Log Management Authors: Dana Gardner, Pat Romanski, Elizabeth White, David H Deans, Carmen Gonzalez

Related Topics: Cloud Security, Microservices Expo, Containers Expo Blog, Log Management, @CloudExpo, @DXWorldExpo

Cloud Security: Article

Anti-Cybercrime Maneuvers Must Keep Up with Growing Threats

Thought leader interview: HP's global CISO Brett Wahlin on the future of security and risk

Join HP’s Chief Information Security Officer (CISO) to learn about how some of the very largest global enterprises like HP are exploring all of their options for doing business safely and continuously.

Brett Wahlin, Vice President and Global CISO at HP, is the next thought leadership guest interview on the HP Discover Performance Podcast Series.

At HP for approximately eight months, Wahlin previously put the security in place after the infamous PlayStation breach while he was the chief security officer (CSO) at Sony Network Entertainment. Prior to that, he was the CSO at McAfee, after a stint as CSO at Los Alamos Laboratory. Years ago, Wahlin got his start doing counterintelligence for the US Army during the Cold War.

Wahlin is interviewed by Paul Muller, Chief Software Evangelist at HP Software, and Dana Gardner, Principal Analyst at Interarbor Solutions. [Disclosure: HP is a sponsor of BriefingsDirect podcasts.]

Here are some excerpts:

Gardner: There's been a lot of discussion about security and a lot of discussion about big data. I'm curious as to how these are actually related.

Wahlin: Big data is quite an interesting development for us in the field of security. If we look back on how we used to do security, trying to determine where our enemies were coming from, what their capacities were, what their targets were, and how we're gathering intelligence to be able to determine how best to protect the company, our resources were quite limited.


We've found that through the use of big data, we're now able to start gathering reams of information that were never available to us in the past. We tend to look at this almost in a modern-warfare type of perspective.

If you're a battlefield commander, and you're looking at how to deploy defenses, how would you deploy those offenses, and what would be the targets that your enemies are looking for? You typically then look at gathering intelligence. This intelligence comes through multiple sources, whether it's electronic or human signals, and you begin to process the intelligence that's gathered, looking for insights into your enemy.

Moving defenses

This could be the enemy’s capabilities, motivation, resourcing, or targets. Then, by that analysis of that intelligence, you can go through a process of moving your defenses, understanding where the targets may be, and adjusting your troops on the ground.

Big data has now given us the ability to collect more intelligence from more sources at a much more rapid pace. As we go through this, we're looking at understanding these types of questions that we would ask as if we were looking at direct adversaries.

We're looking at what these capabilities are, where people are attacking from, why they're attacking us, and what targets they're looking for within our company. We can gather that data much more rapidly through the use of big data and apply these types of analytics.

We begin to ask different questions of the data and, based on the type of questions we're asking, we can come up with some rather interesting information that we never could get in the past. This then takes us to a position where that advanced analytics allows us to almost predict where an enemy might hit.

That’s in the future, I believe. Security is going from the use of prevention, where I'm tackling a known bad thing, to the point where I can use big data to analyze what's happening in real time and then predict where I may be attacked, by whom, and at what targets. That gives me the ability to move the defenses around in such a way that I can protect the high-value items, based on the intelligence that I see coming in through the analytics that we get out of big data.


Muller: Brett, you talk a lot about the idea of getting in front of the problem. Can you talk a little bit about your point of view on how security, from your perspective as a practitioner, has evolved over the last 10-15 years?

Wahlin: Certainly. That’s a great question. Years ago, we used to be about trying to prevent the known bad from happening. The questions we would ask would always be around, can it happen to us, and if it does, can we respond to it? What we have to look at now is the fact that the question should change. It should be not, "Can it happen to us," but "When is it going to happen to us?" And not, "Can we respond to it," but "How can we survive it?"

If we look at that type of a mind-shift change, that takes us back to the old ways of doing security, where you try to prevent, detect, and respond. Basically, you prevented the known bad things from happening.

This went back to the days of -- pick your favorite attack from years ago. One that I remember is very telling. It was Code Red, and we weren’t prepared for it. It hit us. We knew what the signature looked like and we were able to stop it, once we identified what it was. That whole preventive mechanism, back in the day, was pretty much what people did for security.

