This document discusses how AI and big data can help detect cybersecurity threats. It describes Interset's security analytics platform, which uses unsupervised machine learning to establish unique baselines for user, device, and network activity. By analyzing billions of events, the platform can detect anomalies indicative of insider threats, compromised accounts, data breaches, and other security issues. Case studies show how Interset helped identify data thieves at a manufacturer and uncovered inappropriate media leaks. The document emphasizes that accurate anomaly detection requires measuring each individual entity's "unique normal" behavior.
IANS Forum Seattle Technology Spotlight: Looking for and Finding the Inside...Interset
At IANS Forum Seattle, Interset Director of Field Ops, Jay Lillie, took a close look at how user and entity behavioral analytics (UEBA) can help to identify insider threats before data is stolen. To learn more, contact Interset at securityai@interset.com.
WEBINAR: How To Use Artificial Intelligence To Prevent Insider ThreatsInterset
Interset CTO Stephan Jou joins Holger Schulze, CEO at Cybersecurity Insiders, to discuss the impact of insider attacks and how AI can be used to mitigate these threats. To watch the webinar recording, click here: https://register.gotowebinar.com/register/2916777136713869315
Want to learn more about the risks of insider threats? Check out highlights from the 2018 Insider Threat Report: https://www.slideshare.net/Interset/2018-insider-threat-report-infographic
IANS Forum Dallas - Technology Spotlight SessionInterset
Take a deep dive into the Interset AI-enabled, security analytics platform to learn how to cut through the noise and identify the high-quality threat leads that matter the most - before your data is stolen.
How to Operationalize Big Data Security Analytics - Technology Spotlight at I...Interset
At IANS Forum NYC 2018, Interset Technology Architect Bob Patten discussed how companies can operationalize security analytics with Interset's threat detection platform, which distills billions of events into a handful of prioritized threat leads through unsupervised machine learning and an open source, big data architecture.
Operationalizing Big Data Security Analytics - IANS Forum DallasInterset
At IANS Forum Dallas, Interset CTO Stephan Jou discussed how Interset's AI-enabled security analytics platform can connect organizations' fragmented security ecosystems and distill billions of events from across the enterprise into a handful of prioritized, high-quality security leads that security teams can focus on.
Innovation in Cybersecurity [Montreal 2018 CRIAQ RDV Forum]Interset
At the 2018 CRIAQ RDV Forum, Interset Director of Field Operations Jay Lillie presented on Interset's mission to apply principled math and data science to cybersecurity in order to detect insider threats.
Operationalizing Big Data Security Analytics - IANS Forum Toronto KeynoteInterset
Presented by Stephan Jou, Interset CTO, at IANS Forum Toronto 2018, this presentation explores how companies can operationalize security analytics with Interset's threat detection platform, which distills billions of events into a handful of prioritized threat leads through unsupervised machine learning and an open source, big data architecture.
Webinar: Will the Real AI Please Stand Up?Interset
In this webinar, Interset CTO Stephan Jou and VP of Products Mario Daigle discussed what to look for when cybersecurity vendors claim to leverage AI for UEBA. View a recording of this webinar at https://zoom.us/webinar/register/WN_0Etv6kilRN-0QuqoNn26bg.
IANS Forum Seattle Technology Spotlight: Looking for and Finding the Inside...Interset
At IANS Forum Seattle, Interset Director of Field Ops, Jay Lillie, took a close look at how user and entity behavioral analytics (UEBA) can help to identify insider threats before data is stolen. To learn more, contact Interset at securityai@interset.com.
WEBINAR: How To Use Artificial Intelligence To Prevent Insider ThreatsInterset
Interset CTO Stephan Jou joins Holger Schulze, CEO at Cybersecurity Insiders, to discuss the impact of insider attacks and how AI can be used to mitigate these threats. To watch the webinar recording, click here: https://register.gotowebinar.com/register/2916777136713869315
Want to learn more about the risks of insider threats? Check out highlights from the 2018 Insider Threat Report: https://www.slideshare.net/Interset/2018-insider-threat-report-infographic
IANS Forum Dallas - Technology Spotlight SessionInterset
Take a deep dive into the Interset AI-enabled, security analytics platform to learn how to cut through the noise and identify the high-quality threat leads that matter the most - before your data is stolen.
