Blockchain for Master Data Management
What is the relevance of Blockchain for MDM? Blockchain is a type of a
database – through quite different from traditional relational or emerging
NoSQL databases. As highlighted in the podcast, Blockchain is a linked list of
blocks that contain cryptographically secured blocks of transactions that are
immutable. Participants who do not know or trust each other can rely on and
trust the Blockchain. Unlike traditional databases that support CRUD (Create,
Read, Update, and Delete), with Blockchain, you can only Create and Read:
transactions are validated and added to the blocks in the chain. They can be
read but never deleted or updated. All transactions and activities on the
Blockchain are timestamped. So, what is the relevance of Blockchain for MDM
when we cross organizational boundaries. Conducting business transactions
across organizational boundaries has all the challenges of intra-enterprise
silos and adds several others. Inter-Enterprise exchanges and data sharing are
marred with multiple inefficiencies: manual forms and paperwork, error-prone
replications, delays due to organizational or bureaucratic inefficiencies,
errors in language translations, especially cross-country exchanges,
difficulties, and challenges in reconciling governance policies – to name a
few.
Everything you need to know about the weird future of quantum networks
QKD technology is in its very early stages. The "usual" way to create QKD at
the moment consists of sending qubits in a one-directional way to the
receiver, through optic-fibre cables; but those significantly limit the
effectiveness of the protocol. Qubits can easily get lost or scattered in
a fibre-optic cable, which means that quantum signals are very much
error-prone, and struggle to travel long distances. Current experiments, in
fact, are limited to a range of hundreds of kilometers. There is another
solution, and it is the one that underpins the quantum internet: to leverage
another property of quantum, called entanglement, to communicate between two
devices. When two qubits interact and become entangled, they share particular
properties that depend on each other. While the qubits are in an entangled
state, any change to one particle in the pair will result in changes to the
other, even if they are physically separated. The state of the first qubit,
therefore, can be "read" by looking at the behavior of its entangled
counterpart. That's right: even Albert Einstein called the whole thing "spooky
action at a distance". And in the context of quantum communication,
entanglement could in effect, teleport some information from one qubit to its
entangled other half, without the need for a physical channel bridging the two
during the transmission.
Cyber security Career Guidance — Part 1 — the Beginner’s Journey
Logs can seem overwhelming the first time you come across them. But all you
must do is confront the bully head-on! In my training workshops, I always
throw different log file formats on the screen and ask the students to analyze
what’s going on. At first, there’s a typical sigh across the whole class, but
soon people begin to interpret the different fields and what they could mean.
There are numerous tools out there — some that support multiple log formats,
others which do a great job at a specific log format. With experience, you
will figure out which tool works best for which type of log format, but
nothing beats being able to look at raw logs and not be intimidated. ... while
it is not mandatory that you know a programming language, but it helps a lot.
During the interview process, unless it is mentioned on your resume, I would
not ask about your programming know-how. But from personal experience, I can
vouch for the power of programming when solving real-world technical issues.
Again, which language you know is not important. Even C is fine. Shell
scripting is possibly even better. Python is awesome. In college, we were
taught Basic and C. We taught ourselves C++ and Java on the side.
How Google Maps uses DeepMind’s AI tools to predict your arrival time
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Google Maps is one of the company’s most widely-used products, and its ability
to predict upcoming traffic jams makes it indispensable for many drivers. Each
day, says Google, more than 1 billion kilometers of road are driven with the
app’s help. But, as the search giant explains in a blog post today, its
features have got more accurate thanks to machine learning tools from
DeepMind, the London-based AI lab owned by Google’s parent company Alphabet.
In the blog post, Google and DeepMind researchers explain how they take data
from various sources and feed it into machine learning models to predict
traffic flows. This data includes live traffic information collected
anonymously from Android devices, historical traffic data, information like
speed limits and construction sites from local governments, and also factors
like the quality, size, and direction of any given road. So, in Google’s
estimates, paved roads beat unpaved ones, while the algorithm will decide it’s
sometimes faster to take a longer stretch of motorway than navigate multiple
winding streets.
How to Build a Strong Beta Testers Community
Before you start, you should define your goal and target audience. Defining
goals is the first task to complete. Here are a few relevant ones: test an
idea and gather feedback to make sure you are solving the right problem; test
the sketches to make sure you solve the problem right; and test an early
version to get feedback and adjust the solution before the official launch.
Don’t forget to describe how you understand that you have achieved your goal.
For example, if you want to get feedback regarding your product, that’s great.
But what if only one user provides their feedback? Does it mean that you have
achieved your goal? Make sure you can measure the results so that you are able
to achieve your goal. And as with any other goal, don’t forget to revise your
goal during your beta program. You may want to adjust it as you go. How much
time do you have to dedicate to the beta program? If you do everything
manually, then you need to set a maximum number of participants. Think how
many contacts (customers) can you serve during the beta. Your beta customers
will ask questions, provide feedback, and log the bugs.