Fast forward several years, and you get into that new era of security threats highlighted by attacks like Aurora, when it came out. Suddenly, we had the acronyms that flew all over, such as APT -- advanced persistent threats -- and advanced malware. Now, we have attacks that you can't prevent, because you don’t know them. You can't see them. They're zero-days. They're undiscovered malware that’s in your system already.

Detect and respond

That changed the way we moved our security. We went from prevent to a big focus on not just preventing, because that becomes a hygiene function. Now, we move in to detect-and-respond view, where we're looking for anomalies. We're looking for the unknown. We're beefing up the ability to quickly respond to those when we find them.

The evolution, as we move forward, is to add a fourth dimension to this. We prevent, detect, respond, and predict. We use elements like big data to understand not only how to get situational awareness, where we connect the dots within our environment, but taking it one step further and being able to predict where that next stop might land. As we evolve in this particular area, getting to that point where we can understand and predict will become a key capability that security departments must have in future.

Gardner: A reminder to our audience, don't forget to follow the HP Protect 2013 conference activities next week, Sept. 16-19.

As I hear you talking about getting more data, being proactive, and knowing yourself as an organization, Brett, it sounds quite similar to what we have been hearing for many years from the management side, to know yourself to be able better maintain performance standards and therefore be able to quickly remediate when something went wrong.

Are we seeing a confluence between good IT management practices and good security practices, and should we still differentiate between the two?

One of the elements that we look at, of course, is how to add all this additional complexity and additional capability into security and yet still continue to drive value to the business and drive costs out.

Wahlin: As we move into the good management of IT, the good management of knowing yourself, there's a hygiene element that appears within the correlation end of the security industry. One of the elements that we look at, of course, is how to add all this additional complexity and additional capability into security and yet still continue to drive value to the business and drive costs out. So we look for areas of efficiencies and again we will draw many similarities.

As you understand the managing of your environments and knowing yourself, we'll begin to apply known standards that we'll really use in the governance perspective. This is where you will take your hygiene, instead of looking at a very elaborate risk equations. You'll have your typical "risk equals threat times vulnerability times impact," and what are my probabilities.

Known standards

It gets very confusing. So we're trying to cut cost out of those, saying that there are known standards out there. Let's just use them. You can use the ISO 27001, NIST 800-53, or even something like a PCI DSS. Pick your standard, and that then becomes the baseline of control that you want to do. This is knowing yourself.

With these controls, you apply them based on risk to the company. Not all controls are applied equally, nor should they be. As you apply the control based on risk, there is evaluation assessment. Now, I have a known baseline that I can measure myself against.

As you began to build that known baseline, did you understand how well you're doing from a hygiene perspective? These are all the things that you should be doing that give you a chance to understand what your problem areas are.

As you begin to understand those metrics, you can understand where you might have early-warning indicators that would tell you that that you might need to pay attention to certain types of threats, risks, or areas within the company.

There are two types of organizations -- those that have been hacked and those that know they're being hacked.

There are a lot of similarities as you would look at the IT infrastructures, server maintenance, and understanding of those metrics for early warnings or early indicators of problems. We're trying to do the same security, where we make it very repeatable. We can make it standards-based and we can then extend that across the company, of course always being based on risk.

Muller: There is one more element to that, Dana, such as the evolution of IT management through, say, a framework like ITIL, where you very deliberately break down the barriers between silos across IT.

Similarly, I increasingly find with security that collaboration across organizations -- the whole notion of general threat intelligence – forms one of the greatest sources of potential intelligence about an imminent threat. That can come from the operational data, or a lot of operational logs, and then sharing that situational awareness between the operations team is powerful.

At least this works in the experience that I have seen with many of our clients as they improve security outcomes through a heightened sense of what's actually going on, across the infrastructure with customers or users.

One of the greatest challenges we have in moving through Brett’s evolution that he described is that many executives still have the point of view that I have a little green light on my desktop, and that tells me I don’t have any viruses today. I can assume that my organization is safe. That is about as sophisticated a view of security as some executives have.

Increased awareness

Then, of course, you have an increasing level of awareness that that is a false sense of security, particularly in the financial services industry, and increasingly in many governments, certainly national government. Just because you haven't heard about a breach today, that doesn’t mean that one isn't actually either being attempted or is, in fact, being successful.

One of the great challenges we have is just raising that executive awareness that a constant level of vigilance is critical. The other place where we're slowly making progress is that it's not necessarily a bad thing to share negative experiences.

