The security industry is talking a lot about threat intelligence; external information that a company can leverage to understand where potential threats are knocking on the door and might have already perpetrated the network boundaries. Conversations with many CERTs have shown that we have to stop relying on knowledge about how attacks have been conducted in the past and start ‘hunting’ for signs of compromises and anomalies in our own environments.
In this presentation we explore how the decade old field of security visualization has emerged. We show how we have applied advanced analytics and visualization to create our own threat intelligence and investigated lateral movement in a Fortune 50 company.
Visualization. Data science. No machine learning. But pretty pictures.What is internal threat intelligence? Check out http://www.darkreading.com/analytics/creating-your-own-threat-intel-through-hunting-and-visualization/a/d-id/1321225
The Heatmap - Why is Security Visualization so Hard?Raffael Marty
This presentation explores why it is so hard to come up with a security monitoring (or shall we call it security intelligence) approach that helps find sophisticated attackers in all the data collected. It explores the question of how to visualize a billion events. To do so, the presentation dives deeply into heatmaps - matrices - as an example of a simple type of visualization. While these heatmaps are very simple, they are incredibly versatile and help us think about the problem of security visualization. They help illustrate how data mining and user experience design help get a handle of the security visualization challenges - enabling us to gain deep insight for a number of security use-cases.
Ensuring security of a company’s data and infrastructure has largely become a data analytics challenge. It is about finding and understanding patterns and behaviors that are indicative of malicious activities or deviations from the norm. Data, Analytics, and Visualization are used to gain insights and discover those malicious activities. These three components play off of each other, but also have their inherent challenges. A few examples will be given to explore and illustrate some of these challenges,
Delivering Security Insights with Data Analytics and VisualizationRaffael Marty
It's an interesting exercise to look back to the year 2000 to see how we approached cyber security. We just started to realize that data might be a useful currency, but for the most part, security pursued preventative avenues, such as firewalls, intrusion prevention systems, and anti-virus. With the advent of log management and security incident and event management (SIEM) solutions we started to gather gigabytes of sensor data and correlate data from different sensors to improve on their weaknesses and accelerate their strengths. But fundamentally, such solutions didn't scale that well and struggled to deliver real security insight.
Today, cybersecurity wouldn't work anymore without large scale data analytics and machine learning approaches, especially in the realm of malware classification and threat intelligence. Nonetheless, we are still just scratching the surface and learning where the real challenges are in data analytics for security.
This talk will go on a journey of big data in cybersecurity, exploring where big data has been and where it must go to make a true difference. We will look at the potential of data mining, machine learning, and artificial intelligence, as well as the boundaries of these approaches. We will also look at both the shortcomings and potential of data visualization and the human computer interface. It is critical that today's systems take into account the human expert and, most importantly, provide the right data.
How to Hunt for Lateral Movement on Your NetworkSqrrl
Once inside your network, most cyber-attacks go sideways. They progressively move deeper into the network, laterally compromising other systems as they search for key assets and data. Would you spot this lateral movement on your enterprise network?
In this training session, we review the various techniques attackers use to spread through a network, which data sets you can use to reliably find them, and how data science techniques can be used to help automate the detection of lateral movement.
For organizations and individuals with limited security budgets, successfully hunting for cyber adversaries can be a daunting challenge. Threat Intelligence can be expensive and sometimes
nothing more than IoCs or blacklists. In this talk, Endgame’s threat research team will present a series of techniques that can enable organizations to leverage free or almost-free sources of
data and open-source tools to “hunt on the cheap.” They’ll explain how to: retrieve attackers’ tools from globally distributed honeynets that look like your organization or a juicy launching
point to attackers; enrich the data past basic file/tool hashes to identify malicious command and control IPs/domains through automated binary analysis using open-source sandboxes and tools; and use passive DNS data to identify active infections and enrich existing data sets. Attendees will learn how to apply these three techniques to hunt for adversaries within their own
networks. They will also learn about the various open-source solutions available, such as graph databases, that make these techniques inexpensive and within the scope of many organizations.
Anjum Ahuja, Senior Threat Researcher, Endgame
Jamie Butler, Chief Scientist, Endgame
Andrew Morris, Threat Researcher, Endgame
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.
The Heatmap - Why is Security Visualization so Hard?Raffael Marty
This presentation explores why it is so hard to come up with a security monitoring (or shall we call it security intelligence) approach that helps find sophisticated attackers in all the data collected. It explores the question of how to visualize a billion events. To do so, the presentation dives deeply into heatmaps - matrices - as an example of a simple type of visualization. While these heatmaps are very simple, they are incredibly versatile and help us think about the problem of security visualization. They help illustrate how data mining and user experience design help get a handle of the security visualization challenges - enabling us to gain deep insight for a number of security use-cases.
