removed, the index is updated. A top-k query technique ranks document relevance and returns the top matching results. Encryption is done using the Blowfish algorithm before documents are outsourced to the untrusted cloud server. This allows efficient search over the encrypted data based on keyword queries.
SAP Sybase IQ is an analytic database management system designed for advanced analytics, data warehousing, and business intelligence environments. It can handle massive volumes of structured and unstructured data. Key features include its column-based storage which provides faster performance than row-based databases, massively parallel processing capabilities, and the ability to integrate results from Hadoop frameworks and execute R libraries and predictive models within the database. These features allow Sybase IQ to meet the growing needs of analyzing large and diverse datasets, commonly referred to as big data.
ScyllaDB is making a major architecture shift. We’re moving from vNode replication to tablets – fragments of tables that are distributed independently, enabling dynamic data distribution and extreme elasticity. In this keynote, ScyllaDB co-founder and CTO Avi Kivity explains the reason for this shift, provides a look at the implementation and roadmap, and shares how this shift benefits ScyllaDB users.
Northern Engraving | Modern Metal Trim, Nameplates and Appliance PanelsNorthern Engraving
What began over 115 years ago as a supplier of precision gauges to the automotive industry has evolved into being an industry leader in the manufacture of product branding, automotive cockpit trim and decorative appliance trim. Value-added services include in-house Design, Engineering, Program Management, Test Lab and Tool Shops.
Lee Barnes - Path to Becoming an Effective Test Automation Engineer.pdfleebarnesutopia
So… you want to become a Test Automation Engineer (or hire and develop one)? While there’s quite a bit of information available about important technical and tool skills to master, there’s not enough discussion around the path to becoming an effective Test Automation Engineer that knows how to add VALUE. In my experience this had led to a proliferation of engineers who are proficient with tools and building frameworks but have skill and knowledge gaps, especially in software testing, that reduce the value they deliver with test automation.
In this talk, Lee will share his lessons learned from over 30 years of working with, and mentoring, hundreds of Test Automation Engineers. Whether you’re looking to get started in test automation or just want to improve your trade, this talk will give you a solid foundation and roadmap for ensuring your test automation efforts continuously add value. This talk is equally valuable for both aspiring Test Automation Engineers and those managing them! All attendees will take away a set of key foundational knowledge and a high-level learning path for leveling up test automation skills and ensuring they add value to their organizations.
Northern Engraving | Nameplate Manufacturing Process - 2024Northern Engraving
Manufacturing custom quality metal nameplates and badges involves several standard operations. Processes include sheet prep, lithography, screening, coating, punch press and inspection. All decoration is completed in the flat sheet with adhesive and tooling operations following. The possibilities for creating unique durable nameplates are endless. How will you create your brand identity? We can help!
What is an RPA CoE? Session 2 – CoE RolesDianaGray10
In this session, we will review the players involved in the CoE and how each role impacts opportunities.
Topics covered:
• What roles are essential?
• What place in the automation journey does each role play?
Speaker:
Chris Bolin, Senior Intelligent Automation Architect Anika Systems
The Department of Veteran Affairs (VA) invited Taylor Paschal, Knowledge & Information Management Consultant at Enterprise Knowledge, to speak at a Knowledge Management Lunch and Learn hosted on June 12, 2024. All Office of Administration staff were invited to attend and received professional development credit for participating in the voluntary event.
The objectives of the Lunch and Learn presentation were to:
- Review what KM ‘is’ and ‘isn’t’
- Understand the value of KM and the benefits of engaging
- Define and reflect on your “what’s in it for me?”
- Share actionable ways you can participate in Knowledge - - Capture & Transfer
The Microsoft 365 Migration Tutorial For Beginner.pptxoperationspcvita
This presentation will help you understand the power of Microsoft 365. However, we have mentioned every productivity app included in Office 365. Additionally, we have suggested the migration situation related to Office 365 and how we can help you.
