Mouaz Alnouri presented on using big data technologies for cybersecurity. He discussed how cybersecurity poses big data challenges due to the volume, velocity, and variety of security data. Skilledfield helps clients address these challenges by designing analytics pipelines to acquire, parse, enrich, analyze and alert on security data. They also implement techniques like threat modeling, behavioral analytics and machine learning to detect threats. Unleashing big data technologies can help organizations improve security detection, response and visibility to protect against emerging cyber threats.
DATA SCIENCE METHODOLOGY FOR CYBERSECURITY PROJECTS cscpconf
Cybersecurity solutions are traditionally static and signature-based. The traditional solutions
along with the use of analytic models, machine learning and big data could be improved by
automatically trigger mitigation or provide relevant awareness to control or limit consequences
of threats. This kind of intelligent solutions is covered in the context of Data Science for
Cybersecurity. Data Science provides a significant role in cybersecurity by utilising the power
of data (and big data), high-performance computing and data mining (and machine learning) to
protect users against cybercrimes. For this purpose, a successful data science project requires
an effective methodology to cover all issues and provide adequate resources. In this paper, we
are introducing popular data science methodologies and will compare them in accordance with
cybersecurity challenges. A comparison discussion has also delivered to explain methodologies’
strengths and weaknesses in case of cybersecurity projects.
Wolters Kluwer and Risk.Net present the current challenges, priorities and trends influencing banks’ investment in risktech and assesses how they can drive better value in the future. Survey report.
IoT - Data Management Trends, Best Practices, & Use CasesCloudera, Inc.
With billions of new devices, IoT is transforming how businesses capitalize on data. Data driven organizations are using IoT as as a means to improve their customer experience, drive operational efficiencies, and enable new business models. However, without the right data management strategy and tools, investments in IoT can yield limited results.
Join Cloudera and 451 Research for a joint webinar to learn more about some of the data management best practices and how organizations are using advanced analytics and machine learning to enable IoT use cases.
Streaming Cyber Security into Graph: Accelerating Data into DataStax Graph an...Keith Kraus
Traditional security tools like security information and event managers (SIEMs) are struggling to keep up with the terabytes of event data (250M to 2B events) being generated each day from an ever-growing number of devices. Cybersecurity has become a data problem, and enterprises need to reply with scalable solutions to enable effective hunting and combat evolving attacks. Rethinking the cybersecurity problem as a data-centric problem led Accenture Labs’s Cybersecurity team to use emerging big data tools along with new approaches such as graph databases and analysis to exploit the connected nature of the data to its advantage. Joshua Patterson, Michael Wendt, and Keith Kraus explain how Accenture Labs’s Cybersecurity team is using Apache Kafka, Spark, and Flink to stream data into Blazegraph and Datastax Graph to accelerate cyber defense.
Leveraging Datastax Graph and Blazegraph allows Accenture Labs to greatly accelerate query and analysis performance compared to traditional security tools like SIEM. Josh, Michael, and Keith share the challenges of fitting cybersecurity data into each of the graph structures, as well as the ways they exploited the connectedness of events to discover new threats that would have been missed in traditional SIEM tools. In addition, they explain how they use GPUs to accelerate graph analysis by using Blazegraph DASL. Josh, Michael, and Keith end by demonstrating how to efficiently and effectively stream data into these graph databases using best-in-breed technologies such as Apache Kafka, Spark, and Flink and touch on why Kudu is becoming an integral part of Accenture’s technology stack. Utilizing these technologies, clients have supercharged their security analysts’ cyber-hunting abilities and are uncovering threats faster.
Transform Banking with Big Data and Automated Machine Learning 9.12.17Cloudera, Inc.
Banks are rich in valuable data and can build and maintain a competitive advantage by identifying and executing on high-value machine learning projects leveraging the rich data available.This webinar will describe use cases fit for big data and machine learning in the banking sector (commercial, consumer, regulatory, and markets) and the impact they can have for your organization.
3 things to learn:
* How to create a next generation data platform and why it is important
* How to monetize big data using predictive modeling and machine learning
* What is needed for automated machine learning as a sustainable, cost-effective, and efficient solution
DATA SCIENCE METHODOLOGY FOR CYBERSECURITY PROJECTS cscpconf
Cybersecurity solutions are traditionally static and signature-based. The traditional solutions
along with the use of analytic models, machine learning and big data could be improved by
automatically trigger mitigation or provide relevant awareness to control or limit consequences
of threats. This kind of intelligent solutions is covered in the context of Data Science for
Cybersecurity. Data Science provides a significant role in cybersecurity by utilising the power
of data (and big data), high-performance computing and data mining (and machine learning) to
protect users against cybercrimes. For this purpose, a successful data science project requires
an effective methodology to cover all issues and provide adequate resources. In this paper, we
are introducing popular data science methodologies and will compare them in accordance with
cybersecurity challenges. A comparison discussion has also delivered to explain methodologies’
strengths and weaknesses in case of cybersecurity projects.