How to Operationalize Big Data Security Analytics - Technology Spotlight at I...Interset
At IANS Forum NYC 2018, Interset Technology Architect Bob Patten discussed how companies can operationalize security analytics with Interset's threat detection platform, which distills billions of events into a handful of prioritized threat leads through unsupervised machine learning and an open source, big data architecture.
Operationalizing Big Data Security Analytics - IANS Forum DallasInterset
At IANS Forum Dallas, Interset CTO Stephan Jou discussed how Interset's AI-enabled security analytics platform can connect organizations' fragmented security ecosystems and distill billions of events from across the enterprise into a handful of prioritized, high-quality security leads that security teams can focus on.
Innovation in Cybersecurity [Montreal 2018 CRIAQ RDV Forum]Interset
At the 2018 CRIAQ RDV Forum, Interset Director of Field Operations Jay Lillie presented on Interset's mission to apply principled math and data science to cybersecurity in order to detect insider threats.
Operationalizing Big Data Security Analytics - IANS Forum Toronto KeynoteInterset
Presented by Stephan Jou, Interset CTO, at IANS Forum Toronto 2018, this presentation explores how companies can operationalize security analytics with Interset's threat detection platform, which distills billions of events into a handful of prioritized threat leads through unsupervised machine learning and an open source, big data architecture.
Webinar: Will the Real AI Please Stand Up?Interset
In this webinar, Interset CTO Stephan Jou and VP of Products Mario Daigle discussed what to look for when cybersecurity vendors claim to leverage AI for UEBA. View a recording of this webinar at https://zoom.us/webinar/register/WN_0Etv6kilRN-0QuqoNn26bg.
Machine Learning + AI for Accelerated Threat-HuntingInterset
How quickly can your enterprise find the cyberthreats that matter? In case you missed our talk at #MPOWER17, this is how the new Interset-McAfee security ecosystem helps security teams find them faster.
IANS Forum Charlotte: Operationalizing Big Data Security [Tech Spotlight]Interset
At IANS Forum Charlotte, Interset VP Mario Daigle took a deep dive into the math behind Interset's security analytics platform, which allows security teams to leverage behavioral analytics and a open-source, big data architecture to find hidden threats fast.
In security, rules and thresholds create an excess of security alerts. This slows down security teams, and buries real threats to the enterprise. Analytics, in contrast, will take billions of events and distill them into a handful of true threat leads. This presentation explains—through case studies—how to use statistical methods to validate threats and reduce false positives.
The Myths + Realities of Machine-Learning CybersecurityInterset
Dr. Chase Cunningham, Principal Analyst at Forrester Research, joined Interset’s CTO, Stephan Jou, for a chat about what machine learning means and how enterprises can successfully deploy security analytics strengthened by this type of artificial intelligence. (For more information, visit Interset.com.)
TIC-TOC: Disrupt the Threat Management Conversation with Dominique Singer and...SaraPia5
Threat Management, what it means, how Customers struggle with it, and your entry point for the discussion to be your Customer’s hero in solving their Threat Management problems. Even if you think you know what SIEM means, and especially if you don’t, this Webinar will educate you on the real world problem every Organization faces around Threat Management and the challenges with solutions. Esteemed experts from Cybraics, an industry leader in advanced Threat analytics, will walk us through the problem space, and clearly help you understand how they are differentiated in, and a disruption to, the Threat Management marketplace. Please have your questions ready for this dedicated time with Telarus VP of Biz DEV-Cybersecurity, Dominique Singer and Pete Nicoletti and Nate Grinnell of Cybraics, Inc
One Year After WannaCry - Has Anything Changed? A Root Cause Analysis of Data...Forcepoint LLC
This 20 minute talk was delivered by Forcepoint Principal Security Analyst Carl Leonard at Infosecurity Europe 2018. Delivered to the Strategy track this talk provides a review of the macro trends affecting businesses today, reviews root cause of standout data breaches, highlights the security risk presented by employees, and offers guidance on how to protect your business from specific root causes.
AI & ML in Cyber Security - Why Algorithms are DangerousRaffael Marty
Link to the video of the presentation: https://www.youtube.com/watch?v=WG1k-Xh1TqM
Every single security company is talking in some way or another about how they are applying machine learning. Companies go out of their way to make sure they mention machine learning and not statistics when they explain how they work. Recently, that's not enough anymore either. As a security company you have to claim artificial intelligence to be even part of the conversation.
