IELTS Reading: Social Implications of Data Security – Đề thi mẫu có đáp án chi tiết

Mở bài

Trong thời đại số hóa toàn diện hiện nay, vấn đề bảo mật dữ liệu và những tác động xã hội của nó đã trở thành một chủ đề nóng hổi trên toàn cầu. Chủ đề “Social Implications Of Data Security” (Những tác động xã hội của bảo mật dữ liệu) xuất hiện với tần suất ngày càng cao trong các kỳ thi IELTS Reading, đặc biệt từ năm 2018 đến nay. Đây là một chủ đề thuộc nhóm Technology and Society, thường được khai thác ở nhiều góc độ khác nhau từ cơ bản đến nâng cao.

Bài viết này cung cấp cho bạn một bộ đề thi IELTS Reading hoàn chỉnh gồm 3 passages với độ khó tăng dần từ Easy đến Hard, phù hợp cho học viên từ band 5.0 trở lên. Bạn sẽ được luyện tập với 40 câu hỏi đa dạng theo đúng format thi thật, kèm theo đáp án chi tiết và giải thích cụ thể. Đặc biệt, bài viết còn tổng hợp từ vựng quan trọng và các kỹ thuật làm bài hiệu quả giúp bạn tối ưu hóa điểm số.

Hãy dành đủ 60 phút để hoàn thành bài thi trong điều kiện giống thực tế nhất, sau đó đối chiếu đáp án và nghiên cứu kỹ phần giải thích để nâng cao kỹ năng của mình.

1. Hướng dẫn làm bài IELTS Reading

Tổng Quan Về IELTS Reading Test

IELTS Reading Test là một phần thi quan trọng trong kỳ thi IELTS Academic, yêu cầu thí sinh hoàn thành 40 câu hỏi dựa trên 3 passages khác nhau trong vòng 60 phút. Đây là bài kiểm tra khả năng đọc hiểu, phân tích thông tin và quản lý thời gian của bạn.

Phân bổ thời gian khuyến nghị:

• Passage 1 (Easy): 15-17 phút – Đây là phần khởi động với nội dung tương đối dễ hiểu
• Passage 2 (Medium): 18-20 phút – Độ khó tăng lên với từ vựng học thuật hơn
• Passage 3 (Hard): 23-25 phút – Phần khó nhất với nội dung phức tạp và câu hỏi đòi hỏi suy luận cao

Lưu ý: Nên dành 2-3 phút cuối để chuyển đáp án vào answer sheet một cách cẩn thận.

Các Dạng Câu Hỏi Trong Đề Này

Đề thi mẫu này bao gồm 7 dạng câu hỏi phổ biến nhất trong IELTS Reading:

1. Multiple Choice – Câu hỏi trắc nghiệm nhiều lựa chọn
2. True/False/Not Given – Xác định thông tin đúng/sai/không được đề cập
3. Yes/No/Not Given – Xác định quan điểm của tác giả
4. Matching Headings – Nối tiêu đề với đoạn văn
5. Sentence Completion – Hoàn thành câu
6. Summary Completion – Hoàn thành đoạn tóm tắt
7. Short-answer Questions – Câu hỏi trả lời ngắn

2. IELTS Reading Practice Test

PASSAGE 1 – The Digital Footprint: Understanding Personal Data in Modern Society

Độ khó: Easy (Band 5.0-6.5)

Thời gian đề xuất: 15-17 phút

Every time you use your smartphone, browse the internet, or make an online purchase, you leave behind a digital footprint. This trail of data includes everything from your browsing history and location information to your shopping preferences and social media interactions. In today’s interconnected world, understanding what happens to this personal information has become increasingly important for individuals and society as a whole.

Personal data refers to any information that can be used to identify an individual, either directly or indirectly. This includes obvious identifiers like your name, email address, and phone number, but also extends to more subtle information such as your IP address, cookie data, and even your typing patterns. Companies collect this data for various reasons, primarily to improve their services, target advertising, and understand consumer behavior. However, the sheer volume of data being collected has raised significant concerns about privacy and security.