Wolters Kluwer and Risk.Net present the current challenges, priorities and trends influencing banks’ investment in risktech and assesses how they can drive better value in the future. Survey report.
IoT - Data Management Trends, Best Practices, & Use CasesCloudera, Inc.
With billions of new devices, IoT is transforming how businesses capitalize on data. Data driven organizations are using IoT as as a means to improve their customer experience, drive operational efficiencies, and enable new business models. However, without the right data management strategy and tools, investments in IoT can yield limited results.
Join Cloudera and 451 Research for a joint webinar to learn more about some of the data management best practices and how organizations are using advanced analytics and machine learning to enable IoT use cases.
Streaming Cyber Security into Graph: Accelerating Data into DataStax Graph an...Keith Kraus
Traditional security tools like security information and event managers (SIEMs) are struggling to keep up with the terabytes of event data (250M to 2B events) being generated each day from an ever-growing number of devices. Cybersecurity has become a data problem, and enterprises need to reply with scalable solutions to enable effective hunting and combat evolving attacks. Rethinking the cybersecurity problem as a data-centric problem led Accenture Labs’s Cybersecurity team to use emerging big data tools along with new approaches such as graph databases and analysis to exploit the connected nature of the data to its advantage. Joshua Patterson, Michael Wendt, and Keith Kraus explain how Accenture Labs’s Cybersecurity team is using Apache Kafka, Spark, and Flink to stream data into Blazegraph and Datastax Graph to accelerate cyber defense.
Leveraging Datastax Graph and Blazegraph allows Accenture Labs to greatly accelerate query and analysis performance compared to traditional security tools like SIEM. Josh, Michael, and Keith share the challenges of fitting cybersecurity data into each of the graph structures, as well as the ways they exploited the connectedness of events to discover new threats that would have been missed in traditional SIEM tools. In addition, they explain how they use GPUs to accelerate graph analysis by using Blazegraph DASL. Josh, Michael, and Keith end by demonstrating how to efficiently and effectively stream data into these graph databases using best-in-breed technologies such as Apache Kafka, Spark, and Flink and touch on why Kudu is becoming an integral part of Accenture’s technology stack. Utilizing these technologies, clients have supercharged their security analysts’ cyber-hunting abilities and are uncovering threats faster.
Transform Banking with Big Data and Automated Machine Learning 9.12.17Cloudera, Inc.
Banks are rich in valuable data and can build and maintain a competitive advantage by identifying and executing on high-value machine learning projects leveraging the rich data available.This webinar will describe use cases fit for big data and machine learning in the banking sector (commercial, consumer, regulatory, and markets) and the impact they can have for your organization.
3 things to learn:
* How to create a next generation data platform and why it is important
* How to monetize big data using predictive modeling and machine learning
* What is needed for automated machine learning as a sustainable, cost-effective, and efficient solution
The Quality “Logs”-Jam: Why Alerting for Cybersecurity is Awash with False Po...Mark Underwood
What happens when the (Observe) Plan-Do-Check-Adjust cycle is undermined by lapses in data integrity? Observations are questioned. Plans may be ill-conceived. Actions may be undertaken that undermine rather than enhance. “Checks” can fail. Adjustments may be guesswork. In cybersecurity, the results of poor data integrity can be expensive outages, ransom requests, breaches, fines -- even bankruptcy (think Cambridge Analytica). But data integrity issues take many forms, ranging from benign to malicious. The full range of these issues is surveyed from a cybersecurity perspective, where logs and alerts are critical for defenders -- as well as quality engineers . Techniques borrowed from model-based systems engineering and ontology AI to are identified that can mitigate these deleterious effects on PDCA.
Digital Transformation (Implications for the CXO)Anant Desai
Digital transformation refers to the organizational change that occurs through the use of digital technologies and business models to improve the organizational performance.
The Big Picture: Real-time Data is Defining Intelligent OffersCloudera, Inc.