You can also read: https://www.systoolsgroup.com/updates/office-365-tenant-to-tenant-migration-step-by-step-complete-guide/
Introducing BoxLang : A new JVM language for productivity and modularity!Ortus Solutions, Corp
Just like life, our code must adapt to the ever changing world we live in. From one day coding for the web, to the next for our tablets or APIs or for running serverless applications. Multi-runtime development is the future of coding, the future is to be dynamic. Let us introduce you to BoxLang.
Dynamic. Modular. Productive.
BoxLang redefines development with its dynamic nature, empowering developers to craft expressive and functional code effortlessly. Its modular architecture prioritizes flexibility, allowing for seamless integration into existing ecosystems.
Interoperability at its Core
With 100% interoperability with Java, BoxLang seamlessly bridges the gap between traditional and modern development paradigms, unlocking new possibilities for innovation and collaboration.
Multi-Runtime
From the tiny 2m operating system binary to running on our pure Java web server, CommandBox, Jakarta EE, AWS Lambda, Microsoft Functions, Web Assembly, Android and more. BoxLang has been designed to enhance and adapt according to it's runnable runtime.
The Fusion of Modernity and Tradition
Experience the fusion of modern features inspired by CFML, Node, Ruby, Kotlin, Java, and Clojure, combined with the familiarity of Java bytecode compilation, making BoxLang a language of choice for forward-thinking developers.
Empowering Transition with Transpiler Support
Transitioning from CFML to BoxLang is seamless with our JIT transpiler, facilitating smooth migration and preserving existing code investments.
Unlocking Creativity with IDE Tools
Unleash your creativity with powerful IDE tools tailored for BoxLang, providing an intuitive development experience and streamlining your workflow. Join us as we embark on a journey to redefine JVM development. Welcome to the era of BoxLang.
QA or the Highway - Component Testing: Bridging the gap between frontend appl...zjhamm304
These are the slides for the presentation, "Component Testing: Bridging the gap between frontend applications" that was presented at QA or the Highway 2024 in Columbus, OH by Zachary Hamm.
"Frontline Battles with DDoS: Best practices and Lessons Learned", Igor IvaniukFwdays
At this talk we will discuss DDoS protection tools and best practices, discuss network architectures and what AWS has to offer. Also, we will look into one of the largest DDoS attacks on Ukrainian infrastructure that happened in February 2022. We'll see, what techniques helped to keep the web resources available for Ukrainians and how AWS improved DDoS protection for all customers based on Ukraine experience
How information systems are built or acquired puts information, which is what they should be about, in a secondary place. Our language adapted accordingly, and we no longer talk about information systems but applications. Applications evolved in a way to break data into diverse fragments, tightly coupled with applications and expensive to integrate. The result is technical debt, which is re-paid by taking even bigger "loans", resulting in an ever-increasing technical debt. Software engineering and procurement practices work in sync with market forces to maintain this trend. This talk demonstrates how natural this situation is. The question is: can something be done to reverse the trend?
"$10 thousand per minute of downtime: architecture, queues, streaming and fin...Fwdays
Direct losses from downtime in 1 minute = $5-$10 thousand dollars. Reputation is priceless.
As part of the talk, we will consider the architectural strategies necessary for the development of highly loaded fintech solutions. We will focus on using queues and streaming to efficiently work and manage large amounts of data in real-time and to minimize latency.
We will focus special attention on the architectural patterns used in the design of the fintech system, microservices and event-driven architecture, which ensure scalability, fault tolerance, and consistency of the entire system.
Discover the Unseen: Tailored Recommendation of Unwatched ContentScyllaDB
The session shares how JioCinema approaches ""watch discounting."" This capability ensures that if a user watched a certain amount of a show/movie, the platform no longer recommends that particular content to the user. Flawless operation of this feature promotes the discover of new content, improving the overall user experience.
JioCinema is an Indian over-the-top media streaming service owned by Viacom18.