The concept of data security encompasses the protective measures and tools used to safeguard personal information from unauthorized access, corruption, or theft. These measures include encryption technologies, secure passwords, firewalls, and regular security updates. Despite these protections, data breaches have become alarmingly common. In recent years, major corporations and government agencies have experienced significant breaches, exposing the personal information of millions of users.

The social implications of these security issues are far-reaching. When personal data is compromised, individuals may face identity theft, financial fraud, or unwanted surveillance. On a broader scale, data breaches can erode public trust in digital systems and institutions. This loss of confidence can slow down the adoption of beneficial technologies and create a climate of fear and uncertainty around digital interactions.

Demographic groups are affected differently by data security issues. Elderly people, who may be less familiar with technology, often become targets for cybercriminals who exploit their limited digital literacy. Young people, despite being more tech-savvy, frequently share personal information on social media without fully understanding the long-term consequences. Children are particularly vulnerable as they may not comprehend the value of their personal data or the risks associated with sharing it online.

The workplace has also been transformed by data security concerns. Employees increasingly work with sensitive company and customer data, making them potential weak links in the security chain. A single phishing email successfully targeting an employee can provide criminals with access to entire corporate networks. This has led many organizations to invest heavily in cybersecurity training and implement strict data handling protocols.

Educational institutions have recognized the importance of teaching data security awareness. Many schools now include digital citizenship and online safety in their curricula, helping students understand how to protect their personal information and recognize potential threats. This educational approach aims to create a generation that is both digitally empowered and security-conscious.

Regulatory frameworks have emerged globally to address data security concerns. The European Union’s General Data Protection Regulation (GDPR), implemented in 2018, set new standards for how organizations collect, store, and use personal data. Similar legislation has appeared in other regions, reflecting a worldwide recognition that data protection is a fundamental right that requires legal safeguards. These regulations impose significant penalties on organizations that fail to adequately protect user data, providing a strong incentive for better security practices.

Consumer behavior is gradually changing in response to data security concerns. More people are reading privacy policies, using virtual private networks (VPNs), and choosing services based on their security credentials. However, many users still prioritize convenience over security, using simple passwords or agreeing to extensive data collection without careful consideration. This convenience-security trade-off remains a central challenge in promoting better data protection practices.

Looking forward, emerging technologies present both opportunities and challenges for data security. Artificial intelligence can enhance security systems by detecting unusual patterns that might indicate a breach. However, these same technologies can be used by criminals to launch more sophisticated attacks. Blockchain technology promises more secure and transparent data management, but its widespread adoption faces technical and practical hurdles. The ongoing evolution of both threats and protections means that data security will remain a critical social issue for the foreseeable future.

Bảo mật dữ liệu cá nhân trong kỷ nguyên số hóa và IELTS Reading

Questions 1-13

Questions 1-5: Multiple Choice

Choose the correct letter, A, B, C, or D.

1. According to the passage, a digital footprint includes:

   • A. Only social media activity
   • B. Various types of online activities and data
   • C. Just purchasing history
   • D. Only location information

2. Personal data can be used to identify someone through:

   • A. Direct identifiers only
   • B. Indirect identifiers only
   • C. Both direct and indirect identifiers
   • D. Neither direct nor indirect identifiers

3. The main reason companies collect personal data is to:

   • A. Sell it to third parties
   • B. Improve services and understand consumers
   • C. Monitor employee behavior
   • D. Comply with government regulations

4. Which group is mentioned as particularly vulnerable due to limited digital literacy?

   • A. Young professionals
   • B. University students
   • C. Elderly people
   • D. Middle-aged workers

5. The GDPR was implemented in:

   • A. 2016
   • B. 2017
   • C. 2018
   • D. 2019

Questions 6-9: True/False/Not Given

Do the following statements agree with the information given in the passage?