Ensuring security of a company’s data and infrastructure has largely become a data analytics challenge. It is about finding and understanding patterns and behaviors that are indicative of malicious activities or deviations from the norm. Data, Analytics, and Visualization are used to gain insights and discover those malicious activities. These three components play off of each other, but also have their inherent challenges. A few examples will be given to explore and illustrate some of these challenges,
Delivering Security Insights with Data Analytics and VisualizationRaffael Marty
It's an interesting exercise to look back to the year 2000 to see how we approached cyber security. We just started to realize that data might be a useful currency, but for the most part, security pursued preventative avenues, such as firewalls, intrusion prevention systems, and anti-virus. With the advent of log management and security incident and event management (SIEM) solutions we started to gather gigabytes of sensor data and correlate data from different sensors to improve on their weaknesses and accelerate their strengths. But fundamentally, such solutions didn't scale that well and struggled to deliver real security insight.
Today, cybersecurity wouldn't work anymore without large scale data analytics and machine learning approaches, especially in the realm of malware classification and threat intelligence. Nonetheless, we are still just scratching the surface and learning where the real challenges are in data analytics for security.
This talk will go on a journey of big data in cybersecurity, exploring where big data has been and where it must go to make a true difference. We will look at the potential of data mining, machine learning, and artificial intelligence, as well as the boundaries of these approaches. We will also look at both the shortcomings and potential of data visualization and the human computer interface. It is critical that today's systems take into account the human expert and, most importantly, provide the right data.
How to Hunt for Lateral Movement on Your NetworkSqrrl
Once inside your network, most cyber-attacks go sideways. They progressively move deeper into the network, laterally compromising other systems as they search for key assets and data. Would you spot this lateral movement on your enterprise network?
In this training session, we review the various techniques attackers use to spread through a network, which data sets you can use to reliably find them, and how data science techniques can be used to help automate the detection of lateral movement.
For organizations and individuals with limited security budgets, successfully hunting for cyber adversaries can be a daunting challenge. Threat Intelligence can be expensive and sometimes
nothing more than IoCs or blacklists. In this talk, Endgame’s threat research team will present a series of techniques that can enable organizations to leverage free or almost-free sources of
data and open-source tools to “hunt on the cheap.” They’ll explain how to: retrieve attackers’ tools from globally distributed honeynets that look like your organization or a juicy launching
point to attackers; enrich the data past basic file/tool hashes to identify malicious command and control IPs/domains through automated binary analysis using open-source sandboxes and tools; and use passive DNS data to identify active infections and enrich existing data sets. Attendees will learn how to apply these three techniques to hunt for adversaries within their own
networks. They will also learn about the various open-source solutions available, such as graph databases, that make these techniques inexpensive and within the scope of many organizations.
Anjum Ahuja, Senior Threat Researcher, Endgame
Jamie Butler, Chief Scientist, Endgame
Andrew Morris, Threat Researcher, Endgame
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.
My slides for PHDays 2018 Threat Hunting Hands-On Lab - https://www.phdays.com/en/program/reports/build-your-own-threat-hunting-based-on-open-source-tools/
Virtual Machines for lab are available here - https://yadi.sk/d/qB1PNBj_3ViWHe
Blog Post: http://raffy.ch/blog. - Video: https://youtu.be/nk5uz0VZrxM
In this video we talk about the world of security data or log data. In the first section, we dive into a bit of a history lesson around log management, SIEM, and big data in security. We then shift to the present to discuss some of the challenges that we face today with managing all of that data and also discuss some of the trends in the security analytics space. In the third section, we focus on the future. What does tomorrow hold in the SIEM / security data space? What are some of the key features we will see and how does this matter to the user of these approaches.
The Heatmap - Why is Security Visualization so Hard?Raffael Marty
The extent and impact of recent security breaches is showing that current approaches are just not working. But what can we do to protect our business? We have been advocating monitoring for a long time as a way to detect subtle, advanced attacks. However, products have failed to deliver on this promise. Current solutions don't scale in both data volume and analytical insights. In this presentation we will explore why it is so hard to come up with a security monitoring (or shall we call it security intelligence) approach that helps find sophisticated attackers in all the data collected. We are going to explore the question of how to visualize a billion events. We are going to look at a number of security visualization examples to illustrate the problem and some possible solutions. These examples will also help illustrate how data mining and user experience design help us get a handle of the security visualization challenges - enabling us to gain deep insight for a number of security use-cases.
Applied cognitive security complementing the security analyst Priyanka Aash
Security incidents are increasing dramatically and becoming more sophisticated, making it almost impossible for security analysts to keep up. A cognitive solution that can learn about security from structured and unstructured information sources is essential. It can be applied to empower security analysts with insights to qualify incidents and investigate risks quickly and accurately.