New research shows that 57% of the buying cycle is completed before a prospect even speaks to a company. Marketers already know this, Ninety-six percent (96%) of organizations believe that email personalization can improve email marketing performance. But where do we get this increasingly personal direction? The answer is likely in your customer data. In order to understand your customer needs contextualized in the moment they feel the need to act you will require a platform that can leverage real-time data. Apache Kudu is a Cloudera component that makes dealing with quickly changing data fast and easy. Companies are leveraging next generation data stores like Kudu to build data applications that deliver smart promotions, real-time offers, and personalized marketing. Join us as we discuss modern approaches to real-time application development and highlight key Cloudera use cases being powered by Cloudera’s operational database.
MT81 Keys to Successful Enterprise IoT InitiativesDell EMC World
Success with enterprise Internet of Things (IoT) initiatives begins with strong partnerships between IT and operations technology (OT) organizations and identifying relevant use cases with measurable ROI. Next, choosing the right IoT architecture and technology requires determining the capabilities are needed at the edge and what are needed in the cloud and datacenter to minimize cost and enable analytics-driven action. This session will discusses the challenges involved with introducing sensors and smart devices into your network, including building infrastructure and analytics capabilities , and securing data and applications. Learn how Dell'S IoT-specific gateways, edge analytics software and infrastructure solutions provide flexible architecture options for multiple IoT use cases.
Digital Alpha is a leading technology and consulting services firm headquartered in New York. We provide solutions for:
- Asset Management companies
- Digital Health-Tech firms
Backed by the best industry minds from wall street companies like Bloomberg, Goldman Sachs, McKinsey, J.P Morgan, and Deloitte - we help enterprises take advantage of the data and digital paradigm to generate new levers that will accelerate growth.
One of the critical aspects of adopting a digital ecosystem is modernizing or enhancing legacy business suites through evolving technology platforms and frameworks to endure in this digital age. We leverage our integrated array of IT solutions, accelerators, and software expertise to achieve a technological breakthrough and enable companies with a more agile transformation.
Our actionable strategy with data-driven methodologies help you to solve the most complex problems in the following disciplines:
- Data Engineering
- Platform Engineering
- Business Operations Automation
Small businesses face their own set of unique challenges, especially when it comes to IT. Learn the eight common IT challenges, from implementing the cloud to connecting a mobile workforce, and how today's businesses can solve them. This SlideShare highlights key points from our on-demand webinar, "Solving Your IT Challenges": ms.spr.ly/6003T633X
The global pandemic caused swift, radical changes in IT and business operations to ensure business continuity. Was IT ready for the challenges?
Learn more: http://ms.spr.ly/6004TYws0
MBT Webinar: Does the security of your business data keep you up at night? Jorge García
More and more manufacturers have been investing in cloud technology these days, but there is still a contingent of businesses who don’t see the appeal, or are concerned about the risks. In a recent MBT survey about cloud adoption, 50 percent of those manufacturers not using cloud computing said they didn’t because of security concerns. But are these concerns actually justified, or are businesses leaving opportunity on the table due to glaring misconceptions?
The slide has details on below points:
1. Introduction to Machine Learning
2. What are the challenges in acceptance of Machine Learning in Banks
3. How to overcome the challenges in adoption of Machine Learning in Banks
4. How to find new use cases of Machine Learning
5. Few current interesting use cases of Machine Learning
Please contact me (shekup@gmail.com) or connect with me on LinkedIn (https://www.linkedin.com/in/shekup/) for more explanation on ML and how it may help your business.
The slides are inspired by:
Survey & interviews done by me with Bankers & Technology Professionals
Presentation from Google NEXT 2017
Presentation by DATUM on Youtube
Royal Society Machine Learning
Big Data & Social Analytics Course from MIT & GetSmarter
Join us next Wednesday (register at http://clearedjobs.net/jobfair-information/83) at the Baltimore Convention Center to meet with 22 of the MidAtlantic's leading cyber employers. Cyber Job Fair attendance is FREE.
The Job Seeker Handbook contains a listing of all employers and the cleared jobs they will be seeking to fill at the Cyber Job Fair. Cybersecurity experience or degree required.
The Cyber Job Fair is for both cleared and non-cleared cyber professionals.
Industry experts share how to embrace the coming merger of information technology (IT) and operation technology (OT) – originally, two very distinct domains of business.
Read more at: http://tripwire.me/adaptitot and www.belden.com/adaptitot
These are slides used for a 15-min presentation made to Banking and Financial Services leaders at a virtual event hosted by Digital Banking Leadership Council on April 06, 2017
Microservices are an effective approach to orchestrate services in the cloud. The microservices architectural style is an approach to develop a single application as a suite of small services, each running in its own process and communicating with lightweight mechanisms ( API ).
