2024資訊安全趨勢

科技的快速進步和演化為社會帶來了許多好處,但同時也帶來了更複雜的網路威脅。除了2023年人工智慧(AI)技術的迅速崛起及其帶來的風險外,許多權威組織、專家和學者也對2024年的資安趨勢進行了其他預測。

首先,生成式AI仍然會因駭客的惡意使用而帶來更多的資安風險。隨著生成式AI的應用擴大,駭客可能通過讓機器學習錯誤的資料,入侵模型的資料儲存或流程架構,從而導致自然語言模型洩漏機密資料或使系統受到汙染而無法正常運作。這種情況被稱為「資料下毒」。此外,生成式AI還提高了詐騙能力,例如變種詐騙和網絡釣魚。未來,駭客有可能結合不同的AI工具,以更逼真的方式進行勒索活動。

其次,預計供應鏈攻擊也會增加,其中一種名為供應鏈連鎖攻擊的攻擊方式成為駭客的主要手段之一。該攻擊方式是駭客首先獲取其中一個系統的存取權,然後利用該權限侵入與之相連接的其他系統。這種攻擊方式可以有效地避開堅固的防禦,利用互相連接、受信任但相對脆弱的目標中的漏洞,從而滲透到安全性更高的系統中。

此外,生成式AI的普及還將導致雲端網路成為新的攻擊目標。由於運行這些模型的成本急劇上升,甚至達到數千萬美元。因此,駭客開始將目標轉向雲端,他們在雲端建立算力農場,以籌集資金來支持他們的行動。與數年前以加密挖礦為主要目標不同,未來雲端算力農場可能成為攻擊的焦點。此外,根據預測,雲端原生蠕蟲攻擊也可能大規模出現,駭客可以通過感染的雲端技術作為跳板,將感染擴散到其他地方。蠕蟲可以一次感染多個容器並進行大規模攻擊漏洞,實現偵查、攻擊和常駐等全部自動化。

最後,私有區塊鏈也將成為駭客的攻擊目標。與公有區塊鏈不同,私有區塊鏈採用集中化的設計,並且不會經常在攻擊中不斷強化。未來,駭客可能針對這類區塊鏈開發基於勒索的全新商業模式。在這些勒索行動中,駭客可能使用竊取的金鑰故意在區塊鏈上插入惡意資料或篡改現有的交易記錄,然後向受害者勒索贖金作為封口費用。

總結來說,2024年的資訊安全環境持續面臨著各種威脅與挑戰。我們需要關注人工智慧技術的應用與相應的風險,加強對雲端環境的保護並普及多重驗證機制。教育用戶建立防範意識以應對釣魚和勒索軟體攻擊。同時,區塊鏈技術的應用可以提供更安全的驗證方式。企業需要投資人才培訓並建立良好的資訊安全文化。我們也應該提高資訊安全意識,持續關注技術發展與相應風險,以確保我們的數字生活安全。

 

尹展軒

Senior IT Consultant

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Further reading

𝗘𝗺𝗯𝗿𝗮𝗰𝗶𝗻𝗴 𝗔𝗜 𝗳𝗼𝗿 𝗮 𝗙𝘂𝘁𝘂𝗿𝗲-𝗥𝗲𝗮𝗱𝘆 𝗪𝗼𝗿𝗸𝗽𝗹𝗮𝗰𝗲

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Secure, Reliable, High-performing digital systems

At Ringus Solution Enterprise Limited, we know that in today’s digital-first world, two things matter more than ever: security and performance. That’s why our Technical Services Team focuses on helping businesses protect their systems from cyber threats and ensure their applications run smoothly under all conditions.Security breaches can be devastating—leading to data loss, reputational damage, and costly downtime. Our Technical Services Team specializes in technical security assessments that help businesses stay one step ahead of potential threats. We don’t just run automated scans and call it a day. Instead, we take a comprehensive approach that includes in-depth vulnerability assessments, hands-on penetration testing, and detailed security configuration reviews. Our goal is to uncover vulnerabilities before malicious actors do, and to provide clear, actionable recommendations to strengthen your system's defenses.We also understand that a secure system must also be a high-performing one. That’s why we provide application performance testing as a core part of our services. Whether you're launching a new platform or scaling an existing one, we help ensure your application can handle the pressure. Our team conducts rigorous load and stress testing to simulate real-world usage, analyzes response times and throughput, and identifies bottlenecks that could slow down your users. We also assess scalability—so your systems grow as your business grows.What sets our team apart is our commitment to delivering not just technical reports, but real solutions. We translate complex findings into practical recommendations, empowering your business to take action quickly and confidently. With a team of experienced cybersecurity specialists and performance engineers, we combine technical expertise with a deep understanding of business needs.At Ringus, our mission is clear: help our clients build secure, reliable, and high-performing digital systems. If you're looking to strengthen your defenses or optimize your application performance, our Technical Services Team is ready to support you with precision, professionalism, and a proactive approach.

AI Management Standard

At Ringus, we believe that responsible AI adoption is not just a trend—it’s a necessity. With AI transforming industries, leading organizations / entities like NIST, ISO/IEC, HK DPO, the EU, and the UK ICO have published critical guidance / frameworks / standards to ensure AI is ethical, transparent, and risk-aware.Key Best Practice / Standard for AI Deployment and Governance:👉 UK ICO Guidance on AI and Data Protection and AI and Data Protection Risk Toolkit – A reference guidance and toolkit to help businesses avoid privacy violations and bias in AI systems.👉NIST AI Risk Management Framework (AI RMF 1.0) – A structured approach to manage risks to individuals, organizations, and society associated with AI.👉EU AI Act (2024) and Relevant Guideline / Codes of Practice (Under Drafting) – A legal requirement that sets out a clear set of risk-based rules for AI systems and general-purpose AI models. Relevant guideline and Codes of Practice are under development to provide guidance on compliance of regulation.👉Ethical Artificial Intelligence Framework and Hong Kong Generative Artificial Intelligence Technical and Application Guideline  –  A framework that provide practical guidance on embedding ethical principles into AI adoption, focusing on fairness, transparency, and accountability.👉ISO/IEC 42001:2023 – The first global AI management standard, which provide a comprehensive, certifiable framework to establish, implement, maintain, and continually improve trustworthy AI management systems for ensuring responsible, ethical, and secure AI development and deployment.Why Compliance Matters✅ Builds Trust – Customers and regulators demand transparent and fair AI.✅ Reduces Legal Risks – Non-compliance with frameworks like the EU AI Act can lead to heavy fines.✅ Prevents Reputation Damage – AI failures, such as AI bias and privacy breaches, can harm your brand permanently.We help businesses integrate AI responsibly—aligning with global standards and requirements to minimize risks and maximize trust. Feel free to connect with our team for actionable insights on secure and ethical technology adoption.