Unified Communications, Network Security
Article | July 10, 2023
5G trends are shaping the future of various technologies, from the Internet of Things to Virtual Reality. Learn more about the top trends in 5G to stay ahead of the competition in this sector.
Contents
1 The Value of 5G for Businesses
2 5G Trends to Watch in 2023
2.1 Shift to Standalone 5G
2.2 Edge Computing for IoT
2.3 Adoption of Private 5G Networks
2.4 General Availability of 5G
2.5 Partnerships for Rapid Deployments
3 Conclusion
1 The Value of 5G for Businesses
The fifth-generation network technology, or 5G, promises to revolutionize the way businesses communicate and operate. It offers lower latency, faster data transfer speeds, more robust security, and new and enhanced experiences. These capabilities enable 5G to support high-quality video conferencing, real-time collaboration, immersive virtual experiences, and more. By investing in 5G, businesses can stay competitive and meet the evolving needs of their employees and customers. With the growing adoption and use cases of this technology, keeping up with the technology trends in 5G is essential for staying ahead in today's business landscape.
2 5G Trends to Watch in 2023
2.1 Shift to Standalone 5G
The rapid deployment of 5G across the world has been made possible due to the existence of an already-established 4G infrastructure. This has allowed operators to concentrate on developing the radio access network components while relying on 4G networks as a failsafe. This approach has enabled operators to deploy 5G networks at a faster pace, thereby allowing the benefits of this technology trend to reach a wider audience.
The integration of a 5G core and radio forms the backbone of 5G infrastructure, enabling the 5G stand-alone network to achieve its full potential. Wireless providers have been actively promoting the key features of 5G, such as ultra-low latency and complete network slicing, which are exclusively available through the stand-alone version of this advanced technology.
By utilizing this emerging technology, businesses can unlock an entirely new level of performance, allowing them to deliver innovative and immersive services to their end-users. Stand-alone 5G is also a necessity for certain unique use cases, and many 5G trends in 2023 will rely on its capabilities. It is essential for businesses to understand the benefits of this advanced technology and adopt it to remain competitive in the ever-evolving digital landscape.
2.2 Edge Computing for IoT
The convergence of 5G technology and IoT is transforming how businesses operate across industry verticals. This 5G trend enables edge computing for the IoT by providing low-latency and high-bandwidth connectivity. With 5G, data can be transmitted and processed at the edge of the network, closer to the source of the data, rather than being sent to a central data center for processing.
While extensive IoT fleets can operate on a 4G network, a 5G network will improve upon those capabilities with massive multiple-input, multiple output capabilities, enabling an increased number of devices to connect with the cell tower. This is especially useful in IIoT, where a large number of IoT devices are present within a small area, which requires this level of connectivity.
The low latency and high bandwidth offered by 5G infrastructure also support innovative IoT solutions, such as integrating artificial intelligence, by enabling real-time processing of data and faster response times. Edge computing allows IoT devices to perform complex processing tasks and make decisions locally, rather than relying on a centralized cloud server. Businesses that operate in industries that require real-time processing will especially benefit from the digital transformation through 5G.
2.3 Adoption of Private 5G Networks
Private wireless networks are suitable for many industrial applications, and the market for private 5G networks is set to expand rapidly. Private 5G networks offer greater cybersecurity, control, and reliability, making them ideal for mission-critical applications that require high levels of security and privacy. This is one of the key 5G trends because it is applicable to industries such as manufacturing, healthcare, and finance, where IoT devices collect and share sensitive data that requires greater cybersecurity.
Businesses can also utilize private 5G networks to benefit from higher bandwidth, lower latency, and greater flexibility compared to public networks. Private 5G networks can be customized and tailored to meet the specific requirements of each application, making them ideal for specialized functions.
As more enterprises look to benefit from network-intensive technologies such as artificial intelligence, virtual reality, and big data, the demand for private wireless networks will continue to rise. Network operators are also more willing to offer private 5G networks because they represent a new revenue stream and a growth opportunity while also allowing them to provide a more personalized service to their customers.