To be more effective they need a contextual evaluation of the meaning of data of IoT generating always more data.Machine Learning can support Microservices to extract meaning from Big Data making Microservices smarter and speedier. Industries can have huge benefits from this approach.
Meetup introduction to elastic stack - search at scale - skilledfield slide...Mouaz Alnouri
Now, without a doubt, given exponential data growth, there’s increased demand for relevant, real-time insights. We all know this.
Elastic Stack is one of the best solutions with powerful search capabilities. It provides the opportunities to centralise data and consequently make actionable decisions.
In this meetup we will walk through Elastic Stack, to help you better understand how to make the best use of the solution. This meetup will cover:
-What is Elastic Stack and what problems it can solve
-How can data analysts/scientists benefit from Elastic Stack
-A demo
The Quality “Logs”-Jam: Why Alerting for Cybersecurity is Awash with False Po...Mark Underwood
What happens when the (Observe) Plan-Do-Check-Adjust cycle is undermined by lapses in data integrity? Observations are questioned. Plans may be ill-conceived. Actions may be undertaken that undermine rather than enhance. “Checks” can fail. Adjustments may be guesswork. In cybersecurity, the results of poor data integrity can be expensive outages, ransom requests, breaches, fines -- even bankruptcy (think Cambridge Analytica). But data integrity issues take many forms, ranging from benign to malicious. The full range of these issues is surveyed from a cybersecurity perspective, where logs and alerts are critical for defenders -- as well as quality engineers . Techniques borrowed from model-based systems engineering and ontology AI to are identified that can mitigate these deleterious effects on PDCA.
Digital Transformation (Implications for the CXO)Anant Desai
Digital transformation refers to the organizational change that occurs through the use of digital technologies and business models to improve the organizational performance.
The Big Picture: Real-time Data is Defining Intelligent OffersCloudera, Inc.
New research shows that 57% of the buying cycle is completed before a prospect even speaks to a company. Marketers already know this, Ninety-six percent (96%) of organizations believe that email personalization can improve email marketing performance. But where do we get this increasingly personal direction? The answer is likely in your customer data. In order to understand your customer needs contextualized in the moment they feel the need to act you will require a platform that can leverage real-time data. Apache Kudu is a Cloudera component that makes dealing with quickly changing data fast and easy. Companies are leveraging next generation data stores like Kudu to build data applications that deliver smart promotions, real-time offers, and personalized marketing. Join us as we discuss modern approaches to real-time application development and highlight key Cloudera use cases being powered by Cloudera’s operational database.
MT81 Keys to Successful Enterprise IoT InitiativesDell EMC World
Success with enterprise Internet of Things (IoT) initiatives begins with strong partnerships between IT and operations technology (OT) organizations and identifying relevant use cases with measurable ROI. Next, choosing the right IoT architecture and technology requires determining the capabilities are needed at the edge and what are needed in the cloud and datacenter to minimize cost and enable analytics-driven action. This session will discusses the challenges involved with introducing sensors and smart devices into your network, including building infrastructure and analytics capabilities , and securing data and applications. Learn how Dell'S IoT-specific gateways, edge analytics software and infrastructure solutions provide flexible architecture options for multiple IoT use cases.
Digital Alpha is a leading technology and consulting services firm headquartered in New York. We provide solutions for:
- Asset Management companies
- Digital Health-Tech firms
Backed by the best industry minds from wall street companies like Bloomberg, Goldman Sachs, McKinsey, J.P Morgan, and Deloitte - we help enterprises take advantage of the data and digital paradigm to generate new levers that will accelerate growth.
One of the critical aspects of adopting a digital ecosystem is modernizing or enhancing legacy business suites through evolving technology platforms and frameworks to endure in this digital age. We leverage our integrated array of IT solutions, accelerators, and software expertise to achieve a technological breakthrough and enable companies with a more agile transformation.
Our actionable strategy with data-driven methodologies help you to solve the most complex problems in the following disciplines:
- Data Engineering
- Platform Engineering
- Business Operations Automation
Small businesses face their own set of unique challenges, especially when it comes to IT. Learn the eight common IT challenges, from implementing the cloud to connecting a mobile workforce, and how today's businesses can solve them. This SlideShare highlights key points from our on-demand webinar, "Solving Your IT Challenges": ms.spr.ly/6003T633X
The global pandemic caused swift, radical changes in IT and business operations to ensure business continuity. Was IT ready for the challenges?