Write:

• TRUE if the statement agrees with the information
• FALSE if the statement contradicts the information
• NOT GIVEN if there is no information on this

6. Data breaches only affect small companies and never impact major corporations.

7. Children fully understand the risks of sharing personal information online.

8. Many schools now include digital citizenship in their teaching programs.

9. All countries have adopted legislation similar to the GDPR.

Questions 10-13: Sentence Completion

Complete the sentences below. Choose NO MORE THAN TWO WORDS from the passage for each answer.

10. Companies use protective measures such as encryption and __ to secure personal information.

11. When data is compromised, individuals might experience __ or financial fraud.

12. A successful __ targeting an employee can give criminals access to company networks.

13. Many users still choose __ over security when making decisions about their data.

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PASSAGE 2 – The Privacy Paradox: Balancing Connectivity and Protection

Độ khó: Medium (Band 6.0-7.5)

Thời gian đề xuất: 18-20 phút

The contemporary digital landscape presents a fundamental contradiction that social scientists have termed the “privacy paradox”. While surveys consistently demonstrate that individuals express deep concern about their personal data security and the erosion of privacy in digital spaces, their actual online behavior frequently contradicts these stated preferences. This discrepancy between attitude and action has profound implications for how societies navigate the complex relationship between technological advancement and personal autonomy.

Behavioral economists have identified several psychological mechanisms that contribute to this paradoxical behavior. The concept of hyperbolic discounting suggests that people disproportionately value immediate rewards over future benefits, leading them to accept privacy risks in exchange for instant gratification such as free services or convenient features. Additionally, the abstract nature of data collection makes its consequences feel distant and intangible. Unlike physical theft, the appropriation of digital information lacks visceral impact, making it psychologically easier to ignore or downplay.

The commodification of personal data has transformed information into one of the most valuable resources in the global economy. Tech giants have constructed business models fundamentally predicated on data extraction, creating what scholar Shoshana Zuboff calls “surveillance capitalism”. This economic system converts human experience into behavioral data, which is then processed and sold to predict and influence future behavior. The asymmetry of power between individuals and corporations in this arrangement raises critical questions about consent and autonomy in the digital age.

Social media platforms exemplify this dynamic particularly clearly. These services offer significant benefits including connection, information access, and entertainment, all ostensibly free. However, users “pay” through the extensive disclosure of personal information, much of which they may not consciously recognize they are providing. Metadata such as the timing of posts, patterns of interaction, and even the duration of hovering over content reveals intimate details about users’ psychological states, relationships, and vulnerabilities. This data is then leveraged to create highly targeted advertising and, increasingly, to shape the content users see in ways that maximize engagement metrics rather than user wellbeing.

The implications extend far beyond commercial advertising. Political campaigns have adopted these same techniques to micro-target voters with messages designed to exploit their specific concerns, fears, and preferences. The Cambridge Analytica scandal demonstrated how harvested social media data could be weaponized to influence democratic processes, raising alarm about the integrity of electoral systems in the digital era. When personal data becomes a tool for political manipulation, the social implications transcend individual privacy concerns to threaten foundational democratic institutions.

Marginalized communities face disproportionate risks in this data-driven landscape. Algorithmic decision-making systems, trained on historical data that reflects existing social biases, often perpetuate and amplify discrimination. Facial recognition technology has documented accuracy problems with darker-skinned faces, leading to false identifications with potentially severe consequences. Credit scoring algorithms may disadvantage individuals from certain neighborhoods or backgrounds. These examples illustrate how data security issues intersect with broader patterns of social inequality, making privacy a matter of social justice.

The psychological burden of constant data surveillance represents another significant social cost. Researchers have documented increased anxiety and self-censorship among individuals aware they are being monitored. This “chilling effect” can stifle creativity, inhibit free expression, and alter authentic behavior. When people curate their online presence with the knowledge that everything might be recorded and analyzed, they may suppress genuine thoughts and feelings in favor of more socially acceptable but less authentic presentations. Over time, this can impact psychological wellbeing and the quality of human connection.