(Source : RSA Conference 2017)
Hunting: Defense Against The Dark Arts - BSides Philadelphia - 2016Danny Akacki
We can all agree that threat detection is an essential component of a functioning security monitoring program. Let's start thinking about how to take our tradecraft to the next level and hunt for ways for evil to do evil things. This talk will run through some of the observations gathered during hunting expeditions inside the networks of multiple Fortune ranked organizations. We hope to challenge you to expand your security operations, moving beyond traditional signature based detection.
Applied machine learning defeating modern malicious documentsPriyanka Aash
A common tactic adopted by attackers for initial exploitation is the use of malicious code embedded in Microsoft Office documents. This attack vector is not new, but attackers are still having success. This session will dive into the details of these techniques, introduce some machine learning approaches to analyze and detect these attempts, and explore the output in Elasticsearch and Kibana.
(Source : RSA Conference USA 2017)
Vision is a human’s dominant sense. It is the communication channel with the highest bandwidth into the human brain. Security tools and applications need to make better use of information visualization to enhance human computer interactions and information exchange.
In this talk we will explore a few basic principles of information visualization to see how they apply to cyber security. We will explore both visualization as a data presentation, as well as a data discovery tool. We will address questions like: What makes for effective visualizations? What are some core principles to follow when designing a dashboard? How do you go about visually exploring a terabyte of data? And what role do big data and data mining play in security visualization?
The presentation is filled with visualizations of security data to help translate the theoretical concepts into tangible applications.
Machine learning cybersecurity boon or boondogglePriyanka Aash
Machine learning (ML) and artificial intelligence (AI) are the latest “shiny new things” in cybersecurity technology but while ML and AI hold great promise for automating routine processes and tasks and accelerating threat detection, they are not a panacea. This session will demonstrate what they can and can’t do in a cybersecurity program through real world examples of possibilities and limits.
(Source: RSA Conference USA 2017)
Advances in cloud scale machine learning for cyber-defensePriyanka Aash
Picking an attacker’s signals out of billions of log events in near real time from petabyte scale storage is a daunting task, but Microsoft has been using security data science at cloud scale to successfully disrupt attackers. This session will present the latest frameworks, techniques and the unconventional machine-learning algorithms that Microsoft uses to protect its infrastructure and customers.
(Source : RSA Conference USA 2017)
The extent and impact of recent security breaches is showing that current security approaches are just not working. But what can we do to protect our business? We have been advocating monitoring for a long time as a way to detect subtle, advanced attacks that are still making it through our defenses. However, products have failed to deliver on this promise.
Current solutions don't scale in both data volume and analytical insights. In this presentation we will explore what security monitoring is. Specifically, we are going to explore the question of how to visualize a billion log records. A number of security visualization examples will illustrate some of the challenges with big data visualization. They will also help illustrate how data mining and user experience design help us get a handle on the security visualization challenges - enabling us to gain deep insight for a number of security use-cases.
AI & ML in Cyber Security - Welcome Back to 1999 - Security Hasn't ChangedRaffael Marty
We are writing the year 2017. Cyber security has been a discipline for many years and thousands of security companies are offering solutions to deter and block malicious actors in order to keep our businesses operating and our data confidential. But fundamentally, cyber security has not changed during the last two decades. We are still running Snort and Bro. Firewalls are fundamentally still the same. People get hacked for their poor passwords and we collect logs that we don't know what to do with. In this talk I will paint a slightly provocative and dark picture of security. Fundamentally, nothing has really changed. We'll have a look at machine learning and artificial intelligence and see how those techniques are used today. Do they have the potential to change anything? How will the future look with those technologies? I will show some practical examples of machine learning and motivate that simpler approaches generally win. Maybe we find some hope in visualization? Or maybe Augmented reality? We still have a ways to go.
Creating Your Own Threat Intel Through Hunting & VisualizationRaffael Marty
The security industry is talking a lot about threat intelligence; external information that a company can leverage to understand where potential threats are knocking on the door and might have already perpetrated the network boundaries. Conversations with many CERTs have shown that we have to stop relying on knowledge about how attacks have been conducted in the past and start 'hunting' for signs of compromises and anomalies in our own environments.
In this presentation we explore how the decade old field of security visualization has emerged. We show how we have applied advanced analytics and visualization to create our own threat intelligence and investigated lateral movement in a Fortune 50 company.
Visualization. Data science. No machine learning. But pretty pictures.
Here is a blog post I wrote a bit ago about the general theme of internal threat intelligence:
http://www.darkreading.com/analytics/creating-your-own-threat-intel-through-hunting-and-visualization/a/d-id/1321225?
DAVIX - Data Analysis and Visualization LinuxRaffael Marty
DAVIX, a live CD for data analysis and visualization, brings the most important free tools for data processing and visualization to your desk. There is no hassle with installing an operating system or struggle to build the necessary tools to get started with visualization. You can completely dedicate your time to data analysis.