2.4 General Availability of 5G
The 5G trends have moved towards access to 5G across the world, with 5G now available in 95 countries and reaching to more than 1.2 billion people. 5G networks are becoming more widespread in 2023, and as a result, many 5G trends and technologies are expected to emerge. Furthermore, 5G has become standard across all premium devices and many mid-range ones, making it an attractive option for consumers.
For businesses, this means a whole new world of possibilities. 5G networks offer faster speeds, higher bandwidth, and lower latency, enabling businesses to offer more innovative products and services. With the increased availability of 5G, businesses can develop and deploy emerging technologies like artificial intelligence and machine learning, augmented reality, and virtual reality. Remote work and related use cases will also rise in popularity as 5G becomes more common.
However, the distribution of 5G networks differs by region. 5G trends indicate that urban populations will likely be the first beneficiaries of public 5G rollouts and will benefit the most from 5G capabilities such as network densification and massive MIMO. With the deployment of 5G small cells for connectivity, 5G networks will support new use cases and faster, more reliable connectivity for the general public, especially in urban areas.
2.5 Partnerships for Rapid Deployments
By connecting disjointed B2B and B2C networks with ecosystems, service providers can become service enablers, working with businesses, consumers, and even competitors to create unique 5G offerings. Digital transformation is possible through new approaches to partnerships, through which service providers manage commoditization pressures and a hyper-competitive market.
Partnerships also provide businesses with access to industry skill sets that are in high demand, such as cloud, cybersecurity, and automation. By partnering with players who are already experts, cellular network providers offer specialized solutions to their customers that they may not have been able to provide otherwise. Hosted labs also help to speed ecosystem validation of use cases and new technology, ensuring that solutions are effective and efficient.
Furthermore, partnerships enable service providers to create products with global scale, as demonstrated by SAP, IBM, ServiceNow, and Deutsche Telekom, which have collaborated to create global connectivity offerings ranging from 5G to software-defined networks.
In the race to increase revenue and control costs in the 5G industry, collaborating with industry experts and integrating solutions will become one of the key 5G technology trends. Through collaboration, service providers can offer unique solutions to their customers, access necessary industry skill sets, and create products with global scale. These partnerships are necessary for businesses to remain competitive in an ever-changing market.
3 Conclusion
The ongoing rollout of 5G networks is set to transform businesses across all industries, bringing faster speeds, lower latency, and the ability to connect more devices than ever before. As technology continues to evolve, businesses need to stay up-to-date with the future trends in 5G in order to take advantage of its full potential. The growing demand for low latency and massive connectivity due to new use cases such as edge computing and the IoT is driving the growth of 5G networks. These trends will enable businesses to create new products and services, increase efficiency and productivity, and ultimately transform the way they operate. As 5G networks continue to mature, businesses that invest in this technology will have a competitive advantage over those that do not. They will be able to deliver faster, more reliable services to customers, streamline operations, and reduce costs. With the right approach, organizations can capitalize on the latest trends in 5G and unlock new opportunities for growth and innovation in the years to come.
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Enterprise Mobility
Article | June 15, 2023
Applications of AI/ML
Modern businesses are adopting Artificial Intelligence (AI) that encompasses disciplines like machine learning (ML), natural language processing (NLP), evolutionary computation, etc., to increase their productivity and management capabilities.
Companies like Qualcomm are using AI and machine learning to improve their customer experience.
“Across many industries, we are currently experiencing the creation of intelligent machines that is using AI to simulate smart behavior.”
-Dr. Vinesh Sukumar, Senior Director- Head of AI/ML Product Management at Qualcomm, ( in an interview with Media7)
The application of machine learning in networking is swiftly taking shape. However, as the problems in modern computer networks are getting tedious to handle, AI tools are being introduced to hard-carry their smooth functioning.
Let’s take a look at how network complexity impacts businesses:
Difference in Network Parameters
Different client devices like laptops, smartphones, CCTV cameras, etc., are connected to a single network. However, their requirements and parameters are different. Therefore, the IT team of the business needs to meet them without compromising the functionality and security of the network.
