
Nozomi Networks enhances critical infrastructure security amid evolving cyber threats
The cybersecurity landscape is rapidly changing, with digital technologies increasingly integrated into industrial control systems. This digital transformation has introduced new risks, especially with the rise of AI-driven cyber threats. Nozomi Networks is leading the way in securing critical infrastructure, offering solutions that ensure comprehensive protection across OT, IoT, IT, and wireless assets. In this interview, Anton Shipulin, Industrial Cybersecurity Evangelist at Nozomi Networks, discusses how the company addresses these evolving threats and helps organisations comply with stringent regulatory requirements while safeguarding critical and renewable infrastructure.
How does Nozomi secure critical infrastructure in the region amid evolving cybersecurity threats, and how does it contribute to improving operational efficiency?
Critical infrastructure is vital for a nation's cybersecurity and the functioning of the country. Essential services such as water, electricity, and oil and gas energy rely heavily on these systems, and it is crucial to ensure their continuous, uninterrupted operation. With the rapid digital transformation and the integration of advanced technologies into control systems managing critical infrastructure, these systems are increasingly dependent on digital components. However, this dependence introduces new risks.
Unauthorised access and potential cyberattacks pose significant threats to these systems, as malicious actors can exploit vulnerabilities to gain control. It is crucial to monitor these systems closely and identify any deviations from normal operations. Detecting cyberattacks, process anomalies, or other irregular behaviours at an early stage is essential for maintaining security and ensuring the longevity of these facilities.
Nozomi Networks addresses these challenges by providing real-time monitoring of network traffic, process telemetry, vulnerabilities, and asset changes within industrial control systems. This approach allows for the timely detection of anomalies and attacks, enabling prompt responses to safeguard critical infrastructure and ensure its resilience.
How can organisations achieve full-spectrum protection across OT, IoT, IT, and wireless assets, and what solutions does Nozomi offer to address these complex security challenges?
Our primary focus is on securing industrial control systems and cyber-physical systems, including the Internet of Things (IoT). When it comes to industrial control systems, they often comprise a variety of components, including pure OT elements like controllers and PLCs, as well as IT components such as network devices, routers, switches, PCs, laptops, and servers running traditional operating systems like Windows.
It is critical not to focus solely on protecting OT systems. Rather, organisations must ensure protection across all components surrounding these critical systems. To address this, our solution expands beyond just supporting OT protocols. While we excel in supporting OT protocols with deep packet inspection for anomaly detection and attack identification, we also support IT systems and the most common IT protocols like DNS, SNMP, and others. This is achieved through passive network monitoring, which ensures visibility across both OT and IT environments.
For enhanced asset visibility and discovery, we've added active discovery components, including smart polling, which queries devices for details. Additionally, we've expanded our solutions to incorporate various types of sensors, including network sensors and recently, endpoint sensors. These endpoint sensors can be deployed on systems such as Windows, Linux, and MacOS, especially in areas where network sensors cannot be installed.
Furthermore, with the increasing adoption of wireless networks in industrial environments, it is essential to monitor and protect these networks to prevent unauthorised access. In some cases, clients may prohibit wireless networks entirely. However, even in such scenarios, monitoring wireless communications remains vital to detect unauthorised devices, such as rogue wireless access points or USB dongles, that could pose a security risk.
Overall, Nozomi offers a comprehensive solution that ensures protection across wireless networks, wired networks, and endpoints, providing organisations with full-spectrum security across their OT, IoT, IT, and wireless assets.
With the rise of AI-driven cyber threats, how do you see the threat landscape evolving, and what steps is Nozomi taking to stay ahead of these emerging risks?
The rise of AI technologies is both a beneficial and accelerating force for cybersecurity, but unfortunately, it is also being exploited by cybercriminals to enhance their attacks. Attackers leverage AI for tasks such as vulnerability scanning, spam generation, and even coding attacks. This makes it easier for them to create new and more sophisticated attacks, accelerating the pace of the threat landscape.
For organisations, this presents a significant challenge, as AI-driven threats allow attackers to quickly evolve their methods, making it critical for asset owners to detect these attacks in a timely and precise manner. This is where Nozomi Networks focuses its efforts. Our solution is not only designed for network detection but also for understanding industrial and IoT protocols, which is crucial in accurately identifying attacks.