My slides for PHDays 2018 Threat Hunting Hands-On Lab - https://www.phdays.com/en/program/reports/build-your-own-threat-hunting-based-on-open-source-tools/
Virtual Machines for lab are available here - https://yadi.sk/d/qB1PNBj_3ViWHe
Blog Post: http://raffy.ch/blog. - Video: https://youtu.be/nk5uz0VZrxM
In this video we talk about the world of security data or log data. In the first section, we dive into a bit of a history lesson around log management, SIEM, and big data in security. We then shift to the present to discuss some of the challenges that we face today with managing all of that data and also discuss some of the trends in the security analytics space. In the third section, we focus on the future. What does tomorrow hold in the SIEM / security data space? What are some of the key features we will see and how does this matter to the user of these approaches.
The Heatmap - Why is Security Visualization so Hard?Raffael Marty
The extent and impact of recent security breaches is showing that current approaches are just not working. But what can we do to protect our business? We have been advocating monitoring for a long time as a way to detect subtle, advanced attacks. However, products have failed to deliver on this promise. Current solutions don't scale in both data volume and analytical insights. In this presentation we will explore why it is so hard to come up with a security monitoring (or shall we call it security intelligence) approach that helps find sophisticated attackers in all the data collected. We are going to explore the question of how to visualize a billion events. We are going to look at a number of security visualization examples to illustrate the problem and some possible solutions. These examples will also help illustrate how data mining and user experience design help us get a handle of the security visualization challenges - enabling us to gain deep insight for a number of security use-cases.
Applied cognitive security complementing the security analyst Priyanka Aash
Security incidents are increasing dramatically and becoming more sophisticated, making it almost impossible for security analysts to keep up. A cognitive solution that can learn about security from structured and unstructured information sources is essential. It can be applied to empower security analysts with insights to qualify incidents and investigate risks quickly and accurately.
(Source : RSA Conference 2017)
Hunting: Defense Against The Dark Arts - BSides Philadelphia - 2016Danny Akacki
We can all agree that threat detection is an essential component of a functioning security monitoring program. Let's start thinking about how to take our tradecraft to the next level and hunt for ways for evil to do evil things. This talk will run through some of the observations gathered during hunting expeditions inside the networks of multiple Fortune ranked organizations. We hope to challenge you to expand your security operations, moving beyond traditional signature based detection.
Applied machine learning defeating modern malicious documentsPriyanka Aash
A common tactic adopted by attackers for initial exploitation is the use of malicious code embedded in Microsoft Office documents. This attack vector is not new, but attackers are still having success. This session will dive into the details of these techniques, introduce some machine learning approaches to analyze and detect these attempts, and explore the output in Elasticsearch and Kibana.
(Source : RSA Conference USA 2017)
Vision is a human’s dominant sense. It is the communication channel with the highest bandwidth into the human brain. Security tools and applications need to make better use of information visualization to enhance human computer interactions and information exchange.
In this talk we will explore a few basic principles of information visualization to see how they apply to cyber security. We will explore both visualization as a data presentation, as well as a data discovery tool. We will address questions like: What makes for effective visualizations? What are some core principles to follow when designing a dashboard? How do you go about visually exploring a terabyte of data? And what role do big data and data mining play in security visualization?
The presentation is filled with visualizations of security data to help translate the theoretical concepts into tangible applications.
Machine learning cybersecurity boon or boondogglePriyanka Aash
Machine learning (ML) and artificial intelligence (AI) are the latest “shiny new things” in cybersecurity technology but while ML and AI hold great promise for automating routine processes and tasks and accelerating threat detection, they are not a panacea. This session will demonstrate what they can and can’t do in a cybersecurity program through real world examples of possibilities and limits.
(Source: RSA Conference USA 2017)
Advances in cloud scale machine learning for cyber-defensePriyanka Aash
Picking an attacker’s signals out of billions of log events in near real time from petabyte scale storage is a daunting task, but Microsoft has been using security data science at cloud scale to successfully disrupt attackers. This session will present the latest frameworks, techniques and the unconventional machine-learning algorithms that Microsoft uses to protect its infrastructure and customers.
(Source : RSA Conference USA 2017)
The extent and impact of recent security breaches is showing that current security approaches are just not working. But what can we do to protect our business? We have been advocating monitoring for a long time as a way to detect subtle, advanced attacks that are still making it through our defenses. However, products have failed to deliver on this promise.
Current solutions don't scale in both data volume and analytical insights. In this presentation we will explore what security monitoring is. Specifically, we are going to explore the question of how to visualize a billion log records. A number of security visualization examples will illustrate some of the challenges with big data visualization. They will also help illustrate how data mining and user experience design help us get a handle on the security visualization challenges - enabling us to gain deep insight for a number of security use-cases.