Learn more: http://ms.spr.ly/6004TYws0
MBT Webinar: Does the security of your business data keep you up at night? Jorge García
More and more manufacturers have been investing in cloud technology these days, but there is still a contingent of businesses who don’t see the appeal, or are concerned about the risks. In a recent MBT survey about cloud adoption, 50 percent of those manufacturers not using cloud computing said they didn’t because of security concerns. But are these concerns actually justified, or are businesses leaving opportunity on the table due to glaring misconceptions?
The slide has details on below points:
1. Introduction to Machine Learning
2. What are the challenges in acceptance of Machine Learning in Banks
3. How to overcome the challenges in adoption of Machine Learning in Banks
4. How to find new use cases of Machine Learning
5. Few current interesting use cases of Machine Learning
Please contact me (shekup@gmail.com) or connect with me on LinkedIn (https://www.linkedin.com/in/shekup/) for more explanation on ML and how it may help your business.
The slides are inspired by:
Survey & interviews done by me with Bankers & Technology Professionals
Presentation from Google NEXT 2017
Presentation by DATUM on Youtube
Royal Society Machine Learning
Big Data & Social Analytics Course from MIT & GetSmarter
Join us next Wednesday (register at http://clearedjobs.net/jobfair-information/83) at the Baltimore Convention Center to meet with 22 of the MidAtlantic's leading cyber employers. Cyber Job Fair attendance is FREE.
The Job Seeker Handbook contains a listing of all employers and the cleared jobs they will be seeking to fill at the Cyber Job Fair. Cybersecurity experience or degree required.
The Cyber Job Fair is for both cleared and non-cleared cyber professionals.
Industry experts share how to embrace the coming merger of information technology (IT) and operation technology (OT) – originally, two very distinct domains of business.
Read more at: http://tripwire.me/adaptitot and www.belden.com/adaptitot
These are slides used for a 15-min presentation made to Banking and Financial Services leaders at a virtual event hosted by Digital Banking Leadership Council on April 06, 2017
Microservices are an effective approach to orchestrate services in the cloud. The microservices architectural style is an approach to develop a single application as a suite of small services, each running in its own process and communicating with lightweight mechanisms ( API ).
To be more effective they need a contextual evaluation of the meaning of data of IoT generating always more data.Machine Learning can support Microservices to extract meaning from Big Data making Microservices smarter and speedier. Industries can have huge benefits from this approach.
Meetup introduction to elastic stack - search at scale - skilledfield slide...Mouaz Alnouri
Now, without a doubt, given exponential data growth, there’s increased demand for relevant, real-time insights. We all know this.
Elastic Stack is one of the best solutions with powerful search capabilities. It provides the opportunities to centralise data and consequently make actionable decisions.
In this meetup we will walk through Elastic Stack, to help you better understand how to make the best use of the solution. This meetup will cover:
-What is Elastic Stack and what problems it can solve
-How can data analysts/scientists benefit from Elastic Stack
-A demo
PLAY TO WIN
In Business, As In Chess, Forethought Wins
Showcasing exemplary stories of success where channel partners have gone to great lengths to implement innovative solutions. Acclaiming those partners who have risen to the challenges of the digital era and transformed their business to a solutions offering. Inspiring channel businesses to become value-added providers and trusted allies to their customers. Stories that made a Difference.
Building Elastic into security operationsElasticsearch
Learn how Optiv took foundational ideas around optimization of data ingestion, automation, and search to build world-class managed cybersecurity services with Elastic.
Protecting health and life science organizations from breaches and ransomwareCloudera, Inc.
3 Things to Learn About:
* 1. Ransomware is a particular problem and currently the highest priority for healthcare organizations. Machine learning can use the structure of a malicious email to detect an attack even before the email is opened.
* 2. Big data architectures provide the machine-learning models with the volume and variety of data required to achieve complete visibility across the spectrum of IT activity—from packets to logs to alerts.
* 3. Intel and industry partners are currently running one-hour, complimentary, confidential benchmark engagements for HLS organizations that want to see how their security compares with the industry .
Read "Asset intelligence: What it is and why it is critical now" and read how innovative organisations are maximising return on assets and extending their competitive edge.
Please note this is an extract only. To download the complete article go to:
http://www.assetdna.com/content/industry-whitepaper
Project 3 – Hollywood and IT· Find 10 incidents of Hollywood p.docxstilliegeorgiana
Project 3 – Hollywood and IT
· Find 10 incidents of Hollywood portraying IT security incorrectly
· You can use movies or TV episodes
· Write 2-5 paragraphs for each incident. Use supporting citations for each part.
· What has Hollywood portrayed wrong? Describe the scene and what is being shown. Make sure to state whether it is partially wrong or totally fictitious.
