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6 Ways AI Can Help You Fight Cybercrimes

By
Samita Nayak
-
0
6 Ways AI Can Help You Fight Cybercrimes

Updating existing cybersecurity solutions and enforcing every possible applicable security layer doesn’t ensure that your data is breach-proof. You need to have the strong support of advanced technologies – one that can help you ease the task of security professionals. Thus, it makes sense for you to use AI to fight cybercrimes. With AI in place, many companies have experienced financial gains and saved time while increasing efficiency and productivity throughout the company.

Moreover, business and technology analysts expect to see solid applications of AI and ML to fight cybercrimes. This means that CISOs and security professionals will need to quickly get up to speed on deploying AI solutions to fight cybercrimes. 

Here are 6 ways how AI can help you fight cybercrimes.

Automated Detection

    Together with machine learning, AI can help you quickly identify threats and find links between potential risks, thereby, eliminating human errors from the process. Thanks to ML, AI can now adapt and learn from experience and patterns instead of cause and effect. In fact, today ML has made it possible for machines to teach themselves. It means that they can create models for pattern recognition instead of waiting for humans to develop them. AI is trained to process large amounts of data and can easily tap into reasoning to determine various risks, for example, suspicious addresses, strange files, and so forth, before initiating suitable remedies.

     Anomaly Detection

    AI is significantly improving the duration it takes to identify suspicious issues on websites. Thus, developers today are leveraging AI to identify people with bad intentions on sites. This process is referred to as anomaly detection and has several uses with cybersecurity topping the list. Depending on your Artificial Intelligence techniques, the program can analyze tons of visitors and categorize them based on their threat level and behavior in just a few seconds.

    Better Monitoring and Analysis

      AI gives you greater visibility within their security environment. And also gives you the ability to get ahead of threats. A well-designed AI-powered technology can determine whether or not your organization is under attack. This data in turn will help you take the necessary steps to fight cybercrimes before any threat approaches your organization.

      Secure Authentication

        If you own a site that needs visitors to log in, feature forms that require input, or require you to provide another layer of security on the site’s backend – AI can better the authentication process with utmost safety. 

        One way to ensure secure authentication is via physical identification, where AI uses different factors to identify a person. For instance, a smartphone can use fingerprint scanners and facial recognition to allow you to log in. The process behind this entails the program analyzing main data points about your face and fingers to discern if the login is authentic. Apart from that, AI can look into other factors to determine if a specific user is authorized to log in to a technology device. The tech scrutinizes the way you enter keys, your typing speed, and your error rate while spelling something. Isn’t that amazing?

        Quicker Response Time

          AI can process massive amounts of unstructured information to provide insights with greater efficiency. What more? With ML, AI can learn patterns much more quickly. Thus, accelerating response time, making it faster and easier to stop threats before they cause problems. Some of the leading companies like IBM and others are now using cognitive technologies and AI in cybersecurity to identify threats quickly and respond accordingly. 

          Error-Free Cybersecurity

            Unlike humans, AI doesn’t get tired or bored when performing repetitive/mundane tasks. As such, the risk of human error is reduced significantly. Nonetheless, humans need to work with AI for better results.

            No doubt, humans offer the common sense and rationality that machines lack. However, AI-designed applications are better decision-makers in various situations.

            Wrapping Up

            Artificial intelligence and machine learning tools could go a long way to help fight cybercrimes. AI’s crucial role right now is to offload work from human cybersecurity engineers, to handle the depth and detail that humans cannot tackle fast or accurately. Advances in ML technology mean that AI applications can automatically adapt to changes in threats and spot problems as they arise. The above examples are only some of the ways AI can help you govern and manage cybersecurity and fight cybercrimes. And, as developers continue to provide more data points to existing programs as they create new forms of AI, it is safe to say that AI will help fight cybercrimes even more effectively in the future.

            6 Key Elements for a Successful Cloud Migration

            By
            Siddhraj Thaker
            -
            0
            6 Key Elements for a Successful Cloud Migration

            Moving to the cloud offers several benefits for businesses such as improving operational performance, security, scalability and agility. It enables remote working which is essential in today’s world and businesses can migrate workloads to the cloud anytime.

            6 steps to successfully migrate applications to the cloud

            Here are six steps to take when moving your business to the cloud.

            1. Create a strategy

            To accomplish a successful cloud migration, it is essential to have the right approach and strategy. Moving to the cloud is an extensive process that when done correctly offers several benefits. Start with capturing baseline metrics of the IT infrastructure and map workloads to the apps and assets. This helps in establishing cloud migration key performance indicators such as memory and CPU usage, availability, conversion rates, and page load and response times.

            2. Identify the suitable applications for your needs

            Some apps perform better on hybrid or private clouds and some work better on a public cloud. Applications can either need minor tweaking or in-depth code changes. It is best to first identify the applications best suited for your business needs. Do a complete analysis of the complexity, architecture, and implementation of the apps before moving to the cloud. Consider which apps require a redesign, which can be moved as it is, and if the provider offers services to allow migration without the workloads being reconfigured.

            3. Find the right cloud provider

            Moving to the cloud is a complex process. One of the most important key elements of a successful migration is selecting the right service provider. The right provider can guide the migration process while the transition is going on and even after that. Consider the tools offered by the provider, the level of experience, and the support it offers for the migration and beyond. 

            4. Maintain operational continuity and integrity of data

            Cloud migration can be risky as sensitive data can be exposed. Hence, it is critical to manage risk effectively. To ensure that automated controls produce the same outcomes, pre-migration validation of the business processes is important. The normal operations should not be disrupted in this process.

            5. Use an end-to-end approach

            The cloud service providers should have a strong methodology for all aspects of the migration process, including the framework for managing complex transactions consistently. Ensure that it is mentioned in the service-level agreement with set milestones and checkpoints for the progress throughout the process.

            6. Execute the migration

            Migrating to the cloud depends on the architecture of data and the architecture and complexity of the applications. You can do a test to see if the application is moving without complications and then switch over your on-premises traffic. Another approach is first moving customers over, validating and continuing it until all customers are moved. 

            Summing Up

            Cloud migration is an extensive process but when completed successfully offers a lot of benefits:

            • Increased operational performance
            • Cost savings in terms of storage and getting technical help
            • Improved security and reduced risks
            • Ensured business continuity in case of any incidents

            8 Best Angular IDE and Tools of All Time to Use for Web Development

            By
            Samita Nayak
            -
            0
            8 Best Angular IDE and Tools of All Time to Use for Web Development

            When it comes to web development, Angular is one of the most popular frameworks. And with good reason – it’s powerful, versatile, and easy to use. But what about the tools you need to get the most out of Angular? In this article, we’ll take a look at some of the best Angular IDE tools available.

            8 Best Angular IDE And Tools for Web Development

            Here are 8 of the best Angular IDE and tools to use for web development.

            • WebStorm
            • Angular IDE by CodeMix
            • Visual Studio Code
            • Atom
            • Brackets
            • Eclipse
            • Sublime Text 3
            • Vim

            Each of these provides unique features that can streamline your workflow and make Angular development easier.

            1. WebStorm

            WebStorm is a powerful IDE with great support for Angular development. It has built-in support for TypeScript, so you can get up and running quickly with strong type-checking. Also, it comes with many handy features specifically for Angular development, like code completion for Angular templates and a definition function for Angular components. 

            2. Angular IDE by CodeMix

            Angular IDE by CodeMix is a great option if you’re looking for an IDE with Angular-specific features. It includes a wide range of features like code completion, TypeScript support, and inline debugging. Plus, it has a special Angular Language Service that provides code intelligence for Angular templates.

            3. Visual Studio Code

            Visual Studio Code is a popular code editor that also happens to be very well-suited for Angular development. It has strong TypeScript support and comes with many helpful Angular-specific extensions, like the Angular Language Service and the Angular Snippets extension.

            4. Atom

            Atom is a hackable text editor from GitHub that’s gained popularity in recent years. It’s a great choice for Angular development, thanks to its support for TypeScript and its many Angular-specific packages.

            5. Brackets

            Brackets is another code editor that’s well-suited for Angular development. It has strong TypeScript support and comes with an Angular Language Service extension. Plus, it has a live preview feature that makes it easy to see your changes as you make them.

            6. Eclipse

            Eclipse is a popular Java IDE that can also be used for Angular development. It has strong TypeScript support and comes with an Angular Language Service plugin. Also, it includes features like content assist and code completion that can save you time when coding in Angular templates.

            7. Sublime Text 3

            Sublime Text 3 is a popular code editor with a clean, minimalist interface. It’s a great choice for Angular development, thanks to its support for TypeScript and its many Angular-specific packages.

            8. Vim

            Vim is a powerful text editor that’s beloved by many developers for its flexibility and extensibility. And, it’s also a great choice for Angular development, thanks to its excellent TypeScript support and many Angular-specific plugins.

            Wrapping Up

            These are some of the best Angular IDE tools available till date. So if you’re looking for a way to streamline your Angular development workflow, be sure to check out one of these options.

            Decoding Google Analytics 4 and Its Top 4 Features

            By
            Siddhraj Thaker
            -
            0
            Decoding Google Analytics 4 and Its Top 4 Features

            The marketing community is abuzz with a new-found word – Google Analytics 4 or GA4. It is not a marketing jargon but the latest version of the very powerful analytics tool. Businesses have commenced bidding adieu to Universal Analytics (previous versions) and exploring the new one. GA4 comes with advanced and extensive features, so businesses have access to enormous data for decision-making purposes.

            What is Google Analytics 4?

            Google Analytics 4, originally released in October 2020, is the latest version of Google’s analytics suite and is their next-generation measurement solution which will be replacing Universal Analytics as standard Universal Analytics properties stopped processing new data on July 1, 2023, and all customers will lose access to the Universal Analytics interface and API starting on July 1, 2024.

            Google Analytics is one of the most widely used tools in marketing. It offers insights into website traffic and measures marketing campaign performances, KPIs, and more. The new version (the App + Web property) tracks website and app data together and gives a better picture of the data. You can consider it to be an expansive and more powerful tool than universal analytics.

            GA4 uses AI and comes with a better user interface comfortable both for amateurs and professionals. It has several distinctive features different from the previous versions.

            Universal Analytics vs Google Analytics 4

            At first glance, you may feel that GA4 is complex and intimidating as several metrics and reports appear different. The tracking events in Universal Analytics and the new version are also distinct. The measurement model of universal analytics is based on page views and sessions. Google Analytics 4 works on an event-based measurement model where everything (e.g., page view) is seen as an event. Another unique feature of GA4 is there is no option to create separate views online like the older version. You can only create data streams for apps and websites.

            4 Noteworthy features of Google Analytics 4 setup

            What features of GA4 make it distinct and a standout among marketers? Let us take a look at them.

            1. Better data controls

            With an increased demand for data privacy among businesses, Google has come up with new data controls in its latest analytics tool.

            These include:

            • Marketers and businesses have control over how they collect, retain, and share data
            • Users can decide whether they wish to use the collected data for ad personalization
            • Marketers can delete analytics data whenever they wish to by submitting a request to Google

            GA4 can adapt to a cookieless future. It uses machine learning to help marketers customize their campaigns and have accurate data.

            2. Customer-focused measurements

            The customer-focused metrics of GA4 help marketers gain insights into how customers interact with their websites. For example, if a customer purchased from your website or app, you’ll know what steps they took before. You can learn whether they saw your ad on Google or YouTube led them to the website or app, etc. In a way, you get an overview of your customer’s life cycle.

            3. Great marketing insights

            Google Analytics 4 uses advanced machine learning abilities that can automatically find trends in your data and alert you about the same. It understands and predicts user behavior and helps you plan your campaigns well. GA4 has special metrics – predictive metrics – that help you prioritize the right audience and identify issues.

            4. Deeply integrated with Google Ads 

            GA4 analytics is deeply integrated with Google Ads. It assists you in building custom audiences. It identifies high-value, specific audiences so you can target them better with organic or paid campaigns. The analytics also helps in tracking conversions from YouTube.

            The Power of Generative AI Tools for Innovation

            By
            Samita Nayak
            -
            0
            The Power of Generative AI Tools for Innovation

            Do you ever wonder how innovation can be sparked, ideas can be nurtured, and creativity can be unleashed in the digital age? In a world where technology is evolving at an unprecedented pace, the key to staying ahead of the curve lies in the realm of generative AI tools. But what are these tools, and how can they transform our approach to innovation?

            What Are Generative AI Tools?

            Generative AI tools are sophisticated algorithms designed to generate new, creative content such as text, images, music, or even entire designs. They operate on the principle of machine learning, where the system learns patterns from vast amounts of data and uses this knowledge to create something entirely new.

            Fostering Creativity: Breaking Boundaries

            Generative AI tools break the boundaries of human creativity. They allow us to explore uncharted territories, imagine the unimaginable, and innovate without limits. By leveraging these tools, industries ranging from art and design to healthcare and engineering are pushing the envelope of what’s possible.

            Enhancing Collaboration: Humans and AI Working Hand-in-Hand

            One of the remarkable aspects of generative AI tools is their ability to enhance collaboration. Imagine a scenario where humans and AI work together, each complementing the other’s strengths. Creative people can use AI-generated ideas as a springboard, adding their unique touch to create masterpieces.

            Boosting Efficiency: Accelerating Innovation Cycles

            Innovation often involves trial and error, but generative AI tools reduce the time spent on experimentation. They accelerate innovation cycles by rapidly generating diverse concepts. This efficiency allows businesses to iterate and refine their ideas swiftly, staying ahead in the competitive landscape.

            Conclusion

            Generative AI tools are not just machines; they are catalysts for human ingenuity. By harnessing the power of these tools, we embark on a journey where creativity knows no bounds, where collaboration is seamless, and where innovation thrives. So, are you ready to explore the limitless possibilities offered by generative AI tools? Embrace the future of innovation and watch as your ideas transform into groundbreaking realities.

            Top Benefits of Deploying Secure Internet Access Solutions

            By
            Samita Nayak
            -
            0
            Top Benefits of Deploying Secure Internet Access Solutions

            The rise of remote work and hybrid cloud environments has exposed limitations in traditional connectivity models like VPNs (Virtual Private Networks) and MPLS (Multiprotocol Label Switching). Designed for on-premise networks, these technologies struggle to scale and manage the dynamic needs of today’s distributed organizations. They may not handle the increased demand or provide the security and performance required.

            New Solutions for a Modern World

            To address these challenges, organizations are turning to newer technologies like software-defined wide area networks (SD-WAN) and zero-trust networks. These solutions offer greater flexibility, scalability, and enhanced security for hybrid and remote work environments.

            Benefits of Secure Internet Access Solutions

            Secure internet access solutions empower businesses with remote and hybrid workforces. Here’s how they can boost security and productivity:

            URL Filtering

            This feature allows or blocks websites based on their address. It compares requested URLs against an approved or blocked list, ensuring users reach appropriate sites. This helps enforce internet usage policies and protects against cyber threats.

            Anti-Malware Protection

            This security feature safeguards against malicious software (malware). It inspects both encrypted and unencrypted web content to identify and block threats. Different techniques like signature-based detection, heuristics, and behavioral analysis are used for this purpose.

            Application Control

            Administrators can define policies for authorized applications with application control. This prevents unauthorized or malicious software execution, ensuring compliance with internal policies and protecting against cyber threats.

            Simplified IT Operations

            Consolidating complex IT solutions into a single, integrated platform makes IT operations more agile. This reduces complexity and simplifies changes and updates.

            By implementing these solutions, businesses can empower their remote and hybrid workforces while maintaining strong security and efficient operations.

            Manufacturing Goes Green: Enabling a Circular Economy with IoT and Big Data

            By
            Vaishnavi K V
            -
            0
            Manufacturing Goes Green Enabling a Circular Economy with IoT and Big Data

            In the quest for a more sustainable future, the manufacturing industry is playing a crucial role. By implementing circular economy principles, businesses are finding ways to reduce waste, minimize resource use, and create closed-loop systems that keep materials in use for as long as possible. 

            At the heart of this movement is the Internet of Things (IoT) and Big Data analytics. By leveraging these technologies, manufacturers can gain real-time insights into their operations and make data-driven decisions that improve efficiency, reduce environmental impact, and cut costs. 

            What is the Circular Economy?

            The circular economy is a regenerative economic model that aims to minimize waste and maximize the use of resources. In this model, products are designed to be reused, repaired, and recycled, rather than disposed of after use. By keeping materials in use for as long as possible, the circular economy aims to reduce resource consumption and minimize environmental impact. 

            How IoT and Big Data are Enabling the Circular Economy in Manufacturing 

            In the manufacturing industry, IoT sensors are being used to monitor equipment and processes in real time. Basically, by collecting data on everything from energy use to machine performance, manufacturers can gain a better understanding of their operations and identify areas for improvement. 

            This data is then fed into Big Data analytics platforms, where it is analyzed to uncover patterns and insights. By applying machine learning algorithms to this data, manufacturers can identify opportunities to optimize their operations and reduce waste. 

            For example, IoT sensors can be used to track the movement of materials throughout the manufacturing process. By monitoring the location and condition of materials, manufacturers can identify opportunities to reuse or recycle them, rather than disposing of them after use. 

            Similarly, organizations can use IoT sensors to monitor the energy use of equipment and identify opportunities to reduce energy consumption. By optimizing energy use, manufacturers can not only reduce their environmental impact but also cut costs. 

            The Benefits of the Circular Economy in Manufacturing

            By adopting circular economy principles and leveraging IoT and Big Data technologies, manufacturers can achieve a range of benefits. These include: 

            Reduced waste

            By reusing and recycling materials, manufacturers can minimize waste and reduce their environmental impact. 

            Lower costs

            By optimizing operations and reducing waste, manufacturers can cut costs and improve their bottom line.

            Increased efficiency

            By leveraging IoT and Big Data, manufacturers can identify inefficiencies in their operations and make data-driven decisions to improve efficiency.

            Improved sustainability

            By adopting circular economy principles, manufacturers can contribute to a more sustainable future and enhance their reputation as responsible business. 

            In Conclusion

            The manufacturing industry is transforming as businesses look for ways to reduce their environmental impact and create a more sustainable future. By adopting circular economy principles and leveraging IoT and Big Data technologies, manufacturers can achieve these goals while also improving efficiency and cutting costs. As we move towards a more sustainable future, the circular economy will undoubtedly play a crucial role in shaping the manufacturing industry. 

            The Rise of Cognitive Computing Platforms

            By
            Samita Nayak
            -
            0
            The Rise of Cognitive Computing Platforms

            Remember those futuristic movies where machines could understand and respond to human emotions? Well, get ready as science fiction is slowly turning into science fact. We’re witnessing the rise of cognitive computing platforms – powerful AI systems that mimic human thought processes and are revolutionizing the way we interact with technology.

            So, what exactly is a cognitive computing platform?

            Think of it as a computer system that can do more than just crunch numbers. It can analyze tons of data, learn from experience, and even understand natural language. These platforms combine artificial intelligence (AI) with machine learning, reasoning, and natural language processing (NLP) to create a truly intelligent system.

            Who are the Key Players in this Cognitive Computing Field?

            Several big names are leading the charge in this exciting field. Here are a few to mention.

            IBM Watson

            This AI powerhouse uses machine learning to analyze information and answer questions in a human-like way.

            Microsoft Azure Cognitive Services

            This suite of AI tools offers features like facial recognition, sentiment analysis, and language translation, making it a versatile platform for developers.

            Amazon Rekognition

            Don’t be fooled by the name, Rekognition goes beyond just recognizing faces. It can identify objects, scenes, and even inappropriate content in images and videos.

            Google Cloud AI Platform

            Google’s offering provides a wide range of AI tools and services for developers to build intelligent applications. From text-to-speech to natural language understanding, Google Cloud AI has it all.

            What Innovations Are These Platforms Bringing to the Table?

            The applications of cognitive computing platforms are vast and ever-evolving. Here are a few examples.

            Healthcare

            Cognitive computing in healthcare has the potential to analyze medical images, diagnose diseases with greater accuracy, and even personalize treatment plans.

            Customer Service

            Tired of frustrating chatbots that just can’t understand your questions? Cognitive computing platforms can power intelligent chatbots that can engage in natural conversations and resolve customer issues efficiently.

            Finance

            These platforms can analyze complex financial data, identify trends, and even predict market movements, making them valuable tools for financial institutions.

            The Future of Cognitive Computing: A World of Possibilities

            The rise of cognitive computing platforms is just the beginning. As these systems continue to learn and evolve, we can expect even more groundbreaking innovations in the years to come.

            But is this rise of the machines something to fear? Not necessarily. Cognitive computing platforms have the potential to make our lives easier, more efficient, and even safer. The key is to ensure these platforms are developed and used ethically and responsibly.

            Role of Robotics and AI in Modern Manufacturing

            By
            Ishani Mohanty
            -
            0
            Role of Robotics and AI in Modern Manufacturing

            With the advancement in technology, AI is undoubtedly becoming a major factor in many industries. AI is a broader term for computer systems that can process information and make decisions on their own. In the early days, AI was only able to recognize and respond to simple commands, but after the advancement in technology, AI can take complex tasks, and complete them with very little human input.  

            People often get confused between robotics and AI; both are two distinct technologies that enable machines to act, think, and interact with the environment.  

            Precision and Accuracy 

            By deploying robots on assembly lines or using AI based algorithms, companies can drastically reduce production time and enhance overall efficiency level. Machines powered by AI algorithms can perform repetitive tasks with unparalleled precision and accuracy.  

            Precision is a metric that measures how often a machine learning model correctly predicts the positive class We can calculate precision by dividing the number of correct positive predictions by the total number of instances, the model predicted as positive.  

            Accuracy is a metric that measures how often a machine learning model correctly predicts the outcome. We can calculate accuracy by dividing the number of correct predictions by the total number of predictions.  

            Increase in Productivity 

            Robotics and AI have always played a crucial role in modern manufacturing by increasing productivity through automation. These technologies streamline repetitive tasks, reduce errors, and enable continuous operation leading to an increase in efficiency in production processes. They also facilitate data-driven decision-making, optimize resource utilization, and contribute to overall cost savings for the manufacturers.  

            Adaptive Manufacturing 

            Adaptive manufacturing associated with robotics and AI plays a crucial role in modern manufacturing by increasing flexibility, efficiency, and responsiveness. Robotics with AI features enable machines to adapt to the change in production needs, optimizing processes, and improving overall productivity. AI algorithms analyze data in real time, making quick decisions to reduce production parameters, ensuring quality control, and many more. AI and robotics contribute equally to adapting to the changes and challenges of today’s rapidly changing production landscape.   

            Cobots 

            Cobots or Collaborative robotics play the role of working alongside humans to ensure safety and enhance efficiency. AI-driven robots take up repetitive tasks and allow human workers to focus on more complex work of production. The collaboration between robots and humans improves overall productivity and reduces the workplace’s injuries. AI in manufacturing keeps a check on the maintenance quality control, and adaptive manufacturing process, contributing to a more flexible and cost-saving production environment. 

            Quality Control and Inspection 

            Robotics and AI play an important role in quality control and inspection in modern manufacturing. They increase precision, speed, and efficiency for checking defects, ensuring quality production, and reducing human error. The work of AI algorithms not only increases efficiency but also reduces the risk of human error in the inspection process. Robotics even perform tasks, in challenging atmospheres, ensuring improved safety and reliability in manufacturing operations. 

            Conclusion 

            The integration of robotics and AI into modern manufacturing processes is not just a technological evolution but a revolution.  

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