We have to understand which ones of these we need to pay attention to and have the ability to not only correlate amongst ourselves at the company, but correlate across an industry.

Wahlin: Absolutely. We look at the inevitability of the fact that networks are penetrated, and they're penetrated on a daily basis. There's a difference between having unwanted individuals within your network and having the data actually exfiltrated and having a reportable breach.

As we understand what that looks like and how the adversaries are actually getting into our environment, that type of intelligence sharing typically will happen amongst peers. But the need for the ability to actually share and do so without repercussions is an interesting concept. Most companies won't do it, because they still have that preconceived notion that having somebody in your environment is binary -- either my green light is on, and it's not happening, or I've got the red light on, and I've got a problem.

In fact, there are multiple phases of gray that are happening in there, and the ability to share the activities, while they may not be detrimental, are indicators that you have an issue going on and you need to be paying attention to it, which is key when we actually start pointing intelligence.

I've seen these logs. I've seen this type of activity. Is that really an issue I need to pay attention to or is that just an automated probe that’s testing our defenses? If we look at our environment, the size of HP and how many systems we have across the globe, you can imagine that we see that type of activity on a second-by-second basis.

We have to understand which ones of these we need to pay attention to and have the ability to not only correlate amongst ourselves at the company, but correlate across an industry.

HP may be attacked. Other high-tech companies may also be attacked. We'll get supply-chain attacks. We look at various types of politically motivated attacks. Why are they hitting us? So again, it's back to the situational awareness. Knowing the adversary and knowing their motivations, that data can be shared. Right now, it's usually in an ad-hoc way, peer-to-peer, but definitely there's room for some formalized information sharing.

Information sharing

Muller: Especially when you consider the level of information sharing that goes on in the cybercrime world. They run the equivalent of a Facebook almost. There is a huge amount of information sharing that goes on in that community. It's quite well structured. It's quite well organized. It hasn’t necessarily always been that well organized on the defense side of the equation. I think what you're saying is that there's opportunity for improvement.

Wahlin: Yes, and as we look at that opportunity, the counterintelligence person in me always has to stand up and say, "Let's make sure that we're sharing it and we understand our operational security, so that we're sharing that in a way that we're not giving away our secrets to our adversaries." So while there is an opportunity, we also have to be careful with how we share it.

Muller: You, of course, wind up in the situation where you could be amplifying bad information as well. If you were paranoid enough, you could assume that the adversary is actually deliberately planting some sort of distraction at one corner of the organization in order to get to everybody focused on that, while they quietly sneak in through the backdoor.

Wahlin: Correct.

Gardner: Brett, returning to this notion of actionable intelligence and the role of big data as an important tool, where do you go for the data? Is it strictly the systems, the systems log information? Is there an operational side to that that you tap more than the equipment, more than the behaviors? What are the sources of data that you want to analyze in order to be better at security?

Let's make sure that we're sharing it and we understand our operational security, so that we're sharing that in a way that we're not giving away our secrets to our adversaries.

Wahlin: The sources that we use are evolving. We have our traditional sources, and within HP, there is an internal project that is now going into alpha. It's called Project HAVEn and that’s really a combination of ArcSight, Vertica, and Autonomy, integrating with Hadoop. As we build that out and figure out what our capabilities are to put all this data into a large collection and being able to ask the questions and get actionable results out of this, we begin to then analyze our sources.

Sources are obvious as we look at historical operation and security perspective. We have all the log files that are in the perimeter. We have application logs, network infrastructure logs, such as DNS, Active Directory, and other types of LDAP logs.

Then you begin to say, what else can we throw in here? That’s pretty much covered in a traditional ArcSight type of an implementation. But what happens if I start throwing things such as badge access or in-and-out card swipes? How about phone logs? Most companies are running IP phone. They will have logs. So what if I throw that in the equation?

What if I go outside to social media and begin to throw things such as Twitter or Facebook feeds into this equation? What if I start pulling in public searches for government-type databases, law enforcement databases, and start adding these? What results might I get based on all that data commingling?

We're not quite sure at this point. We've added many of these sources as we start to look and ask questions and see from which areas we're able to pull the interesting correlations amongst different types of data to give us that situational awareness.

There's still much to be done here, much to be discovered, as we understand the types of questions that we should be asking. As we look at this data and the sources, we also look at how to create that actionable intelligence.