Guess what. It's all baloney. We have entered a state in cyber security that is, in fact, dangerous. We are blindly relying on algorithms to do the right thing. We are letting deep learning algorithms detect anomalies in our data without having a clue what that algorithm just did. In academia, they call this the lack of explainability and verifiability. But rather than building systems with actual security knowledge, companies are using algorithms that nobody understands and in turn discover wrong insights.
In this talk, I will show the limitations of machine learning, outline the issues of explainability, and show where deep learning should never be applied. I will show examples of how the blind application of algorithms (including deep learning) actually leads to wrong results. Algorithms are dangerous. We need to revert back to experts and invest in systems that learn from, and absorb the knowledge, of experts.
How is ai important to the future of cyber security Robert Smith
Today’s era is driven by technology in every aspect of our lives, so much that we’ve now increased our dependence on technology on a daily basis. With an increase in the dependency, we’re now very vulnerable and exposed to the intermittent threat posed as cyber-attacks. Cyber-attack threats have plagued businesses, corporates, governments, and institutions.
In January IBM Security Systems has announced a new solution wherein it combines the security intelligence capabilities of QRadar SIEM and Big Data + analytics to
Security Analytics and Big Data: What You Need to KnowMapR Technologies
The number of attacks on organization's' IT infrastructure are continuously increasing. It is becoming more and more difficult to identify unknown threats, in particular. This problem requires the ability to store more data and better tools to analyze the data.
Learn in this webinar why big data is enabling new security analytics solutions and why the MapR Quick Start Solution for Security Analytics offers an easy starting point for faster and deeper security analytics.
How to Operationalize Big Data Security AnalyticsInterset
Analytics tools and analysis tools are not the same. Here is how to accelerate threat-detection activities with a holistic, strategic security-analytics solution.
In depth presentation covers market trends and risks related to network security & big data analytics. The presentation was given by Matan Trogan at Cybertech Singapore.
Meet the New IBM i2 QRadar Offense Investigator App and Start Threat Hunting ...IBM Security
When your cyber security is under attack, knowing who is behind your threats and what their motives are can help you ensure those threats don't become a reality. But cyber threat actors conduct their threats through a variety of means and for a variety of reasons. That's why it is critical to analyze a variety of data sources and proactively hunt those threats that are lying in wait. This webinar will illustrate how the IBM i2 QRadar Offense Investigator app enables analysts to push event data from QRadar directly into IBM i2 Analyst's Notebook, where users can apply a variety of visual analysis techniques across a disparate data sources, to build a more comprehensive understand of those threats and hunt them.
Artificial Intelligence – Time Bomb or The Promised Land?Raffael Marty
Companies have AI projects. Security products use AI to keep attackers out and insiders at bay. But what is this "AI" that everyone talks about? In this talk we will explore what artificial intelligence in cyber security is, where the limitations and dangers are, and in what areas we should invest more in AI. We will talk about some of the recent failures of AI in security and invite a conversation about how we verify artificially intelligent systems to understand how much trust we can place in them.
Alongside the AI conversation, we will discover that we need to make a shift in our traditional approach to cyber security. We need to augment our reactive approaches of studying adversary behaviors to understanding behaviors of users and machines to inform a risk-driven approach to security that prevents even zero day attacks.
Every single security company is talking about how they are using machine learning—as a security company you have to claim artificial intelligence to be even part of the conversation. However, this approach can be dangerous when we blindly rely on algorithms to do the right thing. Rather than building systems with actual security knowledge, companies are using algorithms that nobody understands and, in turn, discovering wrong insights.
In this session, we will discuss:
• Limitations of machine learning and issues of explainability
• Where deep learning should never be applied
• Examples of how the blind application of algorithms can lead to wrong results
User and entity behavior analytics: building an effective solutionYolanta Beresna
This presentation provides an overview of UEBA space and gives insights into the core components of an effective solution, such as relevant Threat and Attack Scenarios, Data Sources, and various Analytic techniques. This was presented during ISSA-UK chapter meeting.