Users Prefer Wireless Networks
Wireless networks are more complex than wired ones. They perform dynamically depending on the number of users, applications, and other variables.
Impact of Cloud Computing
Most applications are now cloud-based, and such a network has multiple data entry points and requires more support.
User Experience
Deciphering root cause analysis, finding correlation and solutions becomes tedious without an AI/ML model. Complex patterns remain unanalyzed, and this creates a vacuum between the customer and the business.
What Does ML Bring to the Table?
Machine learning applications in networking correlate to solving four types of network problems: clustering, extraction, regression, and classification.
For classification and regression, ML clusters similar data and creates a gap between data groups. It then successfully maps a new set of data to a pre-set continuously valued output. As for extraction, it easily establishes a statistical relationship between the data it analyzes.
Machine learning applications in networking encompass the following:
Automation and Cognitive Computing
ML enables automation in data processing by eliminating the human error factor and constantly improving with time. It analyzes data, improves the productivity, security, and health of the network. Cognitive computing allows processing diverse data sets, detecting and finding root causes and common traits within the system.
Network Monitoring & Security
Network monitoring is used to solve problems in a large dataset by deciphering the hidden pattern in the data. It then predicts the outcome for clustered data, malware attacks, or impending network failure. It recognizes impending threats in time and sends out warnings. ML uses anomaly-based intrusion, misuse-based intrusion, or hybrid intrusion to prevent misuse, modification, unauthorized access, or malfunction.
Traffic Prediction, Classification, and Routing
Network traffic prediction is important to handle any mishaps proactively. Network analysis in machine learning is done by using Time Series Forecasting (TSF). By using a regression model solution, TSF finds a correlation between the traffic volume in the future and the traffic previously observed.
Traffic classification ensures Quality of Service (QoS), planning ahead for capacity, security, performance analysis, etc. It helps with proper resource utilization by pinpointing unnecessary traffic in a critical application.
Factors like cost-effectiveness, link utilization, operational capabilities, and policies are also considered by the ML model.
Congestion Control
ML models control the number of packets that enter a network to ensure that the network is stable, fairly utilize resources, and follow queue management employed for congestion control.
Efficiently Managing Resources
ML efficiently manages network resources like the CPU, frequency, switches, memory, routers, etc., by using analytical decision-making.
ML Learning Curve
ML models learn in the following ways:
Pitfalls
Like any other technology, machine learning application in networking comes with pitfalls and limitations. Here are a few:
Data Quality
The efficiency of an ML model is based on the quality, quantity, and diversity of data it processes so it can deduce patterns or identify root causes. Most ML models use simplistic synthetic data for training, validation, and performance. The same cannot be said about practical settings because the data comes from different applications and services and is more complex.
Feasibility
There are scalability and feasibility issues because each network and application is different. Moreover, there are no set standards for uniformity for implementation which makes it hard to set benchmarks or best practices. Control over autonomic networks is distributed and remains limited based on the vendor’s specific devices.
Predictive Analysis and Its Cost
Network analysis and machine learning prediction require additional accurate and effective monitoring investments. Moreover, fault management may have some potholes as there may be a scarcity of normal fault data.
High FPR (False Positive Rates)
Anomaly detection by ML in networking has not created enough buzz in the industry because it generates high FPRs during operations. Also, no detailed anomaly report is generated, so no anomaly history log can be maintained.
Striking a Balance
ML requires time to learn and mitigate issues. It is difficult to identify, in advance, how complex the ML’s approach will be. Striking a balance between the performance and computational cost is difficult. Deciphering comprehensive evaluation metrics is also a tedious task.
No Theoretical Model
There is no theoretical model, in turn, a unified theory, for ML in networking, so each network may have to be learned separately. The current machine learning applications in networking are made keeping in mind certain applications. Over time, more research to tailor ML for certain networks needs to be done. Cross-domain experts who understand both ML and networking are also rare.