· How would you protect/secure against what they show (answers might include install firewall, load Antivirus etc.)
· Use APA formatting for your sources on everything.
· Make sure to put your name on assignment.
Big Data and Social Media
Colgate Palmolive
Agenda Of socail media use
Buisness intellegence and Social media concenpts
Intellegent organization
Data Anaylysis and Data trustworthiness
Conclusion
Buisness intellegence and Social media concenpts
No-Hassle Documentation
Gain Trusted Followers
Spy on Competition
Learn Customer Demographics
Research and Analyze Events
Advertise More Accurately
Intellegent organization
They consistently use (big) data proactively
They know exactly where they want to go: all-round vision
They continuously discuss business matters: alignment
They talk to each other regarding positive and negative performance
They know their customers through and through
They think and work in an agile way
Data Anaylysis and Data trustworthiness
Data completeness and accuracy
Data credibility
Data consistency
Data processing and algorithms
Data Validity
Conclusion
How Colgate benefit from Big Data and Social Media
Social media increases sales and customers
Big data shows popular trends and popular companies
All around they are both beneficial
Big Data can find trends that can benefit you greatly
Criteria
Title Page:
Name, Contact info, title of Presentation
Slide 1
Adenda : Topic you going to cover in order
Slide 2
Discuss how big data, social media concepts and knowledge to successfully create business intellegence (Support your bullets points with data, analysis, charts)
Slide 3
Describe how big data can be used to build an intelligent organization
Slide 4
Discuss the importance of data source trustworthiness and data analysis
Slide 5
Conclusion
Slide 6
Big Data And Business Intelligence
Business Value With Big Data
For business to survive in a competitive environment, organizational change requires improved governance, sponsorship, processes, and controls, in addition to new skill sets and technology all work in harmony to deliver the benefits of big data. See Fig. 13.2
Data science has taken the business world by storm. Every field of study and area of business has been affected as companies realize the value of the incredible quantities of data being generated. But to extract value from those data, one needs to be trained in the proper data science skills. The R programming language has become the de fac to programming language for data science. Its flexibility, power, sophistication, and expressiveness have ma ...
Digital Transformation: How to Run Best-in-Class IT Operations in a World of ...Precisely
IT leaders looking to move beyond reactive and ad hoc troubleshooting need to find the intersection of maintaining existing systems while still driving innovation - solving for the present while preparing for the future. Identifying ways to bring existing infrastructure and legacy systems into the modern world can create the business advantage you need.
View the conversation with Splunk’s Chief Technology Advocate, Andi Mann and Syncsort’s Chief Product Officer, David Hodgson where we discuss the digital transformation taking place in IT and how machine learning and AI are helping IT leaders create a more business-centric view of their world including:
• The importance of data sharing and collaboration between mainframe and distributed IT
• The value of integrating legacy data sources and existing infrastructure into the modern world
• Achieving an end to end view of IT operations and application performance with machine learning
How Data Virtualization Puts Machine Learning into Production (APAC)Denodo
Watch full webinar here: https://bit.ly/3mJJ4w9
Advanced data science techniques, like machine learning, have proven an extremely useful tool to derive valuable insights from existing data. Platforms like Spark, and complex libraries for R, Python and Scala put advanced techniques at the fingertips of the data scientists. However, these data scientists spend most of their time looking for the right data and massaging it into a usable format. Data virtualization offers a new alternative to address these issues in a more efficient and agile way.
Attend this session to learn how companies can use data virtualization to:
- Create a logical architecture to make all enterprise data available for advanced analytics exercise
- Accelerate data acquisition and massaging, providing the data scientist with a powerful tool to complement their practice
- Integrate popular tools from the data science ecosystem: Spark, Python, Zeppelin, Jupyter, etc
Similar to Big data for cybersecurity - skilledfield slides - 25032021 (20)
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
Explore our comprehensive data analysis project presentation on predicting product ad campaign performance. Learn how data-driven insights can optimize your marketing strategies and enhance campaign effectiveness. Perfect for professionals and students looking to understand the power of data analysis in advertising. for more details visit: https://bostoninstituteofanalytics.org/data-science-and-artificial-intelligence/
Data Centers - Striving Within A Narrow Range - Research Report - MCG - May 2...pchutichetpong
M Capital Group (“MCG”) expects to see demand and the changing evolution of supply, facilitated through institutional investment rotation out of offices and into work from home (“WFH”), while the ever-expanding need for data storage as global internet usage expands, with experts predicting 5.3 billion users by 2023. These market factors will be underpinned by technological changes, such as progressing cloud services and edge sites, allowing the industry to see strong expected annual growth of 13% over the next 4 years.