How big data and AI saved the day: critical IP almost walked out the doorDataWorks Summit
Cybersecurity threats have evolved beyond what traditional SIEMs and firewalls can detect. We present case studies highlighting how:
•An advanced manufacturer was able to identify new insider threats, enabling them to protect their IP
•A media company’s security operations center was able to verify they weren’t the source of a high-profile media leak.
The common thread across these real-world case studies is how businesses can expand their threat analysis using security analytics powered by artificial intelligence in a big data environment.
Cybersecurity threats increasingly require the aggregation and analysis of multiple data sources. Siloed tools and technologies serve their purpose, but can’t be applied to look across the ever-growing variety and volume of traffic. Big data technologies are a proven solution to aggregating and analysing data across enormous volumes and varieties of data in a scalable way. However, as security professionals well know, more data doesn’t mean more leads or detection. In fact, all too often more data means slower threat hunting and more missed incidents. The solution is to leverage advanced analytical methods like machine learning.
Machine learning is a powerful mathematical approach that can learn patterns in data to identify relevant areas to focus. By applying these methods, we can automatically learn baseline activity and detect deviations across all data sources to flag high-risk entities that behave differently from their peers or past activity. ROY WILDS, Principal Data Scientist, Interset
Data Connectors San Antonio Cybersecurity Conference 2018Interset
In this presentation, Interset Principal Data Scientist Roy Wilds dives into examples of how companies have successfully deployed security analytics. He also addresses how to choose the correct technology, fit it into existing security operations, and define success metrics to measure results.
A New Approach to Threat Detection: Big Data Security Analytics Interset
Learn how to distill billions of events into a handful of security leads. Security analytics powered by machine learning is proven to make your SOC more efficient. This presentation includes four case studies.
Machine Learning + AI for Accelerated Threat-HuntingInterset
How quickly can your enterprise find the cyberthreats that matter? In case you missed our talk at #MPOWER17, this is how the new Interset-McAfee security ecosystem helps security teams find them faster.
IANS Forum Charlotte: Operationalizing Big Data Security [Tech Spotlight]Interset
At IANS Forum Charlotte, Interset VP Mario Daigle took a deep dive into the math behind Interset's security analytics platform, which allows security teams to leverage behavioral analytics and a open-source, big data architecture to find hidden threats fast.
In security, rules and thresholds create an excess of security alerts. This slows down security teams, and buries real threats to the enterprise. Analytics, in contrast, will take billions of events and distill them into a handful of true threat leads. This presentation explains—through case studies—how to use statistical methods to validate threats and reduce false positives.
The Myths + Realities of Machine-Learning CybersecurityInterset
Dr. Chase Cunningham, Principal Analyst at Forrester Research, joined Interset’s CTO, Stephan Jou, for a chat about what machine learning means and how enterprises can successfully deploy security analytics strengthened by this type of artificial intelligence. (For more information, visit Interset.com.)
TIC-TOC: Disrupt the Threat Management Conversation with Dominique Singer and...SaraPia5
Threat Management, what it means, how Customers struggle with it, and your entry point for the discussion to be your Customer’s hero in solving their Threat Management problems. Even if you think you know what SIEM means, and especially if you don’t, this Webinar will educate you on the real world problem every Organization faces around Threat Management and the challenges with solutions. Esteemed experts from Cybraics, an industry leader in advanced Threat analytics, will walk us through the problem space, and clearly help you understand how they are differentiated in, and a disruption to, the Threat Management marketplace. Please have your questions ready for this dedicated time with Telarus VP of Biz DEV-Cybersecurity, Dominique Singer and Pete Nicoletti and Nate Grinnell of Cybraics, Inc
One Year After WannaCry - Has Anything Changed? A Root Cause Analysis of Data...Forcepoint LLC
This 20 minute talk was delivered by Forcepoint Principal Security Analyst Carl Leonard at Infosecurity Europe 2018. Delivered to the Strategy track this talk provides a review of the macro trends affecting businesses today, reviews root cause of standout data breaches, highlights the security risk presented by employees, and offers guidance on how to protect your business from specific root causes.