Solutions
Software Defined Networking (SDN)
CISCO helped PwC Italy set up a secure network at their new twenty-eight-floor tower with the help of their SD-Access product. PwC wanted a secure, robust network with increased Wi-Fi and wired connectivity for their 3000 employees by streamlining network operations.
“We needed a robust and highly reliable wireless network infrastructure that’s as advanced as the tower itself.”
-Simone Demaria,Network Architect and Infrastructure Manager at PwC Italy
By applying Software Defined Network (SDN), IT personnel can remotely govern network policies in real-time through open interfaces, so traffic engineering is easily possible. SDN also contributes to network virtualization.
SDN supports the upcoming 5G ecosystem. When combined with NFV and VNF, SDN can revolutionize networking.
Going Beyond Traffic Volume & Prediction
To tackle the limitations that TSF-based traffic prediction models have, leveraging features beyond traffic prediction and concentrating on traffic interpolation and sampling could be viable. Research is ongoing on this possibility.
Summing It Up
As the influx of data keeps on increasing, the complexity of networks will increase in tandem. For successfully implementing ML for streamlining networking, the ML approaches we are aware of today need to be upgraded to accommodate multi-layer networks and multi-tenancy so autonomic networking can be a reality.
FAQs
How Can ML Help in Making Networking Smarter?
ML can streamline the network by automation, threat detection, and improving its performance.
How Complex Is Integrating ML into Networking?
The complexity depends on the type of network you are integrating it into.
What to Keep in Mind Before Using Ml in Networking?
Consider investment costs, data availability, feasibility, and scalability.
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Network Infrastructure, Network Management
Article | July 27, 2023
Everyone understands the need to track and trace and tracking was one of the first apps that kick-started the M2M industry at scale about two decades ago. It now encompasses everything from routine shipments to monitoring of high value equipment and has even further proved its worth in the pandemic, enabling tracking of essential shipments and cold chain logistics for vaccines.
With narrowband IoT (NB-IoT) now rolling out across the world, the technology is powering tracking applications for the mass-market, bringing new capabilities and functions to tracking and opening up new markets and use cases. Four essential attributes of NB-IoT, in addition to the fundamental ability of throughput, were discussed in a recent Quectel webinar
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Network Security
Article | October 26, 2021
Cybercrimes have increasingly become a matter of concern for companies worldwide. Over the past few years, the rise of big-ticket ransomware attacks and exposure of perilous software supply chain infections has awakened organizations to various digital dangers.
So, the big question is, how to combat the security threats that are on meteoric growth?
The best solution is to adopt a security vulnerability assessment.
What is Security Vulnerability Assessment?
A vulnerability assessment involves a systematic review of security hazards, which helps identify IT infrastructure’s weaknesses, risks, and vulnerabilities.
When it comes to mitigating vulnerabilities and resolving issues, the collective imperative is to analyze the problem areas before getting them fixed.
A security assessment is critically important to combat the complexities and with an effective vulnerability assessment program, organizations use the tools required to comprehend the probable security weaknesses and enable the protection of systems and data from intruders and unauthorized breaches.
For most organizations, ensuring the safety of devices, networks, applications, and digital assets are part of a broader vulnerability management strategy. It includes an extensive assessment, in-depth processes, and mitigation methods to explore the entire threat spectrum.
Typically, it is conducted regularly. Vulnerability assessment offers a firm assurance in the security of data, especially when some alterations have been implemented or a new service has been added, or, for that matter, and installation of new equipment has taken place.
Each assessment provides a perspective about the risk in its periphery and suggests solutions to control the risk factors and the evolving threats.
Why Security Vulnerability Assessment Is Necessary?
The perpetual threat of cybercrime has necessitated the demand for vulnerability assessments significantly. They make organizations realize their security defects and contribute towards mitigating them.
Hackers are forever ready to make phishing attacks. As per reports, hackers are at work every 39 seconds. Thus, it is extremely important to be vigilant or complacent to activate hackers’ and cybercriminals’ machinations. Over the period, cybercrimes are fluctuating and thus need ongoing attention.