Whilst competitive headwinds remain, represented through the recent second bankruptcy filing of Sungard, which blames “COVID-19 and other macroeconomic trends including delayed customer spending decisions, insourcing and reductions in IT spending, energy inflation and reduction in demand for certain services”, the industry has seen key adjustments, where MCG believes that engineering cost management and technological innovation will be paramount to success.
MCG reports that the more favorable market conditions expected over the next few years, helped by the winding down of pandemic restrictions and a hybrid working environment will be driving market momentum forward. The continuous injection of capital by alternative investment firms, as well as the growing infrastructural investment from cloud service providers and social media companies, whose revenues are expected to grow over 3.6x larger by value in 2026, will likely help propel center provision and innovation. These factors paint a promising picture for the industry players that offset rising input costs and adapt to new technologies.
According to M Capital Group: “Specifically, the long-term cost-saving opportunities available from the rise of remote managing will likely aid value growth for the industry. Through margin optimization and further availability of capital for reinvestment, strong players will maintain their competitive foothold, while weaker players exit the market to balance supply and demand.”
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
Big data for cybersecurity - skilledfield slides - 25032021
1. Big Data for Cybersecurity
Mouaz Alnouri
25 March 2021
This Session will be recorded and posted on Skilledfield’s Youtube Channel
2. About me
I’m Mouaz Alnouri, the Managing Director of Skilledfield.
We help clients unleash the power of big data technology to detect cyber
security events and utilise automation to efficiently alert, escalate and
respond to security threats.
Technologist with years of experience in solving complex business
problems through creative client-centric strategies and value-driven
solutions. A change agent, capable of orchestrating a transformative
business strategy through data-driven decisions.
2
Mouaz leads the Skilledfield
team with an unrivalled passion
for data and a zest for problem
solving. With over a decade in
the IT services industry, he’s
provided intelligent solutions
for complex problems
throughout his career. He’s
worked with major technology
and telecommunications firms
including Telstra and NBN Co.
Limited, where he’s delivered
data focused solutions that
have significantly improved
operational efficiency. He’s a
customer-focused problem
solver that leads the Skilledfield
team towards their vision to
become Australia’s leading Big
Data solutions provider.
https://www.linkedin.com/in/malnouri/
This Session is being recorded and will be posted on Skilledfield’s Youtube Channel
3. What we are covering today
➔ One Slides about Skilledfield
➔ Why Cybersecurity is a Big Data use case
➔ How do we address Cybersecurity as Big Data Professionals
➔ How do we keep up with the emerging cyber threats
➔ Benefits of Big Data Technology for Cybersecurity
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This Session is being recorded and will be posted on Skilledfield’s Youtube Channel
4. About Skilledfield: A Field of Skilled professionals!
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Uplift Security Detection and
Response Capability
Uplift Observability Capability BI to AI Analytics Services
● Centralised Security Event
logging and auditing
● Endpoint Protection
● SOAR
● Advanced Security Analytics
● Managed Services
● Centralised Operational event
monitoring and alerting
● AIOps, (Artificial Intelligence for
IT operations)
● Managed Services
● Big Data Analytics using Elastic
● Big Data Analytics using
Databricks
● Big Data Analytics using
Microsoft Azure Services
Solving Complex Problems with Simplified Solutions
This Session is being recorded and will be posted on Skilledfield’s Youtube Channel
5. Cybersecurity is Big Data Use Case
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Volume
High amount of data
generated In terabytes
Velocity
Generated in real-time
in streams, batch or
bits
Variety
Structured,
Unstructured, Semi
structured
Big Data
Use Case
Protect
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Assessment
This Session is being recorded and will be posted on Skilledfield’s Youtube Channel
6. Detection Data Engineering Pipeline
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Acquire Parse Enrich Analyse Alert
Sources
Tune
This Session is being recorded and will be posted on Skilledfield’s Youtube Channel
7. Design Data Analytics Solution
● Comprehend business value chain
● Understand short-term and long-term goals and identify key
business questions
● Define analytics use cases
● Perform an initial assessment of data sources
● Design a solution
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This Session is being recorded and will be posted on Skilledfield’s Youtube Channel
8. Threat Modelling - PASTA (Risk Based)
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Define
Objectives
Define
Technical
Scope
Application
Decomposition
Threat Analysis
Vulnerability &
Weakness
Analysis
Attack
Modelling
Risk & Impact
Analysis
The Process for Attack Simulation and Threat Analysis
https://resources.sei.cmu.edu/asset_files/WhitePaper/2018_019_001_524597.pdf
Potential Threat: Identified, categorized, analysed, prioritise response
This Session is being recorded and will be posted on Skilledfield’s Youtube Channel
9. Most Concerning Types of Cyber Threats
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According to IT security decision makers worldwide as of November 2019. Source:
https://www.statista.com/statistics/500946/worldwide-leading-it-security-threats/
Malware is the most concerning cyberthreat
targeting organizations. Phishing and
ransomware were jointly ranked second.