AI & ML in Cyber Security - Welcome Back to 1999 - Security Hasn't ChangedRaffael Marty
We are writing the year 2017. Cyber security has been a discipline for many years and thousands of security companies are offering solutions to deter and block malicious actors in order to keep our businesses operating and our data confidential. But fundamentally, cyber security has not changed during the last two decades. We are still running Snort and Bro. Firewalls are fundamentally still the same. People get hacked for their poor passwords and we collect logs that we don't know what to do with. In this talk I will paint a slightly provocative and dark picture of security. Fundamentally, nothing has really changed. We'll have a look at machine learning and artificial intelligence and see how those techniques are used today. Do they have the potential to change anything? How will the future look with those technologies? I will show some practical examples of machine learning and motivate that simpler approaches generally win. Maybe we find some hope in visualization? Or maybe Augmented reality? We still have a ways to go.
Creating Your Own Threat Intel Through Hunting & VisualizationRaffael Marty
The security industry is talking a lot about threat intelligence; external information that a company can leverage to understand where potential threats are knocking on the door and might have already perpetrated the network boundaries. Conversations with many CERTs have shown that we have to stop relying on knowledge about how attacks have been conducted in the past and start 'hunting' for signs of compromises and anomalies in our own environments.
In this presentation we explore how the decade old field of security visualization has emerged. We show how we have applied advanced analytics and visualization to create our own threat intelligence and investigated lateral movement in a Fortune 50 company.
Visualization. Data science. No machine learning. But pretty pictures.
Here is a blog post I wrote a bit ago about the general theme of internal threat intelligence:
http://www.darkreading.com/analytics/creating-your-own-threat-intel-through-hunting-and-visualization/a/d-id/1321225?
DAVIX - Data Analysis and Visualization LinuxRaffael Marty
DAVIX, a live CD for data analysis and visualization, brings the most important free tools for data processing and visualization to your desk. There is no hassle with installing an operating system or struggle to build the necessary tools to get started with visualization. You can completely dedicate your time to data analysis.
Cyber Security – How Visual Analytics Unlock InsightRaffael Marty
Video can be found at: http://youtu.be/CEAMF0TaUUU
In the Cyber Security domain, we have been collecting ‘big data’ for almost two decades. The volume and variety of our data is extremely large, but understanding and capturing the semantics of the data is even more of a challenge. Finding the needle in the proverbial haystack has been attempted from many different angles. In this talk we will have a look at what approaches have been explored, what has worked, and what has not. We will see that there is still a large amount of work to be done and data mining is going to play a central role. We’ll try to motivate that in order to successfully find bad guys, we will have to embrace a solution that not only leverages clever data mining, but employs the right mix between human computer interfaces, data mining, and scalable data platforms.
Security Visualization - Let's Take A Step BackRaffael Marty
I gave the keynote at VizSec 2012. I used the opportunity to take a step back to see where security visualization is at and propose a challenge for how some of the problems we should be focusing on going forward.
Video recording is here: http://youtu.be/AEAs7IzTHMo
Supercharging Visualization with Data MiningRaffael Marty
We are exploring how data mining can help visualization. I am giving examples of security visualizations and am discussing how data mining best augments visualization efforts.
Visual Analytics and Security IntelligenceRaffael Marty
Big data and security intelligence are the two hot security topics in 2012. We are collecting more and more information from both the infrastructure, but increasingly also directly from our applications. Some companies are moving away from traditional log management and SIEM tools and are deploying big data products. But what is this big data craze all about? Why is it that we have more and more data to look at? And is big data the right approach or what is missing?
The presentation takes the audience on a journey through big data tools and show that analytical tools are needed to make use of these infrastructures. How can visualization be used to fill in the gap in analytics to move into gaining situational awareness and building up security intelligence.
Cooperative models to transform dairy value chains in Southern AfricaILRI
Presented by Carmen Jaquez (Land O Lakes) at the African Green Revolution Forum Working Session on Transforming Dairy Value Chains in Africa: Pathways to Prosperity, Nairobi, 8 September 2016
The first question is what is meant by a ‘smart city’. The answer is, there is no universally accepted definition of a Smart City. It means different things to different people. The conceptualization of Smart City, therefore, varies from city to city and country to country, depending on the level of development, willingness to change and reform, resources and aspirations of the city residents. A Smart City would have a different connotation in India than, say, Europe. Even in India, there is no one way of defining a Smart City.
Smart City Features:
Quick accident relief: In case of accident or fault in a vehicle, people will get help in just one call. They will get help through CCTV too.
Smart Traffic system: On the lines of London’s Smart Traffic System, people will get the information regarding heavy traffic in advance. At present, Bangalore has this system.
Face Identification System to catch criminals: On the lines of Paris, the Smart City will have Face Identification System in place to catch criminals. The photos and DNA of criminals and suspects will be entered in computer and information will also be shared with other cities.