The ideal solution is to undertake consistent vulnerability assessments to safeguard confidential data, systems, and networks. Furthermore, it helps organizations understand the risk and enables smart decision-making.
To ensure security, companies ought to conduct both external and internal scans of their networks.
According to Gartner (paywall), “Large organizations with thousands of employees, tens of thousands of servers and many operating systems receive hundreds of requests per year to patch thousands of vulnerabilities that cannot be remediated in less than 15 days.”
One of the best reasons security vulnerability assessments are important is because it confirms an enterprise’s management processes and whether it has covered every critical patch through outlined existing remediation.
Why Do Companies Need Vulnerability Assessment?
A vulnerability assessment provides companies insightful details on all types of security discrepancies in their environment.
It paves ways to evaluate the risks associated with the flaws.
This helps organizations have a better knowledge of their security scare, overall weaknesses, and assets.
Moreover, the first thing that strikes us on hearing about a cyber-attack is the security of data. With the right and adequate implementation of security assessments, the safety and security of important data could be easily protected. A security assessment would be helpful to reduce irrelevant expenses and make space and increase the IT budget to invest in other key aspects.
Undoubtedly, data breach causes substantial loss to an organization, which leads to legal hassles and financial hazards. In fact, most of the time companies fail to recover the loss.
Thus, it doesn’t harm to place solid policies and methods to strengthen the entire security position of the organization and this can only be possible with a strategic security vulnerability assessment.
In a nutshell, this would keep the companies aware and, in all likelihood, keep the cyber-criminals at bay.
A CASE STUDY ANALYSIS
To cite an example, let’s take how Zensar conducted a three-pronged vulnerability assessment with port scan and penetration scanning. It determined the security of its offerings to meet customer requests for Brainshark, a leading provider of on-demand presentation solutions, helping customers deliver business interaction across 600+ ranking companies in the market.
While Brainshark knew their systems were secure and could also establish it through their documentation, they still undertook a third-party security vulnerability assessment.
Zensar’s vulnerability assessment procedures were based on the industry’s best practices that included tests for SQL injection, cookie manipulation, access control weakness, session state, and cross-site scripting.
The focus of the test was to identify the host and application security concerns. Upon completing the tests and assessments, Brainshark expressed satisfaction and was confident enough in their ability and solution. They knew their security posture was highly protected and secure.
Types of Vulnerability Assessments:
Vulnerability assessments unearth a variety of system and network vulnerabilities. This indicates the reliability of the assessment process, which is implemented with different tools, scanners, and methods that helps discover the vulnerabilities, risks, and threats.
Network-based assessment scanning: It is used to determine the presumptive network security attacks. This kind of scanning can also detect the vulnerable systems on wired as well as wireless networks.
Host-based scans: It is easy to locate the vulnerabilities in servers or other network hosts with host-based scanning. This type of scanning provides visibility into the configuration settings and legacy systems.
Database scans: Database scans ascertain the weak points in a database to preclude malefic attacks.
Application Scans: It examines websites to identify and recognize software vulnerabilities and inaccurate configurations in network or web applications.
Summing Up
Organizations need to be watchful every minute and ensure the security posture is rigorous, which is only possible with security vulnerability assessments. Based on this criterion, understanding company risks gets simplified in turn preventing intrusions and threats.
FREQUENTLY ASKED QUESTIONS
What Are the Advantages of Security Vulnerability Assessment?
There are several advantages attached to security vulnerability assessments. To put it precisely, it can help identify the vulnerabilities before cybercriminals do and determine the level of risk.
Undoubtedly, opting for vulnerability assessment would save a lot of time and money and mitigate the risk and prevent the irrelevant expenditure that follows after the cyber-attacks.
What Are the Disadvantages of Security Vulnerability Assessment?
While vulnerability assessments are highly advisable, it has its share of drawbacks which cannot be ignored. One of the primary limitations of vulnerability assessment is that it does not hint at every vulnerability that exists. Moreover, it sometimes signals false positives too.
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