Over the last two years, the number of insider
incidents has increased by 47%.
30 percent of malware attacks are zero day
exploits
Advanced attackers uniquely compile the
code they bring with them to specifically not
match anything they’ve used elsewhere or
ever will again
This Session is being recorded and will be posted on Skilledfield’s Youtube Channel
10. Behavioural Analytics
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Acquire Parse Enrich Analyse Alert
Sources
Tune
Learn Detect
This Session is being recorded and will be posted on Skilledfield’s Youtube Channel
11. Same data. Different questions.
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Ingest & prepare Alerting and Machine learning Detect, hunt, investigate
Ecosystem of network and host
data connectors used to
orchestrate your data feed from
edge devices.
Processing the data in real-time
and analysing it to identify
threats and detecting abnormal
behaviours.
Ad hoc queries at scale and
interactive threat hunting allows
a rapid event triage and
investigation.
This Session is being recorded and will be posted on Skilledfield’s Youtube Channel
12. The DAMA Wheel
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To use consistent words
and relations which
leads to more alignment
with current and future
requirements
Data lifecycle, data
integrity, data availability
and data usage
performance
Access control,
confidentiality and
regulatory compliance
Data Consolidation and
Data Movement
Endure effective and
efficient storage, retrieval
and use of data
Provide authoritative
source of reconciled and
quality-assessed data
Technical environment
and Technical and
Business Processes
Provide organisational
understanding of
business terms and
usages
Identify Data storage
and processing
requirements
Standards, requirements
and specifications for
data
Principles, policies,
procedures, metrics,
tools and responsibilities
for data management
This Session is being recorded and will be posted on Skilledfield’s Youtube Channel
13. Skilledfield is Gold Sponsor for DAMA Australia
Our sponsorship in the Data Architecture and Data Security areas demonstrates our
commitment to the data community and our support for best practices. Our engineers
leverage the Data Management Body of Knowledge (DMBoK) to apply information and
data management best practices to enhance the business value of your Big Data.
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The Data
Management
Association
This Session is being recorded and will be posted on Skilledfield’s Youtube Channel
14. Unleash Big Data Technologies to Solve Complex CyberSecurity Problems
Uplift Security Detection and Response Capability
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● Stop malware at the host, while enabling centralized visibility and advanced threat detection.
● Perform threat-modeling to understand the organization's defensive capabilities and develop customised detections
whilst tuning out false alerts to target genuine vulnerabilities.
● Collect, transform and store data from a broad set of systems including custom ones, build a strong track record of
transparency to inspect security measures and increase visibility.
● Implement fast, scalable, and relevant threat intelligence and data enrichment.
● Leverage machine learning to combat zero-day attacks.
● Organise SOC tasks and playbooks for automated analysis and response.
● Right size your solution including hosting, data throughput, licencing and operational resources.
Respond
Analyse
Detect
85% 30%
50%
of MSPs reported
attacks against SMBs
over the last two years.
of malware attacks
are zero-day exploits.
of security alerts are
false positives leading
to SOCs increasing
staff.
This Session is being recorded and will be posted on Skilledfield’s Youtube Channel
15. Protect your Organisation!
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“It takes 20 years to build a reputation
and a few minutes of cyber-incident to
ruin it”
STEPHANE NAPPO
Global Head of Information Security for Société Générale International Banking & Financial Services
This Session is being recorded and will be posted on Skilledfield’s Youtube Channel
16. “A more secure
online world for
Australians, their
businesses and the
essential services
upon which we all
depend.”
Australia’s Cyber Security Strategy 2020
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https://www.homeaffairs.gov.au/cyber-security-subsite/files/cyber-security-strategy-2020.pdf
● Invest $1.67 billion over 10 years
● New ways to investigate and shut
down cyber crime, including on the
dark web.
● Advice for small and medium
enterprises to increase their cyber
resilience.
● Clear guidance for businesses and
consumers about securing Internet of
Things devices.
● Improved community awareness of
cyber security threats.
This Session is being recorded and will be posted on Skilledfield’s Youtube Channel