Responses to these challenges have emerged from multiple directions. Privacy-enhancing technologies such as end-to-end encryption, anonymous browsing tools, and decentralized networks offer technical solutions to reduce data exposure. Regulatory interventions, including comprehensive data protection frameworks like the GDPR and California’s Consumer Privacy Act, establish legal standards and enforcement mechanisms. Grassroots movements advocate for data rights and corporate accountability, while some organizations adopt privacy-by-design principles that build protection into systems from the outset rather than adding it as an afterthought.

However, these responses face significant obstacles. Technical solutions often require expertise and effort that limit their adoption beyond tech-savvy users. Regulations struggle to keep pace with rapidly evolving technologies and business practices, and enforcement remains inconsistent across jurisdictions. Corporate resistance to measures that might reduce profitability creates powerful opposition to meaningful reform. Perhaps most fundamentally, the convenience and network effects that make data-intensive services so appealing create “lock-in effects” that make it difficult for individuals to opt out without significant social and practical costs.

The concept of collective privacy has gained traction among scholars and activists who argue that individual consent frameworks are inadequate for addressing systemic data security challenges. Since data about one person often reveals information about their social contacts and communities, privacy cannot be reduced to individual choice. This perspective suggests that data protection requires collective decision-making and solidarity, treating privacy as a common good rather than merely a personal preference. Such an approach would represent a fundamental shift in how societies conceptualize and govern data security.

Educational initiatives aimed at improving data literacy and critical digital consciousness represent another crucial component of addressing these social implications. Understanding how data is collected, processed, and deployed empowers individuals to make more informed choices and advocate for their interests. However, critics argue that placing the burden of protection on individual knowledge and vigilance is insufficient when facing sophisticated corporate and state actors with vast resource advantages. Systemic problems, they contend, require systemic solutions rather than relying on individual behavior change alone.

Thu thập dữ liệu người dùng trên mạng xã hội và tác động xã hội trong IELTS

Questions 14-26

Questions 14-18: Yes/No/Not Given

Do the following statements agree with the views of the writer in the passage?

Write:

• YES if the statement agrees with the views of the writer
• NO if the statement contradicts the views of the writer
• NOT GIVEN if it is impossible to say what the writer thinks about this

14. People’s online behavior consistently matches their stated concerns about privacy.

15. The abstract nature of data collection makes people less worried about its consequences.

16. All tech companies follow the same business model based on data extraction.

17. Marginalized communities experience greater risks from data security issues.

18. Individual consent frameworks are sufficient to address data protection challenges.

Questions 19-22: Matching Information

Match each statement with the correct concept A-F from the box below.

19. People value immediate benefits more than future consequences.

20. Converting human experience into data for commercial purposes.

21. The effect that makes people self-censor when they know they are being watched.

22. When leaving a service becomes difficult due to social and practical reasons.

Concept Box:

• A. Surveillance capitalism
• B. Hyperbolic discounting
• C. Chilling effect
• D. Lock-in effects
• E. Metadata analysis
• F. Privacy paradox

Questions 23-26: Summary Completion

Complete the summary below. Choose NO MORE THAN TWO WORDS from the passage for each answer.

Social media platforms appear to be free but actually require users to provide extensive personal information including (23) __ such as interaction patterns. This data is used to create targeted advertising and shape content to maximize (24) __. Political campaigns have used similar techniques to (25) __ voters. When such data is used for (26) __, it threatens democratic institutions beyond just individual privacy concerns.

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PASSAGE 3 – Socio-Technical Assemblages: The Infrastructural Politics of Data Security

Độ khó: Hard (Band 7.0-9.0)

Thời gian đề xuất: 23-25 phút

The discourse surrounding data security has predominantly focused on technical vulnerabilities and individual privacy rights, yet this framing obscures the deeper infrastructural and sociopolitical dimensions that fundamentally shape how data insecurity manifests as a form of structural violence. Contemporary critical scholarship increasingly conceptualizes data security not as a discrete technical problem amenable to purely technological solutions, but rather as a nexus where techno-social assemblages, political economy, and power asymmetries converge to produce differentiated vulnerabilities and stratified experiences of digital citizenship.