AI & ML in Cyber Security - Why Algorithms are DangerousRaffael Marty
Link to the video of the presentation: https://www.youtube.com/watch?v=WG1k-Xh1TqM
Every single security company is talking in some way or another about how they are applying machine learning. Companies go out of their way to make sure they mention machine learning and not statistics when they explain how they work. Recently, that's not enough anymore either. As a security company you have to claim artificial intelligence to be even part of the conversation.
Guess what. It's all baloney. We have entered a state in cyber security that is, in fact, dangerous. We are blindly relying on algorithms to do the right thing. We are letting deep learning algorithms detect anomalies in our data without having a clue what that algorithm just did. In academia, they call this the lack of explainability and verifiability. But rather than building systems with actual security knowledge, companies are using algorithms that nobody understands and in turn discover wrong insights.
In this talk, I will show the limitations of machine learning, outline the issues of explainability, and show where deep learning should never be applied. I will show examples of how the blind application of algorithms (including deep learning) actually leads to wrong results. Algorithms are dangerous. We need to revert back to experts and invest in systems that learn from, and absorb the knowledge, of experts.
How is ai important to the future of cyber security Robert Smith
Today’s era is driven by technology in every aspect of our lives, so much that we’ve now increased our dependence on technology on a daily basis. With an increase in the dependency, we’re now very vulnerable and exposed to the intermittent threat posed as cyber-attacks. Cyber-attack threats have plagued businesses, corporates, governments, and institutions.
In January IBM Security Systems has announced a new solution wherein it combines the security intelligence capabilities of QRadar SIEM and Big Data + analytics to
Security Analytics and Big Data: What You Need to KnowMapR Technologies
The number of attacks on organization's' IT infrastructure are continuously increasing. It is becoming more and more difficult to identify unknown threats, in particular. This problem requires the ability to store more data and better tools to analyze the data.
Learn in this webinar why big data is enabling new security analytics solutions and why the MapR Quick Start Solution for Security Analytics offers an easy starting point for faster and deeper security analytics.
How to Operationalize Big Data Security AnalyticsInterset
Analytics tools and analysis tools are not the same. Here is how to accelerate threat-detection activities with a holistic, strategic security-analytics solution.
In depth presentation covers market trends and risks related to network security & big data analytics. The presentation was given by Matan Trogan at Cybertech Singapore.
Meet the New IBM i2 QRadar Offense Investigator App and Start Threat Hunting ...IBM Security
When your cyber security is under attack, knowing who is behind your threats and what their motives are can help you ensure those threats don't become a reality. But cyber threat actors conduct their threats through a variety of means and for a variety of reasons. That's why it is critical to analyze a variety of data sources and proactively hunt those threats that are lying in wait. This webinar will illustrate how the IBM i2 QRadar Offense Investigator app enables analysts to push event data from QRadar directly into IBM i2 Analyst's Notebook, where users can apply a variety of visual analysis techniques across a disparate data sources, to build a more comprehensive understand of those threats and hunt them.
Artificial Intelligence – Time Bomb or The Promised Land?Raffael Marty
Companies have AI projects. Security products use AI to keep attackers out and insiders at bay. But what is this "AI" that everyone talks about? In this talk we will explore what artificial intelligence in cyber security is, where the limitations and dangers are, and in what areas we should invest more in AI. We will talk about some of the recent failures of AI in security and invite a conversation about how we verify artificially intelligent systems to understand how much trust we can place in them.
Alongside the AI conversation, we will discover that we need to make a shift in our traditional approach to cyber security. We need to augment our reactive approaches of studying adversary behaviors to understanding behaviors of users and machines to inform a risk-driven approach to security that prevents even zero day attacks.
Every single security company is talking about how they are using machine learning—as a security company you have to claim artificial intelligence to be even part of the conversation. However, this approach can be dangerous when we blindly rely on algorithms to do the right thing. Rather than building systems with actual security knowledge, companies are using algorithms that nobody understands and, in turn, discovering wrong insights.
In this session, we will discuss:
• Limitations of machine learning and issues of explainability
• Where deep learning should never be applied
• Examples of how the blind application of algorithms can lead to wrong results
User and entity behavior analytics: building an effective solutionYolanta Beresna
This presentation provides an overview of UEBA space and gives insights into the core components of an effective solution, such as relevant Threat and Attack Scenarios, Data Sources, and various Analytic techniques. This was presented during ISSA-UK chapter meeting.