Disparate sources

The type of analysts that we typically use in a security operations center are very used to ArcSight. I ingest the log and I see correlations. They're time-line driven. Now, we begin to ask questions of multiple types of data sources that are very disparate in their information, and that takes a different type of analyst.

Not only do we have different types of sources, but we have to have different types of skill sets to ask the right questions of those sources. This will continue to evolve. We may or may not find value as we add sources. We don’t want to add a source just for the heck of it, but we also want to understand that we can get very creative with the data as it comes together.

Muller: There are actually two things that I think are important to follow up on here. The first is that, as it's true of every type of analytics conversation I am having today, everyone talks about the term "data scientist." I prefer the term "data artist," because there's a certain artistry to working out what information feeds I want to bring in.

The other element is that, once we've got that information, one of the challenges is that we don’t want to add to the overhead or the burden of processing that information. So it's being able to increasing apply intelligence to, as Brett talked about, mechanistic patterns that you can determine with traditional security information. Event management solutions are rather mechanistic. In other words, you apply a set of logical rules to them.

When you're looking at behavioral activities, rules may not be quite as robust as looking at techniques such as information clustering.

Increasingly, when you're looking at behavioral activities, rules may not be quite as robust as looking at techniques such as information clustering, where you look for hotspots of what seem like unrelated activities at first, but turn out later to be related.

There's a whole bunch of science in the area of crime investigation that we've applied to cybercrime, using some of the techniques, Autonomy for example, to uncover fraud in the financial services market. That automation behind those techniques increasingly is being applied to the big-data problem that security is starting to deal with.

Gardner: You were describing this opportunity to bring so much different information together, but you also might have unintended consequences. Have you plumbed that at all?

Wahlin: Yes. As we further evaluate these data sources and the ability to understand, I believe that the insight into using the big data, not only for security, but as more of a business intelligence (BI) type of perspective has been well-documented. Our focus has really been on trying to determine the patterns and characteristics of usage.

Developing patterns

While we look at it from a purely security mindset, where we try to develop patterns, it takes on a counter-intelligence way of understating how people go, where people go, and what do they do. As people try to be unique, they tend to fall into patterns that are individual and specific to themselves. Those patterns may be over weeks or months, but they're there.

Right now, a lot of times, we'll be asked as a security organization to provide badge swipes as people go in and out of buildings. Can we take that even further and begin to understand where the efficiency would come in based on behaviors and characteristics with workforces. Can we divide that into different business units or geography to try to determine the best use of limited resources across companies? This data could be used in those areas.

The unintended consequence that you brought up, as we look at this and begin to come up with patterns of individuals, is that it begins to reveal a lot about how people interact with systems -- what systems they go to, how often they do things -- and that can be used in a negative way. So there are privacy implications that come right to the forefront as we begin to identify folks.

That that will be an interesting discussion going forward, as the data comes out, patterns start to unfold, patterns become uniquely identifiable to cities, buildings, and individuals. What do we do with those unintended consequences?

There are always situations where any new technology or any new capability could ultimately be used in a negative fashion.

It's almost going to be sort of a two-step, where we can make a couple of steps forward in progress and technology, then we are going to have to deal with these issues, and it might take us a step back. It's definitely evolving in this area, and these unintended consequences could be very detrimental if not addressed early.

We don’t want to completely shut down these types of activities based on privacy concerns or some other type of legalities, when we could actually potentially solve for those problems in a systematic perspective, as we move forward with the investigation of the usage of those technologies.

Muller: The question we always need to bear in mind here is, as Brett talks about it, what are the potential unintended consequences? How can we get in front of those potential misuses early? How can we be vigilant of those misuses and put in place good governance ahead of time?

There are three approaches. One is to bury your head in the send and pretend it will never happen. Second is to avoid adopting a technology at all for fear of those unintended consequences. The third is to be aware of them and be constantly looking for breaches of policy, breaches of good governance, and being able to then correct for those if and when they do occur.

Closed-loop cycle

Gardner: What is HP is doing that will set the stage and perhaps help others to learn how to get started in terms of better security and better leveraging of big data as a tool for better security?

Wahlin: As HP progresses into the predicted security front, we're one of, I believe, two companies that are actually trying to understand how to best use HAVEn as we begin the analytics to determine the appropriate usage of the data that is at our fingertips. That takes a predictive capability that HP will be building.

