Networks


Bracing For IoT In The Enterprise

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If you thought the bring-your-own-device (BYOD) experience was a challenge for companies, brace yourself. The mid-2000s brought waves of heterogeneous, non-sanctioned devices into the network. By 2009, workers had made it clear that they preferred BYOD, as CIOs began feeling the pressure of personal devices flooding the workplace. The result has been the creation of so-called "shadow IT" -- projects (applications and systems) managed outside of, and without the knowledge of, the IT department. The BYOD phenomenon went hand in hand with the adoption of non-sanctioned, cloud-based software as a service (SaaS) applications to address a line of business needs.


The Benefits of AI and Machine Learning in Network Monitoring

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Artificial intelligence – also commonly known as AI – has revolutionized the technology world. Companies both inside and outside the tech circle are introducing AI into their work suite. AI takes the basic principles of computing and processing and applies intelligent environment analysis on top of it. For industries, AI analyzes the data they generate and provides them with insights based on its findings. AI can also apply machine learning to examine historical data in order to perform tasks without human input.


Tor traffic from individual Android apps detected with 97 percent accuracy

ZDNet

Italian academics say they've developed an algorithm that can detect the patterns of Android app activity inside Tor traffic with an accuracy of 97 percent. The algorithm isn't a deanonymization script, as it can't reveal a user's real IP address or other identifying details. However, it will reveal if a Tor user is using an Android app. The work of researchers from the Sapienza University of Rome in Italy builds upon previous research that was able to analyze the TCP packet flows of Tor traffic and distinguish between eight traffic types: browsing, email, chat, audio streaming, video streaming, file transfers, VoIP, and P2P. For their work, the Italian researchers applied a similar concept of analyzing the TCP packets flowing through a Tor connection to detect patterns specific to certain Android apps.


How AI can help solve some of humanity's greatest challenges – and why we might fail

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In 2015, all 193 member countries of the United Nations ratified the 2030 "Sustainable Development Goals" (SDG): a call to action to "end poverty, protect the planet and ensure that all people enjoy peace and prosperity." The 17 goals – shown in the chart below – are measured against 169 targets, set on a purposefully aggressive timeline. The first of these targets, for example, is: "by 2030, [to] eradicate extreme poverty for all people everywhere, currently measured as people living on less than $1.25 a day". The UN emphasizes that Science, Technology and Innovation (STI) will be critical in the pursuit of these ambitious targets. Rapid advances in technologies which have only really emerged in the past decade – such as the internet of things (IoT), blockchain, and advanced network connectivity – have exciting SDG applications.


Nokia plugs AI to get MWC ball rolling

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Nokia has announced the launch of its network of Cognitive Collaboration Hubs which will aim to bring telcos and enterprise into its realm to work on a series of AI usecases. Fitting very well into Mobile World Congress' 'Intelligent Connectivity' theme, the network based on a similar Cloud Collaboration Hubs, focusing on developing cloud-based capabilities. While artificial intelligence has been praised as one of the saviours of connectivity and a justification for 5G, the usecases are relatively simplistic, this initiative will aim to correct this. "Network operators are eager to deploy AI to improve network operations and strengthen customer relationships," said John Byrne, Nokia's Service Director for Telecom Technology & Software, Global Data. "Nokia's Cognitive Collaboration Hubs can help accelerate those plans by providing a space for operators, partners and enterprises to co-create new AI solutions utilizing a mix of data science and telco domain expertise."


GLOBAL ARTIFICIAL INTELLIGENCE (AI) IN TELECOMMUNICATION MARKET FORECAST 2019-2027

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KEY FINDINGS The automated chatbots, personalized offers, and efficiently streamlined customer service processes can be managed to provide enhanced customer service by the telecommunication services if the Artificial Intelligence gets integrated with the former. By assimilating advanced technologies like Artificial Intelligence, machine learning, etc. and 5G system, the telecommunication operators, can enhance and implement realization of high levels of self-organization, intelligent management and fault-free networks that are much more reliable as compared to the earlier networks. Advantages like detection of flaws in the network, network security, network optimization & offer virtual assistance are influencing the global market for Artificial Intelligence in telecommunication to propel vigorously at a CAGR of 42.16% from 2019-2027, as estimated by Inkwood Research. Furthermore, the incorporation of artificial intelligence technologies with upcoming wireless networks is appraised to increase the demand & adoption of such artificial intelligence tools & services in the telecommunication sector. MARKET INSIGHTS The upsurge in mobile data traffic & smartphone users across the world and the integration of AI with newer wireless networks will necessarily drive the global AI in the telecom market.Concerns related to incompatibility, the unreliability of artificial intelligence algorithms, lack of skilled personnel & difficulties in the protection of confidential & private data are the primary challenges faced by the market players.


What are the pros and cons of machine learning in network security?

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One advantage of machine learning in network security is that it can identify a zero-day attack. It takes time to identify and analyze a new signature-based attack, but machine learning can apply rules that differentiate legitimate operations from attacks. A new form of malware can be detected based on its actions, so previous observation and analysis are unnecessary. Organizations can prepare machine learning software for operation in several ways. The software can be presented with a set of inputs labeled as attacks and other inputs labeled as legitimate.


Intel and Ericsson develop 5G platform

ZDNet

Intel and Ericsson have partnered to develop a software and hardware management platform for 5G, network function virtualisation (NFV), and distributed cloud. The two companies will combine Ericsson's software-defined infrastructure (SDI) management software and Intel's Rack Scale Design for the multi-year project. "Our infrastructure manageability collaboration with Ericsson will help communications service providers remove deployment barriers, reduce costs, and deliver new 5G and edge services with cloudlike speed on a flexible, programmable and intelligent network," Intel Network Platform Group SVP Sandra Rivera said. It will help carriers deploy open cloud and NFV infrastructure, Ericsson head of Cloud and NFV Business Area Digital Services Lars Mårtensson added, with the product to be demonstrated at Mobile World Congress (MWC) 2019 in Barcelona later this month. In September, Intel had said its technology would be used by Ericsson as well as Nokia in the first series of 5G deployments globally.


Power your AI and modern applications with FlexPod

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As enterprises work towards digital transformation and operational efficiency, they need technology that can adapt to dramatic shifts across the organization and keep up with the ever-increasing demands of modern workloads and applications. Today's businesses are inundated by large volumes of data – data that remains relatively untapped. This data can help uncover critical insights that can drive new and improved customer experiences and create innovative new business opportunities. As these critical insights are needed in real-time, there is a need to ingest, collect, store and process data much more quickly and efficiently than ever before. As a result, IT organizations need a platform capable of supporting modern workloads like Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) as well as next generation databases and enterprise applications.


Q&A: Cisco, Pure Storage dovetail for optimized AI tech - SiliconANGLE

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Key to Cisco Systems Inc.'s evolving software strategy are its strategic acquisitions and partnerships with agile businesses building in artificial intelligence, hybrid cloud, and other developing technologies. While its collaborators offer fresh insights and market opportunities, Cisco's experience and reputable product provide a powerful foundation for innovation, according to Kaustubh Das (pictured, right), vice president of product management at Cisco. Das and Katie Colbert (pictured, left), vice president of alliances at Pure Storage Inc., spoke with Dave Vellante (@dvellante) and Stu Miniman (@stu), co-hosts of theCUBE, SiliconANGLE Media's mobile livestreaming studio, during the Cisco Live event in Barcelona, Spain. They discussed the Cisco and Pure partnership,and how they're working together to facilitate streamlined AI infrastructure in the enterprise. Vellante: Tell us about the partnership.