How big data and AI saved the day: critical IP almost walked out the doorDataWorks Summit
Cybersecurity threats have evolved beyond what traditional SIEMs and firewalls can detect. We present case studies highlighting how:
•An advanced manufacturer was able to identify new insider threats, enabling them to protect their IP
•A media company’s security operations center was able to verify they weren’t the source of a high-profile media leak.
The common thread across these real-world case studies is how businesses can expand their threat analysis using security analytics powered by artificial intelligence in a big data environment.
Cybersecurity threats increasingly require the aggregation and analysis of multiple data sources. Siloed tools and technologies serve their purpose, but can’t be applied to look across the ever-growing variety and volume of traffic. Big data technologies are a proven solution to aggregating and analysing data across enormous volumes and varieties of data in a scalable way. However, as security professionals well know, more data doesn’t mean more leads or detection. In fact, all too often more data means slower threat hunting and more missed incidents. The solution is to leverage advanced analytical methods like machine learning.
Machine learning is a powerful mathematical approach that can learn patterns in data to identify relevant areas to focus. By applying these methods, we can automatically learn baseline activity and detect deviations across all data sources to flag high-risk entities that behave differently from their peers or past activity. ROY WILDS, Principal Data Scientist, Interset
Data Connectors San Antonio Cybersecurity Conference 2018Interset
In this presentation, Interset Principal Data Scientist Roy Wilds dives into examples of how companies have successfully deployed security analytics. He also addresses how to choose the correct technology, fit it into existing security operations, and define success metrics to measure results.
A New Approach to Threat Detection: Big Data Security Analytics Interset
Learn how to distill billions of events into a handful of security leads. Security analytics powered by machine learning is proven to make your SOC more efficient. This presentation includes four case studies.
El contexto de la integración masiva de datosSoftware Guru
http://sg.com.mx/sgce/2013/sessions/el-contexto-la-integraci%C3%B3n-masiva-datos
Los ejecutivos de las áreas de TI saben con certeza que la información de negocio más importante, se encuentra escondida en billones de eventos de seguridad. La habilidad de integrar datos para obtener una fotografía clara de la situación actual, es esencial en la manera que hoy día se detectan los ataques clandestinos. Basado en la colección, manejo y análisis; la seguridad de los datos puede ser un gran activo o un enorme dolor de cabeza.
Los desafíos de las llamadas soluciones “SIEM legacy” combinadas con metodologías de inteligencia en seguridad, pueden llevar su organización al siguiente nivel cuando ataques internos y externos se presentan, siempre en cumplimiento reportando, administrando y entregando un valor excepcional y rentabilidad. Conozca como responder ante las necesidades del Big Data mediante la integración de inteligencia global de amenazas (GTI).
[Webinar] Supercharging Security with Behavioral AnalyticsInterset
In this presentation, special guest Joseph Blankenship, principal analyst at Forrester, joined Interset CTO Stephan Jou and Security Strategist Paul Reid for a discussion on how to practically and effectively boost the IQ of your security arsenal with behavioral analytics so you can find threats faster than ever.
Learn more at Interset.AI
Delivering User Behavior Analytics at Apache Hadoop Scale : A new perspective...Cloudera, Inc.
Learn how to:
* Detect threats automatically and accurately
* Reduce threat response times from 7 days to 4 hour
* Ingest and process 100+TB per day for automated machine learning and behavior-based detection
This webinar series is designed to help internal auditors looking to equip themselves with competencies and confidence to handle audit of IT controls and information security, and learn about the emerging technologies and their underlying risks
The series focuses on contemporary IT audit approaches relevant to Internal Auditors and the processes underlying risk based IT audits.
Session 7 of 10
This Webinar focuses on SEIM Log Analysis
• Logging Sources & Servers
• What is a SIEM?
• Advantages of a SIEM?
• Using SIEM
• Detection of outbound sensitive information
• Data Collection
• Aggrefation, Normalization and Enrichment
• Reporting and Forensics
• Challenges in log management
IANS Forum DC: Operationalizing Big Data Security [Tech Spotlight]Interset
At IANS Forum DC, Interset VP Mario Daigle took a deep dive into the math behind Interset's security analytics platform, which allows security teams to leverage behavioral analytics and an open-source, big data architecture to find hidden threats fast.
