Network as a Service (NaaS): A Technology Businesses Need Today

Network Management, Network Security

Article | July 17, 2023

According to the GSMA 2020 report, 600 million people do not have mobile network coverage and 3.4 billion people do not have mobile Internet access. Most of these areas are remote, difficult to obtain site transmission and power, and high infrastructure costs. As a result, the return of investment (ROI) of traditional solutions is usually as high as 8 to 10 years. Operators are not willing to deploy networks.

Network Management

Article | November 22, 2021

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? 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Network Infrastructure, Network Management

Article | July 27, 2023

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. { "@context": "https://schema.org", "@type": "FAQPage", "mainEntity": [{ "@type": "Question", "name": "What Are the Advantages of Security Vulnerability Assessment?", "acceptedAnswer": { "@type": "Answer", "text": "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. 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Article | April 14, 2020

Before the COVID-19 crisis, the biggest news in tech was the ongoing -- and controversial -- rollout of the 5G network. First, there was the ban on Chinese companies, prohibiting them from being involved with 5G infrastructure in the U.S., U.K. and Australia. Then articles started pointing out that the threat profile for 5G was an order of magnitude higher than that of existing telecom protocols. The coronavirus outbreak, though, has forced some analysts to reassess the value of 5G. While security concerns remain, the network has been invaluable in the fight against the pandemic.