As the frequency and complexity of attacks grow, the amount of data that needs to be processed increases exponentially, making it harder to correlate and analyse all the relevant information. To address this challenge, we integrate AI and machine learning into our platform for alert correlation and generating insights. These technologies help us manage and analyse vast amounts of data, allowing us to detect threats more effectively.
Moreover, as more industrial automation vendors and cloud providers implement AI-based systems, it is essential to protect these components from potential threats. AI-based systems themselves are now vulnerable, and our focus includes monitoring attempts to attack these systems, ensuring that they are adequately safeguarded.
Nozomi is adapting to the evolving threat landscape by incorporating AI and machine learning for better threat detection and data processing, while also expanding our focus to protect AI-based systems in industrial automation and cloud environments.
Could you share insights into Nozomi's complete cyber-physical protection offerings, particularly in securing critical and renewable infrastructure? How do your solutions enable compliance in highly regulated sectors?
Nozomi's solution focuses on comprehensive monitoring across a wide range of environments, including wireless networks, endpoint activities, and IoT systems. Our offerings include a diverse set of sensors for network, wireless, and endpoint monitoring, alongside management components for on-premises environments and cloud-based components for information collection and analysis.
By providing real-time visibility and continuous monitoring, our solutions ensure that critical infrastructure, including renewable energy systems, is secured against potential cyber threats. Furthermore, our solutions help organisations meet the compliance requirements of highly regulated sectors by ensuring that all systems are continuously monitored, vulnerabilities are detected early, and appropriate actions are taken to mitigate risks in real time.
How does Nozomi ensure compliance with highly regulated sectors, especially considering the growing number of cybersecurity frameworks and regulations globally?
Compliance with cybersecurity regulations is increasingly important, with various frameworks emerging across the globe, such as those in Europe, the United States (e.g., New York City's cybersecurity regulations), and other regions. One of the key elements of compliance is ensuring proper asset discovery, asset management, threat detection, and vulnerability management.
To help organisations meet these regulatory requirements, Nozomi offers comprehensive solutions that focus on asset discovery, threat detection, and vulnerability identification. By addressing these key components, our solutions ensure the security of critical networks and data, enabling organisations to comply with regulations while also enhancing their overall cybersecurity posture.
Image Credit: Nozomi Networks
Hashtags

Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles


Khaleej Times
14 hours ago
- Khaleej Times
Artificial Intelligence in cybersecurity: savior or saboteur?
Artificial intelligence has rapidly emerged as both a cornerstone of innovation and a ticking time bomb in the realm of cybersecurity. Once viewed predominantly as a force for good, enabling smarter threat detection, automating incident responses, and predicting attacks before they happen — AI has now taken on a double-edged role. The very capabilities that make it invaluable to cybersecurity professionals are now being exploited by cybercriminals to launch faster, more convincing, and more damaging attacks. From phishing emails indistinguishable from real business correspondence to deepfake videos that impersonate CEOs and public figures with chilling accuracy, AI is arming attackers with tools that were previously the stuff of science fiction. And as large language models (LLMs), generative AI, and deep learning evolve, the tactics used by bad actors are becoming more scalable, precise, and difficult to detect. 'The threat landscape is fundamentally shifting,' says Sergey Lozhkin, Head of the Global Research & Analysis Team for the Middle East, Türkiye, and Africa at Kaspersky. 'From the outset, cybercriminals began using large language models to craft highly convincing phishing emails. Poor grammar and awkward phrasing — once dead giveaways are disappearing. Today's scams can perfectly mimic tone, structure, and professional language.' But the misuse doesn't stop at email. Attackers are now using AI to create fake websites, generate deceptive images, and even produce deepfake audio and video to impersonate trusted figures. In some cases, these tactics have tricked victims into transferring large sums of money or divulging sensitive data. According to Roland Daccache, Senior Manager – Sales Engineering at CrowdStrike MEA, AI is now being used across the entire attack chain. 'Generative models are fueling more convincing phishing lures, deepfake-based social engineering, and faster malware creation. For example, DPRK-nexus adversary Famous Chollima used genAI to create fake LinkedIn profiles and résumé content to infiltrate organisations as IT workers. In another case, attackers used AI-generated voice and video deepfakes to impersonate executives for high-value business email compromise (BEC) schemes.' The cybercrime community is also openly discussing how to weaponize LLMs for writing exploits, shell commands, and malware scripts on dark web forums, further lowering the barrier of entry for would-be hackers. This democratisation of hacking tools means that even novice cybercriminals can now orchestrate sophisticated attacks with minimal effort. Ronghui Gu, Co-Founder of CertiK, a leading blockchain cybersecurity firm, highlights how AI is empowering attackers to scale and personalize their strategies. 'AI-generated phishing that mirrors human tone, deepfake technology for social engineering, and adaptive tools that bypass detection are allowing even low-skill threat actors to act with precision. For advanced groups, AI brings greater automation and effectiveness.' On the technical front, Janne Hirvimies, Chief Technology Officer of QuantumGate, notes a growing use of AI in reconnaissance and brute-force tactics. 'Threat actors use AI to automate phishing, conduct rapid data scraping, and craft malware that adapts in real time. Techniques like reinforcement learning are being explored for lateral movement and exploit optimisation, making attacks faster and more adaptive.' Fortifying Cyber Defenses To outsmart AI-enabled attackers, enterprises must embed AI not just as a support mechanism, but as a central system in their cybersecurity strategy. 'AI has been a core part of our operations for over two decades,' says Lozhkin. 'Without it, security operations center (SOC) analysts can be overwhelmed by alert fatigue and miss critical threats.' Kaspersky's approach focuses on AI-powered alert triage and prioritisation through advanced machine learning, which filters noise and surfaces the most pressing threats. 'It's not just about automation — it's about augmentation,' Lozhkin explains. 'Our AI Technology Research Centre ensures we pair this power with human oversight. That combination of cutting-edge analytics and skilled professionals enables us to detect over 450,000 malicious objects every day.' But the AI evolution doesn't stop at smarter alerts. According to Daccache, the next frontier is agentic AI — a system that can autonomously detect, analyze, and respond to threats in real time. 'Traditional automation tools can only go so far,' Daccache says. 'What's needed is AI that thinks and acts — what we call agentic capabilities. This transforms AI from a passive observer into a frontline responder.' CrowdStrike's Charlotte AI, integrated within its Falcon platform, embodies this vision. It understands security telemetry in context, prioritises critical incidents, and initiates immediate countermeasures, reducing analyst workload and eliminating delays during high-stakes incidents. 'That's what gives defenders the speed and consistency needed to combat fast-moving, AI-enabled threats,' Daccache adds. Gu believes AI's strength lies in its ability to analyze massive volumes of data and identify nuanced threat patterns that traditional tools overlook. 'AI-powered threat detection doesn't replace human decision-making — it amplifies it,' Gu explains. 'With intelligent triage and dynamic anomaly detection, AI reduces response time and makes threat detection more proactive.' He also stresses the importance of training AI models on real-world, diverse datasets to ensure adaptability. 'The threat landscape is not static. Your AI defenses shouldn't be either,' Gu adds. At the core of any robust AI integration strategy lies data — lots of it. Hirvimies advocates for deploying machine learning models across SIEM (Security Information and Event Management) and SOAR (Security Orchestration, Automation, and Response) platforms. 'These systems can correlate real-time threat intelligence, behavioral anomalies, and system events to deliver faster, more precise responses,' he says. 'Especially when it comes to detecting novel or stealthy attack patterns, machine learning makes the difference between catching a threat and becoming a headline.' Balancing Innovation with Integrity While AI can supercharge threat detection, response times, and threat simulations, it also brings with it the potential for misuse, collateral damage, and the erosion of privacy. 'Ethical AI use demands transparency, clear boundaries, and responsible data handling,' says Lozhkin.'Organisations must also ensure that employees are properly trained in the safe use of AI tools to avoid misuse or unintended exposure to threats.' He highlights Kaspersky's Automated Security Awareness Platform, which now includes dedicated sections on AI-assisted threats and responsible usage, reflecting the company's commitment to proactive education. When AI is deployed in red teaming or simulated cyberattacks, the risk matrix expands. Gu warns that AI systems, if left unchecked, can make decisions devoid of human context, potentially leading to unintended and widespread consequences. 'Ethical AI governance, robust testing environments, and clearly defined boundaries are essential,' he says, underlining the delicate balance required to simulate threats without crossing into unethical territory. Daccache emphasises the importance of a privacy-first, security-first approach. 'AI must be developed and operated with Privacy-by-Design and Secure-by-Design principles,' he explains. 'This extends to protecting the AI systems themselves — including their training data, operational logic, and outputs—from adversarial manipulation.' Daccache also points to the need for securing both AI-generated queries and outputs, especially in sensitive operations like red teaming. Without such safeguards, there's a real danger of data leakage or misuse. 'Transparency, accountability, and documentation of AI's capabilities and limitations are vital, not just to build trust, but to meet regulatory and ethical standards,' he adds. Despite AI's growing autonomy, human oversight remains non-negotiable. 