The materiality of data infrastructure reveals how security concerns are embedded in physical systems that reflect and reinforce existing geopolitical hierarchies. Submarine fiber-optic cables that constitute the backbone of global internet connectivity predominantly route through and are controlled by actors in wealthy nations, creating chokepoints where surveillance and interception become architecturally feasible. Data centers, which consume enormous quantities of energy and water, are disproportionately located in regions where environmental regulations are lax and labor is cheap, externalizing the ecological and social costs of data processing onto marginalized populations. This infrastructural colonialism demonstrates how data security intersects with broader patterns of global inequality and environmental injustice.

Surveillance studies scholars have documented how data security discourse often serves hegemonic functions, framing security primarily in terms of protecting existing power structures rather than empowering vulnerable populations. State security agencies routinely invoke data security concerns to justify expanded surveillance capabilities, creating architectures of control that disproportionately target racial minorities, political dissidents, and immigrant communities. The securitization of borders increasingly relies on biometric databases and algorithmic risk assessment systems that encode discriminatory assumptions about which bodies represent threats. When law enforcement agencies deploy predictive policing algorithms trained on biased historical data, they create feedback loops that concentrate scrutiny on already over-policed communities, transforming data security apparatus into instruments of social control rather than protection.

The concept of “security theater” applies aptly to many institutional responses to data breaches. Organizations implement visible security measures such as mandatory password changes and compliance training that create an appearance of action without addressing fundamental vulnerabilities embedded in system architectures and business models. These performative interventions serve primarily to manage reputational risk and satisfy regulatory requirements rather than meaningfully reducing harm to affected individuals. Notification protocols following breaches often employ obfuscating language that minimizes perceived severity and deflects accountability, while offering perfunctory credit monitoring services that provide minimal protection against sophisticated identity theft techniques.

Critical data studies have illuminated how data-intensive technologies reconfigure social relations and reshape intersubjective experiences in ways that extend far beyond conventional privacy concerns. Intimate surveillance facilitated by smart home devices, wearable fitness trackers, and health monitoring applications generates unprecedented granular data about bodies, behaviors, and domestic spaces. This corporeal data is aggregated and analyzed to construct predictive profiles that inform decisions about insurance eligibility, employment opportunities, and access to services. The datafication of intimacy transforms private experiences into quantifiable metrics subject to algorithmic interpretation, creating new forms of biopolitical governance that operate through anticipatory logic rather than responding to observed behaviors.

The epistemological dimensions of data security deserve greater attention. Machine learning systems that process vast datasets to identify security threats or fraudulent activities operate as “black boxes” whose decision-making processes remain opaque even to their creators. This algorithmic opacity presents profound challenges for accountability and contestability. When individuals are denied services or subjected to additional scrutiny based on algorithmic assessments, they typically cannot access meaningful explanations or effectively challenge decisions. The inscrutability of these systems concentrates power in the hands of technical specialists and platform operators while disempowering those subject to algorithmic judgment. Tương tự như The role of AI in improving productivity, công nghệ học máy đang tạo ra những thay đổi sâu sắc trong cách xã hội hoạt động, nhưng đồng thời cũng đặt ra những thách thức mới về quyền lực và trách nhiệm.

Resistance practices to data extraction and surveillance have proliferated, ranging from individual obfuscation tactics to collective organizing around data justice principles. Digital detox movements encourage temporary or permanent disengagement from data-intensive platforms. Cryptographic tools enable secure communication resistant to third-party interception. Data cooperatives explore alternative governance models where individuals collectively control data assets. However, these strategies remain largely confined to relatively privileged actors with resources and technical capacity to implement them, while vulnerable populations—including the unhoused, undocumented immigrants, and those in carceral settings—face compulsory datafication with minimal capacity to resist or negotiate terms of engagement.