The lagging piece of this would be the actual creation of agile security.

We've created something called the Cyber Intelligence Center. The whole intent of that is to develop the methodologies around how the big data is used, the plumbing, and then the sources for which we actually create the big data and how we move logs into big data. That's very different than what we're doing today, traditional ArcSight loggers and ESMs. There are a lot of mechanics that we have to build for that.

Then, as we move out of that, we begin to look at the actual actionable intelligence creation to use the analytics. What questions should we ask? Then, when we get the answer, is it something we need to do something about? The lagging piece of this would be the actual creation of agile security. In some places, we even call it mobile security, and it's different than mobility. It's security that can actually move.

If you look at the war-type of analogies, back in the day, you had these columns of men with rifles, and they weren’t that mobile. Then, as you got into mechanized infantry and other types of technologies came online, airplanes and such, it became much more mobile. What's the equivalent to that in the cyber security world, and how do we create that.

Right now, it's quite difficult to move a firewall around. You don’t just unplug or re-VLAN a network. It's very difficult. You bring down applications. So what is the impact of understanding what's coming at you, maybe tomorrow, maybe next week? Can we actually make a infrastructure such that it can be reconfigured to not only to defend against that attack, but perhaps even introduce some adversarial confusion.

I've done my reconnaissance. It looks like this. I come at it tomorrow, and it looks completely different. That is the kill chain that will set back the adversary quite a bit, because most of the time, during a kill chain, it's actually trying to figure out where am I, what I have, where the are assets located, and doing reconnaissance through the network.

So there are a lot of interesting things that we can do as we come to this next step in the evolution of security. At HP, we're trying to develop that at scale. Being the large company that we are, we get the opportunity to see an enormous amount of data that we wouldn’t see if we are another company.

Numerous networks

Gardner: Paul, it almost sounds as if security is an accelerant to becoming a better organization, a more data-driven organization which will pay dividends in many ways.

Muller: I completely agree with you. Information security and the arms race, quite literally the analogy, is a forcing function for many organizations. It would be hard to say this without a sense of chagrin, but the great part about this is that there are actually technologies that are being developed as a result of this. Take ArcSight Logo as an example, as a result of this arms race.

Just as the space race threw up a whole bunch of technologies like Teflon or silicon adhesives that we use today, the the security arms race is generating some great byproducts.

Those technologies can now be applied to business problems, gathering real-time operational technology data, such as seismic events, Twitter feeds, and so forth, and being able to incorporate those back in for business and public-good purposes. Just as the space race threw up a whole bunch of technologies like Teflon or silicon adhesives that we use today, the the security arms race is generating some great byproducts that are being used by enterprises to create value, and that’s a positive thing.

Wahlin: The analogy of the space race is perfect, as you look at trying to do the security maturation within an environment. You begin to see that a lot of the things that we're doing, whether it's understanding the environment, being able to create the operational metrics around an environment, or push into the fact that we've got to get in front of the adversaries to create the environment that is extremely agile is going to throw off a lot of technology innovations.

It’s going to throw off some challenges to the IT industry and how things are put together. That’s going to force typically sloppy operations -- such as I am just going to throw this up together, I am not going to complete an acquisition, I don’t document, I don't understand my environmental -- to clean it up as we go through those processes.

The confusion and the complexity within an environment is directly opposed to creating a sense of security. As we create the more secure environment, environments that are capable of detecting anomalies within them, you have to put the hygienic pieces in place. You have to create the technologies that will allow you to leapfrog the adversaries. That’s definitely going to be both a driver for business efficiencies, as well as technology, and innovation as it comes down.

You may also be interested in:

More Stories By Dana Gardner

At Interarbor Solutions, we create the analysis and in-depth podcasts on enterprise software and cloud trends that help fuel the social media revolution. As a veteran IT analyst, Dana Gardner moderates discussions and interviews get to the meat of the hottest technology topics. We define and forecast the business productivity effects of enterprise infrastructure, SOA and cloud advances. Our social media vehicles become conversational platforms, powerfully distributed via the BriefingsDirect Network of online media partners like ZDNet and IT-Director.com. As founder and principal analyst at Interarbor Solutions, Dana Gardner created BriefingsDirect to give online readers and listeners in-depth and direct access to the brightest thought leaders on IT. Our twice-monthly BriefingsDirect Analyst Insights Edition podcasts examine the latest IT news with a panel of analysts and guests. Our sponsored discussions provide a unique, deep-dive focus on specific industry problems and the latest solutions. This podcast equivalent of an analyst briefing session -- made available as a podcast/transcript/blog to any interested viewer and search engine seeker -- breaks the mold on closed knowledge. These informational podcasts jump-start conversational evangelism, drive traffic to lead generation campaigns, and produce strong SEO returns. Interarbor Solutions provides fresh and creative thinking on IT, SOA, cloud and social media strategies based on the power of thoughtful content, made freely and easily available to proactive seekers of insights and information. As a result, marketers and branding professionals can communicate inexpensively with self-qualifiying readers/listeners in discreet market segments. BriefingsDirect podcasts hosted by Dana Gardner: Full turnkey planning, moderatiing, producing, hosting, and distribution via blogs and IT media partners of essential IT knowledge and understanding.

@ThingsExpo Stories
A strange thing is happening along the way to the Internet of Things, namely far too many devices to work with and manage. It has become clear that we'll need much higher efficiency user experiences that can allow us to more easily and scalably work with the thousands of devices that will soon be in each of our lives. Enter the conversational interface revolution, combining bots we can literally talk with, gesture to, and even direct with our thoughts, with embedded artificial intelligence, whic...
BnkToTheFuture.com is the largest online investment platform for investing in FinTech, Bitcoin and Blockchain companies. We believe the future of finance looks very different from the past and we aim to invest and provide trading opportunities for qualifying investors that want to build a portfolio in the sector in compliance with international financial regulations.
Imagine if you will, a retail floor so densely packed with sensors that they can pick up the movements of insects scurrying across a store aisle. Or a component of a piece of factory equipment so well-instrumented that its digital twin provides resolution down to the micrometer.
In his keynote at 18th Cloud Expo, Andrew Keys, Co-Founder of ConsenSys Enterprise, provided an overview of the evolution of the Internet and the Database and the future of their combination – the Blockchain. Andrew Keys is Co-Founder of ConsenSys Enterprise. He comes to ConsenSys Enterprise with capital markets, technology and entrepreneurial experience. Previously, he worked for UBS investment bank in equities analysis. Later, he was responsible for the creation and distribution of life settle...
Product connectivity goes hand and hand these days with increased use of personal data. New IoT devices are becoming more personalized than ever before. In his session at 22nd Cloud Expo | DXWorld Expo, Nicolas Fierro, CEO of MIMIR Blockchain Solutions, will discuss how in order to protect your data and privacy, IoT applications need to embrace Blockchain technology for a new level of product security never before seen - or needed.
Leading companies, from the Global Fortune 500 to the smallest companies, are adopting hybrid cloud as the path to business advantage. Hybrid cloud depends on cloud services and on-premises infrastructure working in unison. Successful implementations require new levels of data mobility, enabled by an automated and seamless flow across on-premises and cloud resources. In his general session at 21st Cloud Expo, Greg Tevis, an IBM Storage Software Technical Strategist and Customer Solution Architec...
Nordstrom is transforming the way that they do business and the cloud is the key to enabling speed and hyper personalized customer experiences. In his session at 21st Cloud Expo, Ken Schow, VP of Engineering at Nordstrom, discussed some of the key learnings and common pitfalls of large enterprises moving to the cloud. This includes strategies around choosing a cloud provider(s), architecture, and lessons learned. In addition, he covered some of the best practices for structured team migration an...
No hype cycles or predictions of a gazillion things here. IoT is here. You get it. You know your business and have great ideas for a business transformation strategy. What comes next? Time to make it happen. In his session at @ThingsExpo, Jay Mason, an Associate Partner of Analytics, IoT & Cybersecurity at M&S Consulting, presented a step-by-step plan to develop your technology implementation strategy. He also discussed the evaluation of communication standards and IoT messaging protocols, data...
Coca-Cola’s Google powered digital signage system lays the groundwork for a more valuable connection between Coke and its customers. Digital signs pair software with high-resolution displays so that a message can be changed instantly based on what the operator wants to communicate or sell. In their Day 3 Keynote at 21st Cloud Expo, Greg Chambers, Global Group Director, Digital Innovation, Coca-Cola, and Vidya Nagarajan, a Senior Product Manager at Google, discussed how from store operations and ...
In his session at 21st Cloud Expo, Raju Shreewastava, founder of Big Data Trunk, provided a fun and simple way to introduce Machine Leaning to anyone and everyone. He solved a machine learning problem and demonstrated an easy way to be able to do machine learning without even coding. Raju Shreewastava is the founder of Big Data Trunk (www.BigDataTrunk.com), a Big Data Training and consulting firm with offices in the United States. He previously led the data warehouse/business intelligence and B...
"IBM is really all in on blockchain. We take a look at sort of the history of blockchain ledger technologies. It started out with bitcoin, Ethereum, and IBM evaluated these particular blockchain technologies and found they were anonymous and permissionless and that many companies were looking for permissioned blockchain," stated René Bostic, Technical VP of the IBM Cloud Unit in North America, in this SYS-CON.tv interview at 21st Cloud Expo, held Oct 31 – Nov 2, 2017, at the Santa Clara Conventi...
When shopping for a new data processing platform for IoT solutions, many development teams want to be able to test-drive options before making a choice. Yet when evaluating an IoT solution, it’s simply not feasible to do so at scale with physical devices. Building a sensor simulator is the next best choice; however, generating a realistic simulation at very high TPS with ease of configurability is a formidable challenge. When dealing with multiple application or transport protocols, you would be...
Smart cities have the potential to change our lives at so many levels for citizens: less pollution, reduced parking obstacles, better health, education and more energy savings. Real-time data streaming and the Internet of Things (IoT) possess the power to turn this vision into a reality. However, most organizations today are building their data infrastructure to focus solely on addressing immediate business needs vs. a platform capable of quickly adapting emerging technologies to address future ...
We are given a desktop platform with Java 8 or Java 9 installed and seek to find a way to deploy high-performance Java applications that use Java 3D and/or Jogl without having to run an installer. We are subject to the constraint that the applications be signed and deployed so that they can be run in a trusted environment (i.e., outside of the sandbox). Further, we seek to do this in a way that does not depend on bundling a JRE with our applications, as this makes downloads and installations rat...
Widespread fragmentation is stalling the growth of the IIoT and making it difficult for partners to work together. The number of software platforms, apps, hardware and connectivity standards is creating paralysis among businesses that are afraid of being locked into a solution. EdgeX Foundry is unifying the community around a common IoT edge framework and an ecosystem of interoperable components.
DX World EXPO, LLC, a Lighthouse Point, Florida-based startup trade show producer and the creator of "DXWorldEXPO® - Digital Transformation Conference & Expo" has announced its executive management team. The team is headed by Levent Selamoglu, who has been named CEO. "Now is the time for a truly global DX event, to bring together the leading minds from the technology world in a conversation about Digital Transformation," he said in making the announcement.
In this strange new world where more and more power is drawn from business technology, companies are effectively straddling two paths on the road to innovation and transformation into digital enterprises. The first path is the heritage trail – with “legacy” technology forming the background. Here, extant technologies are transformed by core IT teams to provide more API-driven approaches. Legacy systems can restrict companies that are transitioning into digital enterprises. To truly become a lead...
Digital Transformation (DX) is not a "one-size-fits all" strategy. Each organization needs to develop its own unique, long-term DX plan. It must do so by realizing that we now live in a data-driven age, and that technologies such as Cloud Computing, Big Data, the IoT, Cognitive Computing, and Blockchain are only tools. In her general session at 21st Cloud Expo, Rebecca Wanta explained how the strategy must focus on DX and include a commitment from top management to create great IT jobs, monitor ...
"Cloud Academy is an enterprise training platform for the cloud, specifically public clouds. We offer guided learning experiences on AWS, Azure, Google Cloud and all the surrounding methodologies and technologies that you need to know and your teams need to know in order to leverage the full benefits of the cloud," explained Alex Brower, VP of Marketing at Cloud Academy, in this SYS-CON.tv interview at 21st Cloud Expo, held Oct 31 – Nov 2, 2017, at the Santa Clara Convention Center in Santa Clar...
The IoT Will Grow: In what might be the most obvious prediction of the decade, the IoT will continue to expand next year, with more and more devices coming online every single day. What isn’t so obvious about this prediction: where that growth will occur. The retail, healthcare, and industrial/supply chain industries will likely see the greatest growth. Forrester Research has predicted the IoT will become “the backbone” of customer value as it continues to grow. It is no surprise that retail is ...