'While AI can accelerate simulations and threat detection, it must be guided by skilled professionals who can interpret its actions with context and responsibility,' says Daccache. This human-AI collaboration ensures that the tools remain aligned with organisational values and ethical norms. Hirvimies rounds out the conversation with additional cautionary notes: 'Privacy violations, data misuse, bias in training datasets, and the misuse of offensive tools are pressing concerns. Transparent governance and strict ethical guidelines aren't optional, they're essential.' Balancing the Equation While AI promises speed, scale, and smarter defense mechanisms, experts caution that an over-reliance on these systems, especially when deployed without proper calibration and oversight — could expose organisations to new forms of risk. 'Absolutely, over-reliance on AI can backfire if systems are not properly calibrated or monitored,' says Lozhkin. 'Adversarial attacks where threat actors feed manipulated data to mislead AI are a growing concern. Additionally, AI can generate false positives, which can overwhelm security teams and lead to alert fatigue. To avoid this, companies should use a layered defence strategy, retrain models frequently, and maintain human oversight to validate AI-driven alerts and decisions.' This warning resonates across the cybersecurity landscape. Daccache echoes the concern, emphasising the need for transparency and control. 'Over-relying on AI, especially when treated as a black box, carries real risks. Adversaries are already targeting AI systems — from poisoning training data to crafting inputs that exploit model blind spots,' he explains. 'Without the right guardrails, AI can produce false positives or inconsistent decisions that erode trust and delay response.' Daccache stresses that AI must remain a tool that complements — not replaces—human decision-making. 'AI should be an extension of human judgement. That requires transparency, control, and context at every layer of deployment. High-quality data is essential, but so is ensuring outcomes are explainable, repeatable and operationally sound,' he says. 'Organisations should adopt AI systems that accelerate outcomes and are verifiable, auditable and secure by design.' Gu adds that blind spots in AI models can lead to serious lapses. 'AI systems are not infallible,' he says. 'Over-reliance can lead to susceptibility to adversarial inputs or overwhelming volumes of false positives that strain human analysts. To mitigate this, organizations should adopt a human-in-the-loop approach, combine AI insights with contextual human judgment, and routinely stress-test models against adversarial tactics.' Gu also warns about the evolving tactics of bad actors. 'An AI provider might block certain prompts to prevent misuse, but attackers are constantly finding clever ways to circumvent these restrictions. This makes human intervention all the more important in companies' mitigation strategies.' Governing the Double-Edged Sword As AI continues to embed itself deeper into global digital infrastructure, the question of governance looms large: will we soon see regulations or international frameworks guiding how AI is used in both cyber defense and offense? Lozhkin underscores the urgency of proactive regulation. 'Yes, there should definitely be an international framework. AI technologies offer incredible efficiency and progress, but like any innovation, they carry their fair share of risks,' he says. 'At Kaspersky, we believe new technologies should be embraced, not feared. The key is to fully understand their threats and build strong, proactive security solutions that address those risks while enabling safe and responsible innovation.' For Daccache, the focus is not just on speculative regulation, but on instilling foundational principles in AI systems from the start. 'As AI becomes more embedded in cybersecurity and digital infrastructure, questions around governance, risk, and accountability are drawing increased attention,' he explains. 'Frameworks like the GDPR already mandate technology-neutral protections, meaning what matters most is how organizations manage risk not whether AI is used.' Daccache emphasises that embedding Privacy-by-Design and Secure-by-Design into AI development is paramount. 'To support this approach, CrowdStrike offers AI Red Teaming Services, helping organisations proactively test and secure their AI systems against misuse and adversarial threats. It's one example of how we're enabling customers to adopt AI with confidence and a security-first mindset.' On the other hand, Gu highlights how AI is not only transforming defensive mechanisms but is also fuelling new forms of offensive capabilities. 'As AI becomes integral to both defence and offense in cyberspace, regulatory frameworks will be necessary to establish norms, ensure transparency, and prevent misuse. We expect to see both national guidelines and international cooperation similar to existing cybercrime treaties emerge to govern AI applications, particularly in areas involving privacy, surveillance, and offensive capabilities.' Echoing this sentiment, Hirvimies concludes by saying that developments are already underway. 'Yes. Regulations like the EU AI Act and global cyber norms are evolving to address dual-use AI,' he says. 'We can expect more international frameworks focused on responsible AI use in cyber defence, limits on offensive AI capabilities, and cross-border incident response cooperation. At QuantumGate, we've designed our products to support this shift and facilitate compliance with the country's cryptography regulations.'


Zawya
a day ago
- Zawya
The missed opportunity of not embracing geospatial science in trade area analysis
In the information-rich age we live in, answers to location-based questions have never been more available – and crucial – to a business's success. Yet, many of South Africa's franchises and retailers continue to rely on gut feel or high-level aggregated sales data to guide their decisions on where to open stores and how to optimise their networks. Unfortunately, this approach often leads to lost sales, costly real estate mistakes, and missed opportunities for growth, writes Rochelle Mountany, CEO of AfriGIS. The need for geospatial analysis in trade area decisions is clearer than ever. It's not just about where your next physical location should be – it's about understanding how each potential site fits into a broader network of customer behaviours, traffic patterns, and market dynamics. The problem is, many businesses still overlook geospatial science as a key component of their growth and development strategy. By failing to leverage this tool, they're missing a massive opportunity to optimise their operations and customer experience. Look no further than South Africa's shifting retail landscape. Dozens of stores across the country have recently closed. These closures often stem from a combination of factors, including safety issues and inconsistent municipal services. Frequent load shedding, poor road maintenance, and surging crime rates are making certain neighbourhoods unviable for stores that rely on stability and consistent customer flow. In addition to these environmental challenges, strategic missteps such as failing to correctly identify the customer segment a store is intended to serve have also contributed to closures. These misjudgements highlight the critical importance of understanding not just where customers are today, but where they will be in the future, and how their behaviours and preferences are shaped by their surroundings. Why geospatial analysis matters Trade area analysis is more than just about finding a good location for a new store. It applies to any service-based organisation, whether it's a retail chain, a fast food outlet, or a government department. In fact, public services like health clinics face similar challenges to retail networks when it comes to site planning. For instance, the South African government mandates that health clinics be located within a certain travel radius for underserved communities. Yet, often these clinics are located without any real data-backed understanding of future growth patterns, leading to inefficiencies and gaps in service. In retail, this issue manifests when businesses make location decisions based on outdated assumptions or once-off studies. Planning a store or service location based on static data means you're reacting to the current environment, not anticipating the market's evolution. This is where geospatial science offers real value – through predictive insights that allow businesses to not just react, but anticipate where future opportunities will emerge. The predictive power of geospatial science At the core of effective trade area analysis is the ability to model, forecast, and predict future trends. Without integrating geospatial data, businesses are essentially guessing about where future growth will occur. In the retail world, this means failing to plan for shifts in demographics, consumer behaviour, or commercial development in areas that may seem underserved today but will see population or income growth in the coming years. Geospatial science goes beyond static location analysis. It takes into account factors like local property trends, housing development, consumer behaviour, and competitor movements to create dynamic, adaptable models. By overlaying these data points on a map, businesses can identify high-potential locations that align with their strategic goals. This predictive ability can make the difference between opening a store in a saturated area or identifying an emerging market that could yield higher returns over time. A systematic, live system for smarter decision-making The problem with traditional trade area analysis is that it is often treated as a one-off study – conducted for a few months, analysed, and then shelved for years. In contrast, geospatial science, the likes of which is offered by AfriGIS, provides a systematic, live approach to location planning. With a geospatial analysis platform, businesses can continuously monitor and recalibrate their network strategies, ensuring that their decisions are always based on up-to-date data. This kind of approach doesn't just offer efficiency – it's a game changer for resource allocation. For example, if a flagship store isn't performing as expected, businesses can pivot. By understanding the real-time data through a geospatial lens, companies can reposition resources, potentially converting a flagship store into a mid-tier location and identifying the right place for a true flagship site. By making geospatial analysis a part of your ongoing strategy, businesses can make constant course corrections, rather than waiting five years to realise their initial assumptions were flawed. This proactive, data-driven approach helps ensure that your capital expenditures are allocated where they'll yield the best results. The cost of missing the geospatial edge When it comes to large-scale expansions – whether it's opening hundreds or thousands