So macht man günstig guten Video-Content für die Social Media Auftritte des eigenen Unternehmens. Geräte und Software für einen schnellen Start in Kürze vorgestellt.
A company is like a baby, one leg representing business and the other standing for technology. Moving the first steps as a startup is hard, accelerating to run as a company is even harder: you have to grow up with both legs keeping pace
OpenMove will give its perspective on major challenges faced to bring the company to market its products in 6 countries, dealing with high-profile customers like Ministries of Transport or big telcos… guys you don’t wanna mess with!
On the business side, Lorenzo, CEO, will tell how they have been structuring product- and knowledge-management, business development (and some other super boring stuff), while Michele, CTO, will show the cool things: scalability and high availability of the platform adopting Docker Swarm, optimization by using Meteor.js and MongoDB and evolution towards an ecosystem of microservices.
Co Speaker: Cheryl Biswas
Talk Description:
How about this: a blue team talk given by red teamers. But here’s our rationale - your best defence right now is a strategic offence. The rules of the game have changed and we need to get defence up to speed.
We’ll show you what the key elements are in a good defence strategy; what you can and need to be using to full advantage. We’ll talk about the new “buzzwords” and how they apply: visibility; patterns; big data. There’s a whole lotta data to wrangle, and you aren’t seeing the whole picture if you aren’t doing things right. Threat intel is about getting the big picture as it applies to you. You’ll learn the importance of context and prioritization so that you can manipulate intel feeds to do your bidding. And then we’ll take things further and talk about hunting the adversary, using an update on proven methodologies.
We’ll show you how to understand your data, correlate threats and pin point attacks. Attendees will leave with a new understanding of the resources they have on hand, and how to leverage those into an Adaptive Proactive Defense Strategy.
Google Ad Grants for Nonprofits is a fantastic program that helps nonprofits raise awareness and grow their community. With up to $10,000 per month in free advertising, all nonprofits should be using this resource. Interested in learning more? Contact john@mohrdigital.com today.
RIoT (Raiding Internet of Things) by Jacob HolcombPriyanka Aash
The recorded version of 'Best Of The World Webcast Series' [Webinar] where Jacob Holcomb speaks on 'RIoT (Raiding Internet of Things)' is available on CISOPlatform.
Best Of The World Webcast Series are webinars where breakthrough/original security researchers showcase their study, to offer the CISO/security experts the best insights in information security.
For more signup(it's free): www.cisoplatform.com
Protecting Financial Networks from Cyber CrimeLancope, Inc.
Financial services organizations are prime targets for cyber criminals. They must take extreme care to protect customer data, while also ensuring high levels of network availability to allow for 24/7 access to critical financial information. Additionally, industry consolidation has created large, heterogeneous network environments within large financial institutions, making it difficult to ensure that networks have the necessary visibility and protection to prevent a devastating security breach. By leveraging NetFlow from existing network infrastructure, financial services organizations can achieve comprehensive visibility across even the largest, most complex networks. The ability to quickly detect a wide range of potentially malicious activity helps prevent damaging data breaches and network disruptions. Attend this informational webinar, conducted by Lancope’s Director of Security Research, Tom Cross, to learn: How NetFlow can help quickly uncover both internal and external threats How pervasive network insight can accelerate incident response and forensic investigations How to substantially decrease enterprise risks
Applied Detection and Analysis with Flow Data - SO Con 2014chrissanders88
In this presentation, we discuss the benefit of using flow data for detection and analysis. We also discuss the SiLK flow analysis suite and the FlowPlotter tool that can be used for generating ad-hoc visualizations from flow data, as well as the upcoming FlowBAT tool that is used to ease analysis of this very useful data type.
Applied Detection and Analysis Using Flow Data - MIRCon 2014chrissanders88
In this presentation, Chris Sanders and Jason Smith discuss the importance of using flow data for network security analysis. Flow data is discussed from the viewpoints of collection, detection, and analysis. We also discuss the FlowPlotter tool, and the use of FlowBAT, a graphical flow analysis GUI we've created.
Leverage the Network to Detect and Manage ThreatsCisco Canada
Session: Leverage the Network to Detect and Manage Threats
Presenter: Michael Moriarta, Lancope - Technical Alliance Manager/SE Southeast US
Date: October 6, 2015
Splunk Enterpise for Information Security Hands-OnSplunk
Splunk is the ultimate tool for the InfoSec hunter. In this unique session, we’ll dive straight into the Splunk search interface, and interact with wire data harvested from various interesting and hostile environments, as well as some web access logs. We’ll show how you can use Splunk Enterprise with a few free Splunk applications to hunt for attack patterns. We’ll also demonstrate some ways to add context to your data in order to reduce false positives and more quickly respond to information. Bring your laptop – you’ll need a web browser to access our demo systems!
