Blockchain Vs Relational Database: What’s The Difference?
So, what is blockchain technology? Well, it’s a ledger system that is
decentralized and distributed. More so, it also offers data integrity,
transparency, and so on. In simple terms, blockchain would be connected in a
chain-like format. It means that any data in the ledger will take on a
chain-like structure. So, just imagine the structure of blocks that are
interlinked together. Furthermore, a block will be linked to the previous and
after blocks. As a result, all the blocks create a chain of blocks, thus the
name. More so, every single block on the ledger will have data or information
about the transaction. So, what about the security of those transactional
data? Well, every single block will be cryptographically encrypted. Another
cool thing about blockchain is that it will have a cryptographic Hash ID that
no one can reverse engineer. You might think blockchain as a database that
just stores information. However, the difference is immense. In reality, both
of them are quite different, and we’ll get into that shortly in the blockchain
vs relational database comparison. Blockchain is, by default, immutable. So,
it means that no one can modify any form of data whatsoever. Thus, any
information that gets into the system once can never be altered or deleted. As
a result, it will stay in the ledger forever.
6 Cloud Native Do’s and Don’ts for Developers
It’s easy to get so caught up in the question of what technologies you’re
using, that you forget why you’re using them in the first place. But remember
that adopting cloud infrastructure — whether it’s a Kubernetes cluster in your
own data center, or serverless API in the public cloud — isn’t the goal. The
goal is to help your organization build more scalable and flexible
applications and to do it quicker. If you’re not actually taking into account
the advantages and disadvantages of cloud infrastructure when you build
applications, there’s a good chance you’re not actually meeting your
organization’s real goals. ... Nodes crash. Networks fail. Remote APIs give
unexpected results. Cloud native development requires you to handle these
problems gracefully. Applications need to give users some sort of response,
even if a component, or several components, are broken or non-responsive. You
also need to think about how to recover once the broken or unavailable
component is working again. Check out the Reactive Principles for additional
guidance and techniques for getting started. ... Cloud native applications
have unique compliance and security challenges.
Security considerations for OTA software updates for IOT gateway devices
Security is a process and a mindset. There is no magic switch we can toggle
to make a system secure. It is important to stay vigilant, reviewing
existing security flaws, and adapting to your workflow to account for them.
New classes of attacks appear seemingly every day and engineering teams must
prepare for this in order to remain secure. The white hats have to get it
right every time while the black hats only need to get it right once. You
need to identify what resources are worthy of being protected. A database of
weather readings is unlikely to contain proprietary information whereas a
customer database most certainly is. You will want to tailor the security to
match the severity of a breach. The objective of most security devices is to
increase the cost of an attack or reduce the value of any successful
breaches. It is important to realize that the OTA update system is generally
only concerned with potential attacks and vulnerabilities to the update
process itself. It does not provide any protection against attacks that
happened outside of the update change. For these kinds of attacks, you need
to rely on other components provided by your operating system. One
extremely important general security consideration is the principle of least
privilege.
Microsoft and the State of Quantum: Q&A With Mariia Mykhailova
The existing quantum hardware is just not mature enough to run quantum algorithms to solve real-world problems, both in terms of the number of qubits in the devices and their quality. However, quantum computing can have impact today – it just requires some extra creativity! We call these solutions “quantum-inspired algorithms” – algorithms that were developed with quantum processes in mind but run on classical hardware. ... Microsoft Quantum’s mission is to develop a scalable and open quantum system and ecosystem around it. This means that we’re working on building a full stack quantum system, and that stack has a lot of layers. Some of these get a lot of publicity, such as Microsoft Quantum Development Kit or the quantum hardware and the fundamental physics research required to implement our vision for it, the topological qubits. But there are other, less known but not less important layers of the stack between these two, such as qubit control technology that has to support scaling quantum systems to millions of qubits, way beyond the physical limitations of current systems. That being said, solving world’s intractable problems is certainly not a single-company effort!An Introduction to Blockchain + NoSQL Databases
Despite the benefits, distributed computing is not pervasive; even within
modern enterprises centralization of many systems is still quite common.
This includes industries that you would expect to be designed with more
resiliency in mind, like the global financial systems or supply chain
management which have tended to be more centralized around mainframe
computing. By the way, you can always tell when there is a centralized
system because when it fails, it fails absolutely! When all data or services
are running on a single machine it is quite easy to know when it goes down
because everything completely stops. It may be because it takes time to
start up a replacement machine, or takes time to notice a failure before
re-routing users or a myriad of other devastating engineering reasons. A
centralized system is the opposite of the peer-to-peer networks we aspire
to. However, with the introduction of platforms like Bitcoin, the next
generation of digital currency and “ledgers” are slowly being proven out.
Now there are thousands of different cryptocurrencies and dozens of
Blockchain backends that are taking advantage of decentralized technology.
As an aside, note that “distributed ledger” does not equate to the
proof-of-work scenarios that many cryptocurrencies use.