Learn more at Interset.AI
Security Challenges and Use Cases in the Modern Application Build-and-Deploy ...Amazon Web Services
Modern application build-and-deploy workflows are creating new challenges for traditional security models. Traditional workflows need to be recast in new datasets, and new workflows need to be added to cover the expanding threat surface area. In this session, we explore the security challenges created by modern application build-and-deploy pipelines. We also discuss basic considerations for security defense, example use cases, and a customer case study to illustrate the concepts. This session is brought to you by AWS partner, Sumo Logic.
Big Data Analytics to Enhance Security คุณอนพัทย์ พิพัฒน์กิติบดี Technical Ma...BAINIDA
Big Data Analytics to Enhance Security คุณอนพัทย์ พิพัฒน์กิติบดี Technical Manager, Stelligence ในงาน THE FIRST NIDA BUSINESS ANALYTICS AND DATA SCIENCES CONTEST/CONFERENCE จัดโดย คณะสถิติประยุกต์และ DATA SCIENCES THAILAND
An overview on the application of data science methods and data analytics tools to complement cyber risk quantification, cyber insurance valuation, and cyber risk assessment.
AI & ML in Cyber Security - Why Algorithms are DangerousPriyanka Aash
Every single security company is talking in some way or another about how they are applying machine learning. Companies go out of their way to make sure they mention machine learning and not statistics when they explain how they work. Recently, that's not enough anymore either. As a security company you have to claim artificial intelligence to be even part of the conversation.
Guess what. It's all baloney. We have entered a state in cyber security that is, in fact, dangerous. We are blindly relying on algorithms to do the right thing. We are letting deep learning algorithms detect anomalies in our data without having a clue what that algorithm just did. In academia, they call this the lack of explainability and verifiability. But rather than building systems with actual security knowledge, companies are using algorithms that nobody understands and in turn discover wrong insights.
In this talk, I will show the limitations of machine learning, outline the issues of explainability, and show where deep learning should never be applied. I will show examples of how the blind application of algorithms (including deep learning) actually leads to wrong results. Algorithms are dangerous. We need to revert back to experts and invest in systems that learn from, and absorb the knowledge, of experts.
How to Operationalize Big Data Security AnalyticsInterset
"Analysis" and "analytics" tools are not interchangeable. Here's how to accelerate threat-detection activities with a strategic, holistic security analytics solution. (For more information, visit Interset.com.)
Building a Real-Time Security Application Using Log Data and Machine Learning...Sri Ambati
Building a Real-Time Security Application Using Log Data and Machine Learning- Karthik Aaravabhoomi
- Powered by the open source machine learning software H2O.ai. Contributors welcome at: https://github.com/h2oai
- To view videos on H2O open source machine learning software, go to: https://www.youtube.com/user/0xdata
Cyber Risk Management in 2017: Challenges & RecommendationsUlf Mattsson
https://www.brighttalk.com/webcast/14723/234829?utm_source=Compliance+Engineering&utm_medium=brighttalk&utm_campaign=234829 :
With cyber attacks on the rise, securing your data is more imperative than ever. In future, organizations will face severe penalties if their data isn’t robustly secured. This will have a far reaching impact for how businesses deal with security in terms of managing their cyber risk.
Join this presentation to learn the cyber security controls prescribed by regulation, how this impacts compliance, and how cyber risk management helps CISOs understand the degree these controls are in place and where to prioritize their cyber dollars and ensure they are not at risk for fines.
Viewers will learn:
- The latest cybercrime trends and targets
- Trends in board involvement in cybersecurity
- How to effectively manage the full range of enterprise risks
- How to protect against ransomware
- Visibility into third party risk
- Data security metrics
Sqrrl Enterprise: Big Data Security Analytics Use CaseSqrrl
Organizations are utilizing Sqrrl Enterprise to securely integrate vast amounts of multi-structured data (e.g., tens of petabytes) onto a single Big Data platform and then are building real-time applications using this data and Sqrrl Enterprise’s analytical interfaces. The secure integration is enabled by Accumulo’s innovative cell-level security capabilities and Sqrrl Enterprise’s security extensions, such as encryption.
Similar to DataWorks 2018: How Big Data and AI Saved the Day (20)
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath