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    1Jun, 2024
    Audi virtualizes factory with software PLCs

    Audi has implemented virtual PLCs at one of its plants, with the aim of reducing the variety and number of hardware devices needed and converting applications to run in software thus making production faster, more robust, and more flexible.

    A key aim of the German car-maker Audi is to have stable and consistently available production facilities where it can build as many cars as possible. But to speed up the integration of innovations from the rapidly developing world of IT, and to optimize production continuously, this production needs to become more IT-oriented.

    A major challenge for Audi is the wide variety of devices that it uses. To adapt production to increasing customer demand, more hardware devices must be installed. However, in recent years, delivery periods have become stretched. Often, updates have to be installed manually on the hardware devices and maintenance can be costly, but both are necessary to ensure cybersecurity. Power consumption is also high. As more hardware devices are installed, more power is consumed, affecting energy efficiency.

    To meet these challenges, Audi realized that it needed to merge IT and OT in its production environments by virtualizing the shop floor. It has therefore created a new software-based infrastructure modeled on how data centers are implemented.

    The lowest level of the infrastructure is always the same and lays the foundation for various applications. With its Edge Cloud 4 Production platform, Audi has transferred this principle to production and has revolutionized automation on its shop floor, including the use of virtual PLCs.

    The platform has been created by a team of IT and OT specialists who’ve designed a private cloud infrastructure that covers all of the production requirements in a factory. Applications run in this cloud as software – including Siemens’ Simatic S7-1500V virtual PLC.

    After some initial debate about how IT-based production should be designed, it quickly became clear that a large-scale concept was required. It took about three years to evaluate its feasibility and perform the necessary tests. This period was needed to define requirements, test conditions, and talk to the manufacturers of the necessary components. This way, the partners in the virtual PLC project were already benefitting from each other early on: Audi from Siemens’ expertise in the field of automation engineering, and Siemens from Audi’s feedback. The technologies also needed to be modified: for example, to establish the real-time capability of the lower-level infrastructure.

    Software-driven factory automation is only feasible if suitable software-based controllers are available. Audi needed a virtual PLC that would be compatible with its Edge Cloud 4 Production platform and could be integrated into its existing automation environments.

    “The virtual PLC represents a revolution in automation engineering and industry, making it possible to rethink a factory and its infrastructure,” says Sven Müller, project manager for Edge Cloud 4 Production at Audi.

    The Simatic S7-1500V virtual PLC was first tested successfully in Audi’s production laboratory. Part of the line being used to produce Audi’s e-tron GT high-performance electric car at the company’s Böllinger Höfe plant in Neckarsulm was then chosen as suitable for the initial commissioning of the virtual PLC in a production environment. The line’s small-series manufacturing was ideal for testing the new technologies.

    Working with Siemens, Audi performed tests at the plant to learn about the on-site setup and to discover if there were any challenges that might hamper the implementation. This cautious approach helped to increase employee acceptance. The growing number of successful tests boosted Audi’s confidence in the virtual PLC.

    “Naturally, employees were initially skeptical and expressed reservations,” acknowledges Robin Fallmann, who is involved in production planning for automation engineering at Audi. “This was our motivation for making the rollout planning for the overall project as detailed and predictable as possible.”

    Before commissioning the technology in a working production environment, there was a preparatory phase, lasting several months, during which servers were built, the network was planned, components were installed, and connections to the industrial edge were set up.

    According to Pascal Schirmer, the member of the Edge Cloud 4 Production team who was mainly responsible for the initial implementation, the preparatory phase was successful because all of the participants had agreed on clear goals, and each of them had invested the time needed to achieve the agreed milestones on schedule. The experience will contribute to the implementation of subsequent rollouts, he adds.

    Implementation

    The virtual PLC was introduced in the spring of 2023. At the time, Audi was already starting to convert its first assembly plant to Edge Cloud 4 Production. The cloud went live in July 2023.

    Preparations for implementing the virtual PLC started soon after that and required close collaboration between Audi, Siemens, and other technology partners. Since January 2024, two virtual PLCs have been deployed successfully on the e-tron GT axle assembly line in Audi’s Böllinger Höfe factory.

    Although the conversion to IT-based shopfloor automation is a huge step, the site’s employees have hardly noticed the change. They continue to access all the functions that they know from hardware PLCs, as well as familiar user interfaces and tools. Thanks to compatibility with the Siemens TIA Portal platform, no other programs have needed to be written for the virtual PLC.

    The uniform infrastructure ensures that all of the virtual applications operate on the same basis, allowing complete digital management. Activities can be conducted centrally or remotely. Management via the cloud production platform also enhances cybersecurity, because many of the previous attack vectors have been removed from the production environment.

    Because the virtual PLC is downloaded as software and deployed via an industrial edge platform, the problems of extended delivery periods and the need to install hardware components have both been eliminated. Additional instances of the PLC can be downloaded if needed, and unnecessary instances can be uninstalled. This saves money and energy. Updates, and apps from industrial edge management, can also be rolled out quickly and easily plant-wide and on a remote basis.

    In addition to the technological hurdles, many organizational challenges also needed to be overcome. Employees and management had to be won over to the concept of IT-based factory automation, the functionality of the virtual PLC had to be demonstrated, and responsibilities had to be assigned. An Edge Cloud 4 Production team was established that allowed IT experts to collaborate closely with OT specialists. Thanks to extensive testing at the plant and close alignment between the IT and OT teams, Audi and Siemens were able to commission the new technology relatively smoothly.

    Just the start

    The successful initial implementation of the virtual PLC is just the starting point. Over the next few years, both the virtual controller and the cloud-based infrastructure will continue to be developed, tested and rolled out further.

    The priority in the coming months is to train employees at the Böllinger Höfe plant in the new technology. The first apps from Industrial Edge Management are also being rolled out and tested, including Siemens’ Sinec Traffic Analyser. The apps can be downloaded and used flexibly, and can be deleted later when they are no longer being used.

    The initial implementation lays the groundwork for learning organizational and operational lessons. For example, there are plans to test a virtual operator panel, and any potential obstacles to the plant’s everyday operation will be detected. Challenges that arose in the initial implementation were overcome thanks to the dedication of the project partners. Based on the successful collaboration to date, they are optimistic about the future of the project.

    Ref: Link

    13Dec, 2023
    Scaling Security Operations with Automation

    In an increasingly complex and fast-paced digital landscape, organizations strive to protect themselves from various security threats. However, limited resources often hinder security teams when combatting these threats, making it difficult to keep up with the growing number of security incidents and alerts. Implementing automation throughout security operations helps security teams alleviate these challenges by streamlining repetitive tasks, reducing the risk of human error, and allowing them to focus on higher-value initiatives.

    While automation offers significant benefits, there is no foolproof method or process to guarantee success. Clear definitions, consistent implementation, and standardized processes are crucial for optimal results. Without guidelines, manual and time-consuming methods can undermine the effectiveness of automation.

    This blog explores the challenges faced by security operations teams when implementing automation and the practical steps needed to build a strong foundation for successful implementation.

    The Automation Challenge

    Organizations often struggle with automation due to a lack of well-documented processes and limited resources. With constant alerts and fires to put out, security teams are often spread thin, and only have time to focus on the task in front of them. This leaves them little to no time for proper documentation of processes and procedures. This, along with other factors such as maturity and process monitorability, contributes to the challenges security teams face when implementing automation. Successful automation requires a pragmatic approach, where teams identify and prioritize processes that are feasible and provide the greatest impact on efficiency and risk reduction.

    When considering the feasibility of automation, it becomes crucial to assess whether the processes and procedures in place can be seamlessly automated from start to finish. Not all tasks are suitable for complete end-to-end automation. The decision to automate certain processes should be based on factors like the organization’s maturity level, the available time and resources, and the ability to monitor and ensure the feasibility of the automation efforts. It requires careful evaluation to determine if automation makes sense and can effectively streamline security operations.

    Identifying Automation Maturity

    To reach effective security automation, organizations must assess their readiness and maturity level. A comprehensive assessment involves evaluating three critical investigation processes.

    Evidence Gathering

    This process involves querying information across the organization’s technology environment. Historically, the biggest problem with this process is that it has been manual. Organizations usually have a multitude of different technologies, all of which speak their own different languages, resulting in extensive amounts of time spent pivoting from tool to tool gathering data for any given investigation.

    Automation can greatly enhance this stage by unifying and simplifying queries, thereby eliminating the complexities associated with different logging systems and query nomenclatures. A security orchestration, automation, and response (SOAR) solution can prove to be extremely useful here. However, the main hurdle with implementing SOARs lies in integration, maintenance, and upkeep. If organizations are already facing resource constraints, attempting to set up a SOAR becomes even more challenging as they may not have sufficient people available to handle incidents effectively while also maintaining a SOAR.

    Analysis

    Once evidence is gathered, the analysis stage takes the output of evidence gathering and analyzes it against internal and external. Automation can help extract insights, identify patterns, and accelerate the detection of potential threats, but it is important to note that the analysis process often requires human intervention to ensure accuracy and effectiveness.

    Depending on what is being analyzed, human involvement may be necessary. For instance, when dealing with critical assets, vulnerability scanning, or identifying all the root and admin accounts within a system, it’s essential to have internal human intelligence reviewing and verifying the information.

    Remediation

    This process involves responding effectively to true-positive alerts within an environment. Remediation greatly depends on the efficacy of everything built before that. It’s going to be extremely difficult to have confidence in your remediation process if you don’t have all the data, you need or if there are gaps in your internal or external intelligence.

    Practical Automation Development

    It’s crucial to understand what processes and procedures are in place when responding to threats. Depending on where an organization is in their maturity journey, it might be hard to know where to start with implementing automation. Building a solid foundation for automation involves following a systematic and iterative approach. Below are five steps organizations can use to better implement automation:

    1. Interview Security Teams: Engage with security teams about their existing processes and identify use cases suitable for automation.
    2. Identify Use Cases: Identify automation use case opportunities based on those interviews. Prioritize high-volume, repetitive tasks or those with significant human effort. Focus on one process at a time to avoid complications caused by rushing through multiple processes without proper understanding and development.
    3. Document Findings: During the documentation phase, analyze actions in consoles and compare them with the corresponding API endpoints. Changing technologies and unexpected variables can disrupt processes. To mitigate any disruptions, it’s crucial to have a solid understanding of the APIs being used and document the findings thoroughly. By integrating this documentation into the overall workflow, any deviations from the initial assumptions can be identified and addressed promptly.
    4. Develop a Feedback Loop: Incorporate the security operations team’s insights, suggestions, and expertise throughout the development process to ensure the automation solution aligns with the organization’s needs and enhances productivity.
    5. Measure and Assess: After implementing automation, measure its effectiveness and efficiency. Continuously assess the impact and gather feedback from the security team. Use these insights to fine-tune the automation techniques and address any emerging edge cases.

    To have a successful automation foundation, it’s not enough to simply create and deploy automation solutions. It’s also important to integrate automation into existing security operations workflows. This process of operationalization ensures that automated processes and human decision-making can work together seamlessly.

    Conclusion

    Implementing automation is crucial for organizations to combat the increasing security threats in today’s digital landscape. It streamlines tasks, reduces human errors, and enables security teams to focus on higher-value initiatives. However, success in automation requires clear definitions, consistent implementation, and standardized processes. Organizations should assess feasibility, readiness, and maturity level, and follow a systematic approach for practical automation development. By integrating automation into existing workflows and identifying relevant use cases, security teams can maximize the benefits and leverage the expertise of professionals. A solid foundation for automation can reduce response times, improve accuracy, minimize errors, and enhance threat detection in various security processes for organizations.

    Resource : https://thehackernews.com/2023/12/scaling-security-operations-with.html

    15Mar, 2023
    Digital twins could be the key to successful automation

    Automation has delivered significant benefits for organizations that have taken the necessary steps to adopt it, but let’s face facts: The journey to successful automation typically isn’t an easy one. Despite best-laid plans, barriers and pain points continue to plague automation programs, creating bottlenecks, stifling scale and throttling better returns.

    Given the challenges of automation — for instance, heavy maintenance burdens can eat away at ROI, and a lack of visibility on automation estates can result in redundancies and inflated costs — it is little wonder that digital twinning and its innate ability to successfully address issues is beginning to resonate.

    Tracing its origins to NASA’s space program in the 1960s, digital twinning in automation can best be defined as a digital copy of an automated process that resides in a separate repository to the robotics process automation (RPA) platform where the actual automation is developed, deployed and orchestrated.

    Advantages of digital twins

    The primary advantage of the digital twin is that it evolves as automation evolves. As a result, if any changes are applied to the automation in the RPA platform, those same changes are reflected in the twin, ideally in real-time or at least near real-time.

    Operational metrics (including runs, last time run, number of issues, utilizations, and success rates) are also accessible and displayed where the twin resides so that it can be monitored and continuously improved.

    Beyond changes and operational metrics, a digital twin in automation enables an organization to compile accurate documentation and detailed audit trails for the entire automation estate and maintain it in a single, centralized repository. Doing so not only addresses the problem of misplaced or lost process design documents, but also solves one of the major pain points of automating: An inability to visualize and understand how automations have changed over time.

    Maintaining digital twins for all automations in a central location — regardless of the RPA platform in which they are designed, deployed and orchestrated — vastly improves automation standardization, governance and visibility. Particularly for companies that employ a multi-platform automation strategy, a single repository allows for greater visibility into the complexity of all processes, as well as the systems and applications with which they interact.

    This not only vastly improves oversight of the entire automation estate, but allows for faster recognition of potential issues and redundancies and identification of automations that can be retired to lower costs and increase returns.

    Less maintenance required

    Digital twinning also reduces the need for maintenance. By serving as a canvas for automation, a digital twin can be quickly reviewed to identify where an error has occurred and how it can be corrected, saving both time and money.

    It also flips the change management process. Rather than waiting for an automation to fail before taking corrective action, digital twins enable proactive steps to be taken as soon as a potential malfunction is detected or in advance of a regulatory change or application update.

    Finally, digital twins enable accelerated and simplified RPA platform migrations because the feasibility assessments to evaluate the effort needed to switch destination platforms can be more easily performed. Because a digital version of up-to-date automation exists, exporting automation with a mapping engine that requires only minor modifications dramatically reduces the effort needed and removes manual recoding.

    Forging new partnerships

    This will prove to be particularly important in the year ahead as more organizations look to migrate from their legacy RPA platforms to next-generation intelligent automation solutions.

    Migrations will be further complicated as new partnerships are being formed among well-established solution providers using information from Internet of Things (IoT). At least three digital twin-focused industry standards groups have already emerged to assist in guiding the technology forward.

    While there can be little doubt that digital twins in automation provide a palpable source for understanding what is delivering value (and what isn’t), implementing digital twins is likely to get more complicated as parameters, design principles and even basic assumptions change.

    Some digital twins still rely on older simulations and monitoring, while others have built-in AI solutions that rely on evolving data to keep parameters up-to-date.

    All of this suggests that while their benefits will likely vary from one organization to the next, digital twins undoubtedly will see even wider use in the future. With compound annual growth rates generally projected to approach 40% annually, some analysts are already predicting 2023 as a banner year for the digital twin.

    Spurred by new developments — including the ability to proactively search for and harvest data — expect the digital twin market to grow from its current level of $6.9 billion to more than $73.5 billion by 2027. More organizations will recognize the persistent problems digital twins can address and the benefits, from increased efficiency to greater ROI that they offer.  

    Resource : https://venturebeat.com/automation/digital-twins-could-be-the-key-to-successful-automation/

    22Dec, 2022
    4 Ways AI Capabilities Transform Security

    Many industries have had to tighten belts in the “new normal”. In cybersecurity, artificial intelligence (AI) can help.

    Every day of the new normal we learn how the pandemic sped up digital transformation, as reflected in the new opportunities and new risks. For many, organizational complexity and legacy infrastructure and support processes are the leading barriers to the effectiveness of their security.

    Adding to the dynamics, short-handed teams are overwhelmed with too much data from disparate sources and an abundance of tools, yet a scarcity of insights. These challenges can easily exceed the skills of even the largest, best teams.

    In a time of greater challenges and fewer resources, how can security leaders become more effective, minimize their expenses and get the most out of their employees without burning them out? A recent study from the IBM Institute for Business Value (IBV) suggests people are investing in AI and automation to address many of these challenges.

    The IBV partnered with APQC (American Productivity and Quality Center) in a survey of 1,000 business leaders to find out how AI is being used to support their operations and to quantify its impact on performance.

    AI: Defense In a Fast-Paced World

    The in-depth report contemplates questions that are top-of-mind for today’s leaders. How do AI and automation help? Where in the security life cycle do these tools have the greatest impact? Can pairing AI with automation deliver a higher return on security investment?

    There are four primary ways AI technologies are transforming security operations:

    1. Machine learning helps identify patterns, take inventory of new assets and services and refine the performance of AI models.
    1. Reasoning tools help inform data analysis, enhance scenario modeling and foresee new attack vectors.
    1. Natural language processing can be used to mine text data sources, improve threat intelligence and enrich knowledge resources.
    1. Automation can help orchestrate time-intensive tasks, improve response times and reduce the burden for human analysts.

    According to survey respondents, adopting AI-powered automation has enabled them to operate faster, with greater flexibility.

    How are they doing this? One of the survey’s most compelling findings is that the mix of AI and automation is being used to offload routine triage tasks. It enables skilled analysts to focus on higher-value investigations that require human expertise and judgment.

    Practical Use of AI

    The report offers actionable insights into how security leaders are using AI and automation to support their protection, prevention, detection and response processes. For example:

    Source: IBM Security Services based on an analysis of aggregated 2021 performance data. Note: Performance thresholds depicted are expected to improve on a continuing basis. 

    Investing in security AI and automation is leading to tangible performance benefits. Compared to non-AI adopters, AI adopters can save more than 14 weeks in threat detection and response:

    Importantly, these organizations are achieving this level of performance while also reducing costs and complexity.

    Backed By Research

    Other IBM security research studies have found similar results. The 2022 Cost of a Data Breach report from IBM and Ponemon Institute found security AI and automation had the greatest positive impact on reducing the overall costs of a data breach. To address emerging threats, the IBM X-Force annual Threat Intelligence Index suggests best practices such as adopting a zero trust approach, automating incident response and deploying extended detection and response.

    For security leaders, the key takeaway is that investing in AI and automation enables you to make more of your skilled talent while also improving your overall performance.

    Want to dig into the data or get more insights? Read the full report here. Learn more about AI and cybersecurity here.

    Resource : https://securityintelligence.com/posts/ai-capabilities-transform-security/

    3Dec, 2022
    Raspberry Pi Has New Hi-Fi Audio Boards for Your DIY Project

    Raspberry Pi single-board computers are still wildly popular, with uses ranging from learning programming to DIY electronics. Now there’s an updated lineup of hi-fi audio cards that can turn a Pi into a better media station.

    The company behind Raspberry Pi acquired IQaudio two years ago, which was already producing four external DACs compatible with various Pi boards. The accessories allowed Pi devices to output powerful and higher-quality audio, ideal for home theater setups, music studios, or anywhere else audio quality is a priority.

    Raspberry Pi announced today that it has updated all four boards. The most noticeable change is that they all use green boards, making them “a bit more Raspberry Pi-like” compared to the older black boards. The announcement also mentioned “a few minor layout and connector changes, aimed at making the boards simpler and quicker to manufacture: this sort of continuous design‑for‑manufacturability work is the hallmark of all Raspberry Pi products.”

    The lineup consists of four boards. First is the $20 DAC+, which provides stereo analogue audio and a dedicated headphone amplifier. There’s also the $25 DAC Pro, with a better Texas Instruments chip for a higher signal-to-noise ratio, and the $30 DigiAMP+ has an integrated digital-input amplifier. Finally, the Codec Zero is a $20 board designed specifically for the Raspberry Pi Zero.

    It’s great to see Raspberry Pi invest in better audio support for projects using Pi boards, but the elephant in the room remains — the actual Pi boards themselves are still remarkably difficult to purchase. Demand for Pi boards has outstripped supply for well over a year now, with many people venting their frustration on social media. There’s even a third-party tracking site for finding restocked store listings.

    Resource : https://www.howtogeek.com/852455/raspberry-pi-has-new-hi-fi-audio-boards-for-your-diy-project/

    16Nov, 2022
    The Uncertain Future of IT Automation

    While IT automation is growing, big challenges remain. Chris Hass, director of information security and research at Automox, discusses how the future looks.

    The majority of today’s cybersecurity breaches stem from unpatched vulnerabilities and outdated systems, which means that many cyberattacks are preventable. Unfortunately, it can be challenging for IT teams to keep up with the pace of new patches every month, especially when employee devices are scattered across a distributed workforce and there’s a shortage of cybersecurity professionals. These emerging factors make efficiency a critical component for any IT team.

    To enable a rapid discovery of new exploits, more companies are turning to IT-automation tools for patching and system management. By streamlining the processes and reducing the workload, IT teams can quickly address new severe exploits and save time to focus their efforts on more high-impact projects.

    However, while the trend of automation will continue to grow, there still remain many challenges to its adoption, and new innovations or threats could change how the future looks for this technology.

    What Can We Expect in IT Automation in the Near Future?

    First and foremost, IT automation will adapt to distributed environments. When we surveyed IT professionals, 80 percent stated that the process of managing endpoints has become harder as a result of more employees working remotely. Having to both maintain management servers across multiple, distributed sites and with sporadic, inconsistent connectivity to endpoints has made it difficult for IT teams to remain efficient and nimble. This has led to more organizations looking for cloud-native solutions to remedy these challenges.

    Cloud-native technologies make connectivity with remote devices easier while staying secure without the use of VPNs. They also improve visibility into the exact, real-time status of a device. IT teams will have an easier time pushing patches automatically without worrying about VPN bandwidth restrictions. Within the next year, anticipate that more businesses will realize these immense benefits and replace existing tools with cloud-native IT automation.

    On the flip side, challenges remain, such as addressing burnout and emerging security concepts.

    IT and Security Teams’ Mental Health Comes to the Fore

    One thing that has become evident in the 2020s is that there is a lack of attention on and investment in employee mental health and safety. This is especially true when it comes to IT and security workers, who have come under enormous pressure and stress in our hybrid world today, where both outages and cyberattacks aren’t just common, but expected to happen at all times.

    Automation is one way to drive more accessibility and ease-of-use for IT teams. While in the past the core argument for automation is to provide more time for innovation, today the argument must simply be, automation creates more time for teams — but we’re not there yet.

    Consider the (relatively) recent issue with the Log4j vulnerability. The issue wasn’t “just” that there was a new vulnerability to respond to and worry about. It was that many security and IT professionals had to go through the manual task of updating every endpoint across their system, while managers and even the C-suite watched over their shoulders.

    This isn’t easy – it’s stressful, and it will make your teams more likely to quit, which is just unacceptable as we continue to navigate a world reshaped by the Great Resignation and IT skills shortage.

    New IT Security Concepts Are on the Horizon

    As Automox predicted at the end of last year, IT and security transformation continue as organizations everywhere try to find a new normal following the disruptions of the pandemic, and IT automation will have to adjust.

    This has been challenging for many organizations — and more importantly, people, as discussed above — but there are silver linings too. The pandemic has pushed new innovation across many areas, with exciting new tools and practices on the horizon for IT and security teams.

    One innovation that is particularly interesting is cybersecurity mesh architectures. Gartner has claimed that “organizations adopting a cybersecurity mesh architecture will reduce the financial impact of security incidents by an average of 90 percent” by 2024.

    A cybersecurity mesh architecture leverages various parts of the enterprise to integrate widely distributed, disparate security services. This is key to managing and accounting for a workforce that has never been more remote and globally distributed. Designing and implementing an IT security infrastructure that is not focused on a single perimeter, but instead smaller individual perimeters around each access point, provides quality-of-life improvements as well as more control over an organization’s overall security profile.

    Another trend that may seem overdue but is very much happening in real-time is the transition of ITOps and SecOps tools to cloud infrastructure. This includes firewalls, cloud access service brokers (CASBs), web gateways and other tools, as teams wind down legacy on-prem contracts and move to the cloud for more accessibility, speed and scale.

    Bottom line: IT automation is a transformational trend that is already occurring across the enterprise today, but it needs to accelerate in order to address the many pain points security and IT teams still face today.

    Resource : https://threatpost.com/uncertain-future-it-automation/178709/