There are some industries like financial services and healthcare that are very global in nature. They have similar challenges such as being heavily regulated and the need to manage large-scale data. But I do see differences in the maturity scale. ...It’s important because as you’re creating data, you need to have good understanding of that data to manage it. In the US and other more developed economies, there are already massive amounts of data collected, but classifying all that data takes a large amount of effort, which means it’s never going to get done. Also, organisations in countries that are spearheading digitisation efforts will also have to take into account data protection laws not only at home, but also in countries where they operate. Organisations are custodians of customer and employee data that has to be managed from both compliance and cost standpoints.
When using serverless computing, coders upload code snippets packaged as a function that carries out a specific task. The code only runs when triggered by an event. But while the coder is responsible for the code itself, the service provider manages the compute stack that runs it; the provider automatically provisions the compute and storage resources needed for that function. Users (generally enterprise IT departments) then are billed on a pay-per-use basis, determined by the number of requests served and the compute time needed to run the code, metered in increments of 100 milliseconds. On the other hand, if the code is never triggered, the user is never billed. Serverless computing differs from other cloud services, such as infrastructure as a service and platform as a service, in that under those cloud versions, users must spin up virtual machines for their applications and also deploy codebase as an entire application.
Griping about AI’s deflated aspirations might seem unimportant. If sensor-driven, data-backed machine learning systems are poised to grow, perhaps people would do well to track the evolution of those technologies. But previous experience suggests that computation’s ascendency demands scrutiny. I’ve previously argued that the word “algorithm” has become a cultural fetish, the secular, technical equivalent of invoking God. To use the term indiscriminately exalts ordinary—and flawed—software services as false idols. AI is no different. As the bot author Allison Parrish puts it, “whenever someone says ‘AI’ what they're really talking about is ‘a computer program someone wrote.’”
Businesses today run on IT. This makes cyber security a business necessity as well as a technology requirement. A strong security program can not only protect a business’s assets, it can also give it a competitive advantage. Although SMBs face the same cyber security challenges as large businesses, they often have fewer resources and little in-house expertise to address these challenges. This makes it important that they get the best return on their security investments by prioritising the right things in their security programs. Cloud computing and hosted services can make advanced technology affordable, and SMBs often find it cost-effective to outsource many IT functions, including security. But at the end of the day, each business is still responsible for its own security. Owners and executives need to understand the basics of cyber security, know what their service providers are doing and what questions to ask of them.
If several products can be orchestrated together, they can build up complex sets of actions like dimming the lights, drawing the blinds, and pausing the dishwasher when the TV comes on -- at least in theory. But for all this to succeed in the long term, consumers will have to want smart homes and be willing to pay for them, probably through subscriptions, Gartner analyst Amanda Sabia said. Some of the results revealed Monday aren’t promising. Three-quarters of respondents said they’d just as soon set their lights and thermostats by hand as have IoT do it, while only a quarter were attracted to the idea of devices anticipating their needs and making changes automatically, Gartner said. The results were similar for doing things manually versus through voice commands to IoT devices.
First, Bandos said, determine threat vectors and points of access. Gather data about your system, potential vulnerabilities, and previous hacks. "The first weapon any cyber threat hunter needs is data. A centralized Security Information & Event Management (SIEM) system is preferred, but simple access to proxy logs and antivirus logs is also highly beneficial. If there are hundreds or even billions of events, the hunting process whittles away the noise like a digital wood carver chipping away to reveal his masterpiece." The data aggregation and culling process should reveal a short list of suspicious activities. Proxy logs are a great place to start hunting, he said, because warning signs like slow connections and automated behavior are easy to spot.
A key task when you want to build an appropriate analytic model using machine learning or deep learning techniques, is the integration and preparation of data sets from various sources like files, databases, big data storage, sensors or social networks. This step can take up to 80 percent of the whole analytics project. This article compares different alternative techniques to prepare data, including extract-transform-load (ETL) batch processing, streaming ingestion and data wrangling. Various options and their trade-offs are discussed using different advanced analytics technologies and open source frameworks such as R, Apache Spark, KNIME or RapidMiner. The article also discusses how this is related to visual analytics, and best practices for how different user roles such as the Data Scientist or Business Analyst should work together to build analytic models.
Prioritising what to focus on is hard in any organisation, but Wilkinson says “everybody understands that one of the really critical success factors for us now in this post-Brexit world is to be far more brutal about what we actually need to get done versus what we would like to get done in a slightly simpler world”. While the exact implications Brexit will have on the Home Office’s IT projects aren’t yet set in stone due to ongoing negotiations in government, the department is trying to “hone in on the stuff that really matters”. “But we need to get that really clear to focus on it, because it’s important we ensure the critical matters are delivered. We’re going to have to let go of, or postpone, some of the stuff we wanted to do in a pre-Brexit world,” she says.
While some ransomware developers -- like those behind Locky or Cryptowall -- closely guard their product, keeping it solely for their own use, others happily distribute ransomware to any wannabe hacker keen to cash in on cyber extortion. One of the most common forms of ransomware distributed in this way is Cerber, which has been known to infect hundreds of thousands of users in just a single month. The original creators of Cerber are selling it on the dark web, allowing other criminals to use the code in return for receiving 40 percent of each ransom paid. In exchange for giving up some of the profits, wannabe cyber fraudsters are provided with everything they need in order to successfully make money through extortion of victims.
The business should ensure that its business continuity/disaster recovery plan and backup and recovery tools are entirely separate from the data and systems that could fall under attack by ransomware. “There are many automated on-site and cloud-based backup solutions that will leave you with options even if ransomware hits network drives,” says Moffitt. There are measures to address ransomware that starts with phishing emails that contain macros, which prerecord commands that will run automatically, in this case unleashing malware and, ultimately, ransomware attacks. You can disable macro functionality in the trust center in Microsoft Office.
Quote for the day:
"When a man assumes a public trust he should consider himself a public property." -- Thomas Jefferson