StealthWatch & Point-of-Sale (POS) Malware Lancope, Inc.
Retailers are under cyber-attack at an alarming rate. Day after day, we hear of another major national retail chain experiencing a colossal data breach.
Learn key concepts and techniques that will help you rapidly enhance your current cyber security efforts.
• Get a complete view what is currently happening in the retail industry
• Understand the concepts of NetFlow and how it can greatly enhance security efforts
• Learn how attacks are injected into the network from the POS system, and ways to detect and remediate these attacks
• Establish a means to recognize data exfiltration and learn techniques to prevent it
A Hacker's Perspective on Embedded Device Security, presented by Paul Dant of Independent Security Evaluators at the Security of Things Forum, Sept. 10, 2015
MMIX Peering Forum and MMNOG 2020: Packet Analysis for Network SecurityAPNIC
APNIC Senior Network Analyst/Technical Trainer Warren Finch presents on packet analysis for network security at the MMIX Peering Forum and MMNOG 2020 in Yangon, Myanmar, from 13 to 17 January 2020.
This is Next-Gen IT Security - Introducing Intercept XSophos Benelux
Former CEO of Surfright (now Sophos' Director of Engineering) Mark Loman, presented Intercept X to the Dutch market at the Sophos Day Netherlands. This signatureless next-generation endpoint security solution delivers anti-ransomware, anti-exploit and anti-hacker features that will bring the game of IT security to a whole new level.
Sophos Day Belgium - This is Next-Gen IT Security (Sophos Intercept X)Sophos Benelux
Mark Loman showed the audience Sophos' next-generation signatureless endpoint solution which tackles exploits, zero-days, ransomware and any other known and unknown types of malware.
The realities of insider threats and determined attackers have made it necessary to implement security technologies on the network interior. This session will discuss leveraging network telemetry, such as NetFlow and Cisco ISE, in combination with the Cisco StealthWatch System and in order to monitor the network interior to detect and respond to threats. Use cases on how to best organize and query NetFlow data will be presented as well as how to drive an investigation in order to identify an attacker's presence on the network based on the statistical analysis of network telemetry. The target audience for this session are network and security administrators and analysts interested in learning how to best leverage NetFlow, ISE, and StealthWatch as a component of their security operations center.
How to protect, detect, and respond to your threats.
This is an MSP centric talk exploring how to detect, protect, and respond to cyber security threats. We first walk through the cyber defense matrix, explore what security intelligence needs to be and emphasize the concepts with two case studies of BlackCat.
Extended Detection and Response (XDR)An Overhyped Product Category With Ulti...Raffael Marty
Extended Detection and Response, or XDR for short, is one of the acronyms that are increasingly used by cybersecurity vendors to explain their approach to solving the cyber security problem. We have been spending trillions of dollars on approaches to secure our systems and data, with what success? Cybersecurity is still one of the biggest and most challenging areas that companies, small and large, are dealing with. XDR is another approach driven by security vendors to solve this problem. The challenge is that every vendor defines XDR slightly differently and makes it fit their own “challenge du jour” for marketing and selling their products.
In this presentation we will demystify the XDR acronym and put a working model behind it. Together, we will explore why XDR is a fabulous concept, but also discover that it’s nothing revolutionarily new. With an MSP lens, we will explore what the XDR benefits are for small and medium businesses and what it means to the security strategy of both MSPs and their clients. The audience will leave with a clear understanding of what XDR is, how the technology matters to them, and how XDR will ultimately help them secure their customers and enable trusted commerce.
Cyber Security Beyond 2020 – Will We Learn From Our Mistakes?Raffael Marty
The cyber security industry has spent trillions of dollars to keep external attackers at bay. To what effect? We still don't see an end to the cat and mouse game between attackers and the security industry; zero day attacks, new vulnerabilities, ever increasingly sophisticated attacks, etc. We need a paradigm shift in security. A shift away from traditional threat intelligence and indicators of compromise (IOCs). We need to look at understanding behaviors. Those of devices and those of humans.
What are the security approaches and trends that will make an actual difference in protecting our critical data and intellectual property; not just from external attackers, but also from malicious insiders? We will explore topics from the 'all solving' artificial intelligence to risk-based security. We will look at what is happening within the security industry itself, where startups are putting placing their bets, and how human factors will play an increasingly important role in security, along with all of the potential challenges that will create.
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.
In this presentation I explore the topic of artificial intelligence in cyber security. What is AI and how do we get to real intelligence in a cyber context. I outline some of the dangers of the way we are using algorithms (AI, ML) today and what that leads to. We then explore how we can add real intelligence through export knowledge to the problem of finding attackers and anomalies in our applications and networks.