How to judge open-source projects
An easier way to determine an open-source program's quality is simply to
look at the number and quality of its developers. Mike Volpi, a well-known
venture capitalist and Index Ventures partner, said that since "software is
never sold," it is adopted by the developers who appreciate the software
more because they can see it and use it themselves rather than being subject
to it based on executive decisions." Therefore, "open-source software
permeates itself through the true experts," and . . . "the developers . . .
vote with their feet." If the programmers are leaving, the maintainers
aren't getting back on patch requests, and the code is growly moldy, it's
time to bid that program good-bye. Or, if it's essential to you, take it
over yourself. You can also determine a project's health by how easy
-- or not -- it makes it for others to participate in it. Ed Warnicke, a
Cisco Distinguished Consulting Engineer, believes successful open-source
communities lower the barriers to useful participation. He lists many
barriers to participation, which are red flags. ... Another way of judging
open-source projects is how many people actually use them.
Which cybersecurity failures cost companies the most and which defenses have the highest ROI?
SCRAM (Secure Cyber Risk Aggregation and Measurement) has, according to its
creators, solved that longstanding cyber-security problem. “SCRAM mimics the
traditional aggregation technique, but works exclusively on encrypted data
that it cannot see. The system takes in encrypted data from the
participants, runs a blind computation on it, and returns an encrypted
result that must be unlocked by each participant separately before anyone
can see the answer,” they explained. “The security of the system comes from
the requirement that the keys from all the participants are needed in order
to unlock any of the data. Participants guarantee their own security by
agreeing to unlock only the result using their privately held key.” More
technical details about the process and the platform, which consists of a
central server, software clients, and a communication network to pass
encrypted data between the clients and the server, can be found in this
paper. ... The researchers recruited seven large companies that had a high
level of security sophistication and a CISO to test out the platform, i.e.,
to contribute encrypted information about their network defenses and a list
of all monetary losses from cyber attacks and their associated defensive
failures over a two-year period.
Open Service Mesh: a Service Mesh Implementation from Microsoft
Microsoft has released (in alpha) the open service mesh (OSM), a service
mesh implementation compliant with the SMI specification. OSM covers
standard features of a service mesh like canary releases, secure
communication, and application insights, similar to other service mesh
implementations like Istio, Linkerd, Consul, or Kuma. Additionally, the OSM
team is in the process of donating the project to the CNCF. OSM implements
the service mesh interface (SMI), a set of standard and portable APIs to
deploy a service mesh in Kubernetes. When users configure a service mesh
through SMI specification, they don't need to be specific about which
service implementation they're running in the cluster. Additionally, OSM
comes with standard and basic service mesh features like canary releases,
secure service communication, and application insights. In this alpha
release, OSM comes with the ability to configure traffic shifting policies,
secure communication within services through mTLS, grained access control
policies, application metrics, external certificate managers, and inject the
sidecar Envoy proxy automatically.
The Hidden Costs of Losing Security Talent
Ryan Corey, co-founder and CEO of online training site Cybrary, says
companies also lose money on staffing when they don't chart a clear career
path for their employees. "Every cyber professional has recruiters calling
them all the time. That's just the way it is because there are not enough
people to fill the available jobs," he says. "When people feel boxed in,
they will leave. They have to know what the path is to the next level."
Another issue: Companies don't handle diversity well, adds Ron Gula, a board
member at Cybrary. "By diversity I mean diversity in employment
backgrounds," he says. "Companies may want to hire a pen tester because they
have security experience, but they should also be looking for people who
have experience in accounting, a legal department, or other types of jobs."
Finally, companies don't fund cyber departments well enough, either, Gula
says. "Too often there's a lack of leadership, funding, and a vision
for what the department could be," he says."Sometimes they outsource and
have a bad experience and then move forward with a skeleton
crew." CyberVista's Petrella says she works with companies on
developing their recruiting and retention strategies, as well as how to
upskill the people they recruit.
Businesses, policymakers ‘misaligned’ on what ethical AI really means
Policymakers rated “fairness and avoiding bias”, such as the
misidentification of individuals, as the top priority for this application
of the technology, followed by “privacy and data rights” and
“transparency.” Among private firms, however, the number one concern
was different. These companies identified “privacy and data rights” as their
number one worry. While this is just one example, experts from EY have
remarked that the substantial misalignment in points of view between the
public and private sectors poses a huge risk to the business landscape, as a
focused approach between the two in relation to ethical AI is absent.
Policymakers and firms need to unite and collaborate in truly defining
ethical AI and must work together to narrow the existing gap. EY global
markets digital and business disruption leader, Gil Forer said, “As AI
scales up in new applications, policymakers and companies must work together
to mitigate new market and legal risks.” Forer continued:
“Cross-collaboration will help these groups understand how emerging ethical
principles will influence AI regulations and will aid policymakers in
enacting decisions that are nuanced and realistic.”
Quote for the day:
"A true dreamer is one who knows how to navigate in the dark" -- John Paul Warren
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