Ethical design thinking: empowering designers to drive ethical change
Designers have started to recognise that some of what they have created is
harming people. They are now starting to look at the use of technology and
its impact in the long term, with ethical design at the centre of their
thinking. Despite their motivation, companies have accepted that AI bias
exists and are changing how they harvest and use people’s data — and
designers are central to this change in strategy. “The core is really around
pivoting from what can be done, with the designer coming in at a later
stage, to thinking about what should be done, with the designer coming in at
the beginning of the process,” says Woodley. “The designer represents the
human. They create what is consumed by the person and so they should be ones
influencing the line between what the business wants, what is possible from
a technology perspective and what is responsible from an ethical
perspective,” she continues. Design thinking, starting with empathy or the
understanding of the human, needs to be at the forefront of future
technology innovations and services. We need to flip the current model.
Instead of leveraging technology to achieve business goals without taking
the human impact into consideration, we need to put the human at the centre
of our technology endeavours.
What’s at stake in the Computer Fraud and Abuse Act (CFAA)
Intended as the United States’ first anti-hacking law, the CFAA was enacted
almost thirty-five years ago, long before lawyers and technologists had any
sense of how the Internet would proliferate and evolve. In fact, the Act is
outdated enough that it specifically excludes typewriters and portable
hand-held calculators as a type of computer. Since its inception, it has
been robustly applied for basic terms and services breaches, like the
infamous case of Aaron Swartz downloading articles from the digital library
JSTOR, to indicting nation-state hackers and extraditing Julian Assange. The
core of the problem lies in the vague, perhaps even draconian, description
of “unauthorized” computer use. While the law has been amended several
times, including to clarify the definition of a protected computer, the
ambiguity of unauthorized access puts the average consumer at risk of
breaking federal law. According to the Ninth Circuit, you could potentially
be committing a felony by sharing subscription passwords. The stakes are
particularly high for security researchers who identify vulnerabilities for
companies without safe harbor or bug bounty programs. White-hat hackers, who
act in good faith to report vulnerabilities to a company before it is
breached, face the same legal risks as cybercriminals who actively exploit
and profit from those vulnerabilities.
Take any open source project — its contributors cut across national, religious and racial lines
“Open source is not all technical, and there is a strong community angle to
this. During my college days, I’ve been involved in small ways with local
user groups, where I used to conduct classes and tutorials on various
topics. Once I moved to Bengaluru to work, I got heavily involved in the
Python community and organised the first Python conference in India in 2009.
PyCon India was probably one of the first language-specific tech conferences
in India, and it has since then grown to be one of the largest PyCons in the
world. This year, due to the coronavirus situation, we’re conducting the
conference online. I’m also an active contributor to the Stack Overflow
website, where I rank among the top 0.29 per cent worldwide for giving
answers to questions.” Ibrahim feels that a lot of people don’t seem to
realise that contributing something significant to a project requires a
large amount of work. The main challenge is to develop patience and
dedication to spend enough time to understand a project so that one can
contribute to it. There are smaller problems, like some projects do not have
enough contributors to help with technical problems, but overall, the main
problem is the lack of discipline to put in the time necessary to achieve
some level of proficiency.
Hear the Music Behind Your Data
When faced with the troves of data piling up daily, companies can become
quickly overwhelmed. They’re unsure of where to begin an analysis for
connections between data points. Data science is about exploring and seeking
patterns within data, so it plays a pivotal role in getting companies
started with their analyses. Oftentimes, data scientists won’t even know the
question before they explore; instead, they’ll use their technology to
identify emerging trends and patterns. Capturing and interpreting those
patterns can provide tremendous benefits to a company. For example, data can
help you catch bots that sign up and then spam your product. Human
interaction with a product produces certain patterns — behavior forms a
shape. You can compare that behavior shape to potentially anomalous datasets
and determine if a user is human or not. That gives your team confidence in
disconnecting potential bots from your system, which can save a fair amount
of server space and money. Music is all about patterns, too. Composing a
musical piece requires understanding how notes and the spaces between them
all fit together to create cohesive patterns. Every song you’ve ever heard
has a particular waveform derived from unique patterns of notes and spaces.
The Private Sector Needs a Cybersecurity Transformation
Fundamentally, the current approach to security is focused on the past — even
if it's just a few milliseconds ago. Identifying a threat that already
occurred and stopping the next one is not protection. And with the advances in
technology available today, it should not be the accepted protocol for our
industry. When a time-consuming analysis results in the conclusion of "we can
block this attack next time," you are nowhere close to secure. Simply put,
this approach does nothing to account for the agile adversaries that we know
exist. Staying agile in this fight means looking forward, not back. For that
to be a reality however, time plays a crucial role. Research from Ponemon
Institute shows that security teams spend at least 25% of their time chasing
false positives. I'd argue it's even higher. Defense cannot continue to be
about uncovering the threats that have already happened while trying to block
them again. Time has to be spent on truly preventing what's coming next. ...
While hygiene is important, there is very little prevention going on at the
threat level. Well-meaning employees have been stretched so thin that they
find post-event response acceptable and equate it to cybersecurity. Sometimes
hygiene equates to patching, but often there is a good reason why you can't
patch.
Quote for the day:
“The real voyage of discovery consists not in seeking new landscapes but in having new eyes.” -- Marcel Proust
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