Presented at AI 4 Cyber in NYC on April 30, 2019
AI & ML in Cyber Security - Why Algorithms Are DangerousRaffael Marty
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.
An overview of some methods and principles for big data visualization. The presentation quickly hits on the topic of dashboards and some cyber security uses. The topic of a big data lake is also briefly discussed in the context of a cyber security big data setup.
Workshop: Big Data Visualization for SecurityRaffael Marty
Big Data is the latest hype in the security industry. We will have a closer look at what big data is comprised of: Hadoop, Spark, ElasticSearch, Hive, MongoDB, etc. We will learn how to best manage security data in a small Hadoop cluster for different types of use-cases. Doing so, we will encounter a number of big-data open source tools, such as LogStash and Moloch that help with managing log files and packet captures.
As a second topic we will look at visualization and how we can leverage visualization to learn more about our data. In the hands-on part, we will use some of the big data tools, as well as a number of visualization tools to actively investigate a sample data set.
AfterGlow is a script that assists with the visualization of log data. It reads CSV files and converts them into a Graph description. Check out http://afterglow.sf.net for more information also.
This short presentation gives an overview of AfterGlow and outlines the features and capabilities of the tool. It discusses some of the harder to understand features by showing some configuration examples that can be used as a starting point for some more sophisticated setups.
AftterGlow is one the most downloaded security visualization tools with over 17,000 downloads.
This 7-second Brain Wave Ritual Attracts Money To You.!nirahealhty
Discover the power of a simple 7-second brain wave ritual that can attract wealth and abundance into your life. By tapping into specific brain frequencies, this technique helps you manifest financial success effortlessly. Ready to transform your financial future? Try this powerful ritual and start attracting money today!
ER(Entity Relationship) Diagram for online shopping - TAEHimani415946
https://bit.ly/3KACoyV
The ER diagram for the project is the foundation for the building of the database of the project. The properties, datatypes, and attributes are defined by the ER diagram.
Multi-cluster Kubernetes Networking- Patterns, Projects and GuidelinesSanjeev Rampal
Talk presented at Kubernetes Community Day, New York, May 2024.
Technical summary of Multi-Cluster Kubernetes Networking architectures with focus on 4 key topics.
1) Key patterns for Multi-cluster architectures
2) Architectural comparison of several OSS/ CNCF projects to address these patterns
3) Evolution trends for the APIs of these projects
4) Some design recommendations & guidelines for adopting/ deploying these solutions.
1.Wireless Communication System_Wireless communication is a broad term that i...JeyaPerumal1
Wireless communication involves the transmission of information over a distance without the help of wires, cables or any other forms of electrical conductors.
Wireless communication is a broad term that incorporates all procedures and forms of connecting and communicating between two or more devices using a wireless signal through wireless communication technologies and devices.
Features of Wireless Communication
The evolution of wireless technology has brought many advancements with its effective features.
The transmitted distance can be anywhere between a few meters (for example, a television's remote control) and thousands of kilometers (for example, radio communication).
Wireless communication can be used for cellular telephony, wireless access to the internet, wireless home networking, and so on.
Creating Your Own Threat Intel Through Hunting & Visualization
1. Creating Your Own Threat Intel
Through Hunting & Visualization
Raffael Marty
VP Security Analytics
May 11, 2016
Honeynet Workshop 2016 – San Antonio, TX
13. 14
• SELECT count(distinct protocol) FROM flows;
• SELECT count(distinct port) FROM flows;
• SELECT count(distinct src_network) FROM flows;
• SELECT count(distinct dest_network) FROM flows;
• SELECT port, count(*) FROM flows GROUP BY port;
• SELECT protocol,
count(CASE WHEN flows < 200 THEN 1 END) AS [<200],
count(CASE WHEN flows>= 201 AND flows < 300 THEN 1 END)
AS [201 - 300],
count(CASE WHEN flows>= 301 AND flows < 350 THEN 1 END)
AS [301 - 350],
count(CASE WHEN flows>= 351 THEN 1 END) AS [>351]
FROM flows GROUP BY protocol;
• SELECT port, count(distinct src_network) FROM flows GROUP BY
port;
• SELECT src_network, count(distinct dest_network) FROM flows
GROUP BY port;
• SELECT src_network, count(distinct dest_network) AS dn,
sum(flows) FROM flows GROUP BY port, dn;
• SELECT port, protocol, count(*) FROM flows GROUP BY port,
protocol;
• SELECT sum(flows), dest_network FROM flows GROUP BY
dest_network;
• etc.
One Graph Summarizes Dozens of Queries
port dest_network
protocol src_network flows
15. 16
Technical
• Visualization
• Context
• Data Science
Non-Technical
• Analysts are your best and most expensive resource
• They need the right tools and data
• Speed (see the data lake)
• Interaction (visual!)
• Machine-assisted insight (datascience)
Core Components To Enable Hunting