The political economy of data security reflects and reinforces transnational patterns of wealth concentration and asymmetric power relations. The oligopolistic structure of the technology sector means that a handful of corporations exercise outsized influence over digital infrastructure, standards, and norms. These platform giants possess capabilities for data aggregation and analysis that far exceed those available to individuals, communities, or even most nation-states. Antitrust frameworks developed for industrial-era monopolies prove inadequate for addressing the distinctive competitive dynamics of data-driven markets, where network effects and economies of scale in data collection create formidable barriers to entry. Regulatory capture, where industry actors shape the very regulations meant to constrain them, further entrenches existing power structures.

Decolonial and postcolonial critiques highlight how data security discourse often universalizes Western liberal conceptions of privacy and individual rights while marginalizing alternative cultural frameworks and communal approaches to information governance. Indigenous communities, for instance, may conceptualize data sovereignty quite differently, emphasizing collective rights and relationships to land and heritage rather than individual control over personal information. For communities with histories of exploitation through research and documentation, data security concerns center on epistemic justice and ensuring that data collection and analysis serve community interests rather than extracting value for external actors. These perspectives challenge the adequacy of dominant data protection frameworks and call for more pluralistic approaches that respect diverse ways of understanding information, privacy, and security.

The temporal dimensions of data security remain underexamined. Unlike physical threats that occur in discrete moments, data insecurity involves attenuated harms that may not materialize until years or decades after initial compromise. Biometric data, once compromised, cannot be changed like passwords. The “digital exhaust” produced throughout life accumulates into comprehensive profiles that could be weaponized against individuals or used to discriminate against their descendants. This intergenerational dimension raises profound ethical questions about consent, as current decisions about data sharing and security have consequences that extend beyond the lifespans of those making them. Forensic practices that analyze historical data to retroactively identify individuals or predict behaviors create temporally complex scenarios where past information becomes newly dangerous in present contexts.

Emerging technologies including quantum computing, synthetic biology, and brain-computer interfaces promise to dramatically expand both the scope and sensitivity of data collection, intensifying existing security challenges while introducing novel concerns. Quantum computers could potentially break current encryption standards, necessitating comprehensive cryptographic infrastructure overhauls. Neurotechnologies that read and modulate brain activity raise the specter of cognitive surveillance and mental privacy violations. Gene editing and precision medicine rely on extensive genetic data, the security of which has ramifications not only for individuals but for their biological relatives and broader population groups who share genetic characteristics. Những tiến bộ công nghệ này, tương tự Big data’s role in environmental conservation, có tiềm năng mang lại lợi ích to lớn nhưng cũng đòi hỏi sự cảnh giác về các tác động xã hội tiềm ẩn.

Addressing the social implications of data security requires moving beyond techno-solutionism toward comprehensive approaches that integrate technical, regulatory, economic, and cultural interventions. Participatory design methodologies that involve affected communities in shaping data systems can help ensure that security measures reflect diverse needs and contexts rather than imposing one-size-fits-all solutions. Public interest technology initiatives seek to develop alternatives to extraction-based business models, creating sustainable systems that align incentives with user wellbeing. Digital public infrastructure operated according to democratic principles could provide essential services without subjecting users to commercial surveillance. Cultivating critical data consciousness throughout society enables more informed collective deliberation about the socio-technical futures we wish to inhabit. Ultimately, achieving meaningful data security demands recognizing it as fundamentally a political project concerning the distribution of power, resources, and vulnerability in increasingly datafied societies.

Hạ tầng dữ liệu toàn cầu và vấn đề bảo mật trong bài thi IELTS Reading

Questions 27-40

Questions 27-31: Multiple Choice

Choose the correct letter, A, B, C, or D.