of new stores – geospatial science is no longer optional. It's an essential tool for ensuring that businesses make the right location decisions. Without accurate, predictive modelling, the investment required to roll out new stores or facilities becomes a huge gamble. A business that attempts to plan for such growth with spreadsheets or basic market research is setting itself up for failure. Geospatial science offers a level of insight and precision that cannot be achieved through traditional methods. It incorporates real-time data, predictive models, and customer behaviour patterns to provide a comprehensive, dynamic view of the market landscape. This is a massive competitive advantage, especially in sectors like retail and services, where location is everything. A more efficient, cost-effective way forward While implementing geospatial analysis may initially seem like a costly or complex undertaking, the truth is that it offers an incredibly cost-effective solution in the long run. At AfriGIS, we've designed geospatial platforms that allow businesses to tap into rich, updated datasets without needing to invest in specialised in-house teams of geospatial scientists. By sourcing, cleaning, and spatially enabling datasets, we give businesses the tools they need to make smarter, data-driven decisions without the need for ongoing, expensive consultancy studies. What's more, this data is continuously updated, ensuring businesses always have the latest insights at their fingertips. With a platform that integrates both current data and predictive models, businesses can confidently plan for future growth and adapt to changing market conditions without the need for costly, periodic studies. In an age where location-based decisions are critical to growth, businesses that fail to adopt geospatial science are leaving money on the table. Whether you're planning the next retail store, healthcare facility, or public service delivery point, ignoring geospatial analysis is a huge missed opportunity. The ability to predict, analyse, and continually adapt your strategy based on dynamic geospatial data isn't just a nice-to-have – it's a competitive necessity. By adopting a live, ongoing system for trade area analysis, businesses can make informed, future-proof decisions that drive growth, optimise resources, and reduce costly real estate mistakes. For companies looking to stay ahead of the curve, the time to integrate geospatial science into your planning is now.

Zawya
2 days ago
- Zawya
Ukraine and Ghana Agreed to Develop Cooperation in Cybersecurity, Digitalization, and Information Technologies
Deputy Foreign Minister of Ukraine, Chief Digital Transformation Officer, Anton Demokhin held an online meeting with the Minister for Communication, Information Technology, and Innovation of the Republic of Ghana, Samuel Nartey George. During the meeting, both parties reaffirmed their mutual interest in expanding areas of bilateral cooperation between Ukraine and Ghana and outlined priority areas for collaboration in digitalization, digital transformation, innovation, cybersecurity, and combating cybercrime. The parties agreed to work in detail on relevant cooperation tracks between our countries, involving the respective government agencies. "The growing dynamic of Ukrainian-Ghanaian dialogue at the highest political level, as well as between our foreign ministers, clearly demonstrates the mutual interest of Ukraine and Ghana in developing broad bilateral cooperation. We commend Ghana's Digital Agenda as a timely step towards the global digital economy and believe that Ukrainian experience would support the initiatives on agenda", - emphasized the Deputy Foreign Minister of Ukraine. Anton Demokhin informed the Minister for Communications, Information Technology, and Innovation of the Republic of Ghana about Ukraine's experience in digitalization and digital transformation, innovation development, and the strengthening of cyber capabilities. Samuel Nartey George expressed Ghana's interest in learning from Ukraine's cybersecurity experience as well as in applying artificial intelligence technologies in public administration, establishing the institution of Chief Digital Transformation Officers (CDTOs), and improving digital literacy among the population. The Deputy Minister of Foreign Affairs of Ukraine also spoke about initiatives aimed at showcasing the potential of Ukraine's IT market and facilitating business connections with leading Ukrainian tech companies, including the Code-UA platform. Anton Demokhin emphasized the strong interest of Ukrainian IT companies in developing mutually beneficial cooperation with both the private and public sectors in Ghana. In this context, both sides agreed on the advisability of organizing a joint Ukrainian-Ghanaian IT Forum. During the meeting, the Deputy Minister of Foreign Affairs of Ukraine thanked his counterpart for Ghana's principled position and participation in international efforts aimed at achieving a just and sustainable peace in Ukraine. The negotiations continued the bilateral dialogue initiated on the sidelines of the Second Global Conference on Cyber Capacity Building, held on May 13–14 in Geneva. Representatives of the Ministry of Digital Transformation of Ukraine and the State Service of Special Communications and Information Protection of Ukraine also participated in the meeting. Distributed by APO Group on behalf of Ministry of Foreign Affairs of Ukraine.