Today’s most pressing data challenges center around connections, not just tabulating discrete data. Graph analytics accelerate breakthroughs across industries with more intelligent solutions.
This article series is designed to help you better leverage graph analytics so you can effectively innovate and develop intelligent solutions faster.
So, I’ve been looking a little deeper into what I have running on my network over the past day or so, and I found a few interesting things. I covered the most interesting things I found in my last piece, as well as some initial scans of the equipment I found. I had a couple of interesting addresses on my NAT LAN, at .128, .131, and .147.
I have no idea what’s running at .128. Whatever it is, it has absolutely no ports open, and believe me, I’ve looked over them all (nmap … -p-65535 is your friend). I ran all the usual suspects from the script library too, and it doesn’t register any vulnerabilities nor has it been hooked by any known malware. I’m going to need to figure out another way to get to whatever that is.
The practice of creating a threat model can help teams proactively understand and develop a strategy for managing the possible vulnerabilities their organization faces, instead of waiting until after an incident occurs. OWASP defines threat modeling as “a procedure for optimizing security by identifying objectives and vulnerabilities, and then defining countermeasures to prevent, or mitigate the effects of, threats to the system.”
SecOps teams can benefit from creating a threat model for cloud infrastructure and defining an approach to operationalizing, hardening, and automating security throughout the software development lifecycle. While it’s best to build security into the design of your systems at the outset, remember the motto:
The United States Patent Office published a patent yesterday, filed by Salesforce, for an email messaging system designed to filter spam. This system uses a blockchain to "ensure integrity of message delivery," as the filing states.
Screenshot of the U.S. Patent Office’s record of Salesforce’s new patent
In the pursuit of data protection, businesses nowadays face more hurdles in the security landscape than ever before. We know there’s a growing demand for reliable, scalable infrastructure, but issues with downtime are complicating businesses’ confidence in their existing systems, implicating all-too-precious data in the process.
For example, 31 percent of respondents in the 2018 Data Center Industry Survey experienced severe and damaging downtime, and almost 80 percent note that the downtime they did experience could have been avoided. Not to mention, prior to IoT, organizations had to protect their datacenter and ROBO locations. With the emergence of IoT, organizations need to protect their infrastructures at the edge and ensure reliability beyond the core of their datacenter alone.
With this article series, I want to deliver an in-depth understanding of not only blockchain and its applications, but also an understanding of how it interweaves with Artificial Intelligence.
Let’s start with blockchain and understand its features.
The considerable number of articles cover Machine Learning for cybersecurity and the ability to protect us from cyber attacks. Still, it’s important to scrutinize how actually Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) can help in cybersecurity right now and what this hype is all about.
First of all, I have to disappoint you. Unfortunately, Machine Learning will never be a silver bullet for cybersecurity compared to image recognition or natural language processing, two areas where Machine Learning is thriving. There will always be a man trying to find weaknesses in systems or ML algorithms and to bypass security mechanisms. What’s worse, now hackers are able to use Machine Learning to carry out all their nefarious endeavors.
“Smart but insecure” sounds like you’re talking about a high achiever who needs therapy.
Which you could be. But in the online world, it applies to semi-animate objects — the hundreds of millions of devices in American homes that are, at one level, smart.
It was great speaking with Torsten Zube, Head of Blockchain at SAP, about their new services that help customers integrate blockchain and the two new consortia that accelerate industry-specific blockchain co-innovation with customers and partners.
The new network extensibility services enable customers and partners to integrate different blockchain infrastructures seamlessly. By providing equal functionalities irrespective of their environment, it supports the interplay between:
“DevOps is Agile on steroids — because Agile isn’t Agile enough.”
So says Jim Bird, the CTO for BiDS Trading, a trading platform for institutional investors. Jim continued, "DevOps teams can move really fast…maybe too fast? This is a significant challenge for operations and security. How do you identify and contain risks when decisions are being made quickly and often by self-managing delivery teams? CABs, annual pen tests, and periodic vulnerability assessment are quickly made irrelevant. How can you prove compliance when developers are pushing their own changes to production?"
Jim was presenting at the 2018 Nexus User Conference on Continuous Delivery. Pulling on his 20+ years of experience in development, operations, and security in highly regulated environments, Jim laid how and why Continuous Delivery reduces risk and how you can get some easy wins toward making it more secure.
