
Redington powers MXDR Growth with Microsoft at GISEC Global
Redington, a leading technology aggregator and innovation powerhouse across emerging markets, recently announced the expansion of its Managed Extended Detection and Response (MXDR) Solution based on Microsoft Sentinel and Defender, supported through its robust partner network at GISEC Global 2025.
This milestone enables Redington and its partners to help customers address evolving security challenges with comprehensive, ready-to-deploy managed services.
With the full solution stack now live on the Azure Marketplace, Redington is actively onboarding customers through its channel ecosystem. The offering is delivered via DigiGlass, Redington's managed security services practice and now brings advanced Azure Sentinel-based solutions to market.
Redington's expanded MXDR capabilities open new opportunities for partners, especially those without their own Security Operations Center (SOC) practices, to deliver managed security services seamlessly to their customers. Through this model, partners can leverage Redington's expertise and DigiGlass capabilities to offer end-to-end security coverage — giving customers peace of mind and allowing them to focus on innovation and growth.
'The expansion of our MXDR solution, built on Microsoft Sentinel and Defender, marks a significant milestone in Redington's mission to democratise advanced cybersecurity across the region', said Nehal Sharma, Vice President, Cloud Solutions Group, Redington. 'With our solution stack now live on the Azure Marketplace, we're enabling our partners — particularly those without in-house SOC capabilities — to deliver powerful, end-to-end managed security services to their customers. This is about empowering businesses to navigate today's complex threat landscape with confidence, so they can focus on driving innovation and growth'.
As part of this launch, Redington will showcase its expanded MXDR offering at GISEC Global 2025, alongside key Microsoft partners including noventiq, Exquitech, and IDC Technologies.
Visitors can explore Redington's booth in Hall 4, Stand J10 to see live demos, learn more about the solutions, and engage with the Redington and DigiGlass teams.
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Khaleej Times
a day 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
2 days ago
- Zawya
A comprehensive guide to high-utility crypto picks: Inside the 5 best tokens to buy in 2025
Heading deeper into 2025, blockchain is more focused on utility. The most promising tokens are those delivering practical solutions, driving adoption through real-world applications rather than marketing buzz. This shift highlights projects that build essential infrastructure, facilitate seamless transactions, and enable decentralized services across various sectors, such as Qubetics' cross-border payments. Contents1. Qubetics: The Cross-Border Payments Pioneer Among the Best Tokens to Buy in 2025Latest Project Information: The Qubetics Crypto PresaleProjected Growth: A $5,000 Scenario2. Polygon: Ethereum's Fast Lane3. Stellar: The Infrastructure for Emerging Markets4. Tron: Redefining Digital Content and Smart Contracts5. Filecoin: The Web3 Data BackboneFinal Words: High-Utility Best Tokens to Buy in 2025For More Information:FAQs1. What makes a crypto token 'high-utility'?2. Is Qubetics focused only on finance?3. How is Filecoin different from traditional cloud storage?4. Can Polygon fully replace Ethereum?5. Are crypto presales safe? This guide examines five standout tokens that combine high utility and strong growth potential. Besides Qubetics, there's Polygon, a leading scalability solution enhancing Ethereum's capabilities; Stellar, dedicated to expanding financial access in emerging markets; Tron, focused on decentralized content distribution and DeFi; and Filecoin, a pioneer in decentralized data storage. Each token plays a distinct role in the blockchain ecosystem and offers unique advantages for developers, enterprises, and users. By exploring these projects, this guide identifies the five best tokens to buy in 2025 based on their real-world value propositions and readiness for mass adoption. 1. Qubetics: The Cross-Border Payments Pioneer Among the Best Tokens to Buy in 2025 One of the most promising use cases for blockchain lies in global payments. Qubetics tackles this challenge with precision. At its core, the TICS token powers near-instant cross-border payments. By bypassing the outdated financial rails of correspondent banking, Qubetics delivers secure, real-time transfers that cost a fraction of traditional fees. Qubetics' architecture was built with banks and regulated financial institutions in mind. Its compliance-first approach ensures frictionless deployment across multiple jurisdictions. For these institutions, Qubetics offers improved settlement speed, reduced costs, and a significant enhancement in customer satisfaction. The platform's hybrid ledger structure supports fast transaction throughput while maintaining robust audit trails. Latest Project Information: The Qubetics Crypto Presale Currently in Stage 36 of its presale, the project has set the price per token at $0.3064. The presale phase has generated significant interest, raising over $17.5 million in funds to date. This strong backing is reflected in the growing community, which now boasts more than 27,200 token holders. So far, a substantial 514 million $TICS tokens have been sold, highlighting both buyer confidence and the momentum behind the project as it moves closer to its next milestones. Projected Growth: A $5,000 Scenario At the current price of $0.3064, a $5,000 purchase yields approximately 16,319 $TICS tokens. Should $TICS reach: $1: Portfolio value becomes $16,319 (226% ROI)$5: Portfolio value becomes $81,595 (1,531% ROI)$6: Portfolio value becomes $97,914 (1,857% ROI)$10: Portfolio value becomes $163,190 (3,163% ROI)$15: Portfolio value becomes $244,785 (4,794% ROI) These projections are based on internal growth models and third-party analyst forecasts. As always, results depend on market conditions. Why this crypto makes it to this list: Qubetics earns its place on this list by delivering a highly scalable and compliant solution to a critical global challenge—cross-border payments. Its innovative technology enables near-instant, low-cost transactions that bypass traditional banking inefficiencies, making it an essential tool for financial institutions seeking faster, more secure, and cost-effective payment methods. 2. Polygon: Ethereum's Fast Lane Ethereum's scalability bottleneck has long limited its growth. Polygon solves this with a Layer-2 framework that drastically improves speed and reduces gas fees. The network's Plasma Chains, zk-rollups, and PoS sidechains enable seamless scaling while remaining compatible with Ethereum's base layer. Polygon supports thousands of dApps and DeFi platforms, giving developers the performance headroom to build enterprise-grade products. With an average block confirmation time of 2.3 seconds and transaction costs below $0.01, it outpaces most networks in efficiency. Why this crypto makes it to this list: Polygon enhances Ethereum's ecosystem without competing against it. It offers immediate utility for developers and end users alike—a solid bet among the best tokens to buy in 2025. 3. Stellar: The Infrastructure for Emerging Markets Stellar's mission focuses on financial inclusion. By providing a platform for fast, low-cost international remittances, Stellar empowers underserved populations. Its consensus mechanism, the Stellar Consensus Protocol (SCP), supports rapid transaction finality and energy-efficient operations. Stellar's asset issuance model allows anyone to create, send, and trade digital representations of fiat currencies or commodities. The protocol supports KYC/AML compliance, making it attractive for regulated entities. Stellar has been used for cross-border payment corridors in Africa, Southeast Asia, and Latin America. Why this crypto makes it to this list: Stellar offers real-world financial infrastructure, particularly valuable in regions where legacy systems fall short. 4. Tron: Redefining Digital Content and Smart Contracts Tron was designed for decentralized content distribution. With over 180 million user accounts and billions of daily transactions, it's one of the most actively used blockchains. Its delegated Proof-of-Stake consensus ensures high throughput and minimal fees. The Tron Virtual Machine (TVM) allows easy migration for Ethereum-based projects. Tron also powers a vibrant DeFi ecosystem, supporting stablecoins, lending, and NFTs. Its integration with BitTorrent further extends its utility to decentralized file sharing and media. Why this crypto makes it to this list: Tron combines scalability, developer tools, and real-world applications in digital media and finance, making it one of the best tokens to buy in 2025. 5. Filecoin: The Web3 Data Backbone Filecoin addresses decentralized storage, a growing necessity as Web3 applications expand. It transforms unused storage capacity into a global, open market where users pay for data hosting and retrieval using FIL tokens. Its proof-of-replication and proof-of-spacetime consensus models ensure data integrity and availability. Filecoin is already integrated with multiple Layer-1s and used in sectors like research, archiving, and media. It has become the go-to solution among the best tokens to buy in 2025 for trustless, persistent, and cost-efficient file storage. Why this crypto makes it to this list: Filecoin offers a decentralized alternative to cloud storage, critical for the growth of Web3 applications. Final Words: High-Utility Best Tokens to Buy in 2025 These five tokens—Qubetics, Polygon, Stellar, Tron, and Filecoin—demonstrate the evolving priorities of the crypto universe. Each addresses a specific, large-scale challenge and delivers measurable solutions. As crypto adoption grows, high-utility tokens will become the foundation of long-term value creation. While all markets involve risk, the projects discussed here are backed by functioning technologies, strategic partnerships, and demonstrable use cases. For developers, analysts, and crypto enthusiasts, these represent five of the best tokens to buy in 2025, especially Qubetics' crypto presale, which smart buyers are joining early for 1000X growth potential (as highlighted by analyst predictions). This article is for informational purposes only and doesn't constitute financial advice. Readers should conduct their own research before making any investment decisions. For More Information: Qubetics: Presale: Telegram: Twitter: FAQs1. What makes a crypto token 'high-utility'? A high-utility token serves a specific function within a platform, solving real-world problems like payments, scalability, or data storage. The best tokens to buy in 2025 are usually high-utility projects. 2. Is Qubetics focused only on finance? While primarily geared toward cross-border payments, Qubetics is expanding into other enterprise-grade applications as well, like QubeQode and a multi-chain wallet. 3. How is Filecoin different from traditional cloud storage? Filecoin is decentralized, meaning it avoids single points of failure and creates a competitive, open market for data storage. 4. Can Polygon fully replace Ethereum? No, Polygon is designed to scale Ethereum, not replace it. It improves usability and performance without compromising compatibility. 5. Are crypto presales safe? Crypto presales carry risks like any early-stage project. It's essential to verify tokenomics, team credentials, and regulatory compliance. Alt Text: 6 types of boxer pants for men — good for your health and comfort Copyright © 2022 Nigerian Tribune Provided by SyndiGate Media Inc. (

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.