27. According to the passage, contemporary scholarship views data security as:

    • A. Purely a technical problem
    • B. A convergence of technical, social and political factors
    • C. Only an individual privacy concern
    • D. A problem that can be easily solved

28. The materiality of data infrastructure demonstrates:

    • A. That all countries have equal access to technology
    • B. How physical systems reflect geopolitical hierarchies
    • C. That data centers have no environmental impact
    • D. That infrastructure is distributed fairly globally

29. The term “security theater” refers to:

    • A. Effective security measures
    • B. Training programs for employees
    • C. Visible measures that don’t address fundamental vulnerabilities
    • D. Entertainment about security topics

30. Machine learning systems are described as “black boxes” because:

    • A. They are physically black in color
    • B. Their decision-making processes are opaque
    • C. They are located in dark rooms
    • D. They only process dark data

31. Indigenous communities’ approach to data sovereignty emphasizes:

    • A. Individual control exclusively
    • B. Corporate partnerships
    • C. Collective rights and relationships
    • D. Western privacy concepts

Questions 32-36: Matching Features

Match each concept with the correct description A-H.

Write the correct letter A-H next to questions 32-36.

32. Infrastructural colonialism _____
33. Predictive policing _____
34. Algorithmic opacity _____
35. Data cooperatives _____
36. Intergenerational dimension _____

Descriptions:

• A. When past decisions about data have consequences for future generations
• B. Algorithms that concentrate scrutiny on already over-policed communities
• C. Systems whose decision-making processes are not transparent
• D. When data infrastructure costs are imposed on marginalized populations
• E. Individual resistance to data collection
• F. Alternative governance models for collective data control
• G. Government data storage facilities
• H. Public awareness campaigns

Questions 37-40: Short-answer Questions

Answer the questions below. Choose NO MORE THAN THREE WORDS from the passage for each answer.

37. What type of data cannot be changed once compromised, unlike passwords?

38. What emerging technology could potentially break current encryption standards?

39. What type of design methodology involves affected communities in shaping data systems?

40. According to the passage, achieving meaningful data security is fundamentally what type of project?

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3. Answer Keys – Đáp Án

PASSAGE 1: Questions 1-13

1. B
2. C
3. B
4. C
5. C
6. FALSE
7. FALSE
8. TRUE
9. NOT GIVEN
10. firewalls
11. identity theft
12. phishing email
13. convenience

PASSAGE 2: Questions 14-26

14. NO
15. YES
16. NOT GIVEN
17. YES
18. NO
19. B
20. A
21. C
22. D
23. metadata
24. engagement metrics
25. micro-target
26. political manipulation

PASSAGE 3: Questions 27-40

27. B
28. B
29. C
30. B
31. C
32. D
33. B
34. C
35. F
36. A
37. Biometric data
38. Quantum computing
39. Participatory design
40. political project

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4. Giải Thích Đáp Án Chi Tiết

Passage 1 – Giải Thích

Câu 1: B

• Dạng câu hỏi: Multiple Choice
• Từ khóa: digital footprint, includes
• Vị trí trong bài: Đoạn 1, dòng 1-3
• Giải thích: Đoạn văn nói rõ “This trail of data includes everything from your browsing history and location information to your shopping preferences and social media interactions.” Điều này cho thấy digital footprint bao gồm nhiều loại hoạt động trực tuyến khác nhau, không chỉ một loại duy nhất như các đáp án A, C, D.

Câu 2: C

• Dạng câu hỏi: Multiple Choice
• Từ khóa: Personal data, identify someone
• Vị trí trong bài: Đoạn 2, dòng 1-3
• Giải thích: Passage nói rõ “any information that can be used to identify an individual, either directly or indirectly”. Từ “either…or” cho thấy cả hai cách đều có thể được sử dụng.

Câu 3: B

• Dạng câu hỏi: Multiple Choice
• Từ khóa: main reason, companies collect
• Vị trí trong bài: Đoạn 2, dòng 4-6
• Giải thích: “Companies collect this data for various reasons, primarily to improve their services, target advertising, and understand consumer behavior.” Từ “primarily” chỉ ra lý do chính.

Câu 4: C

• Dạng câu hỏi: Multiple Choice
• Từ khóa: vulnerable, limited digital literacy
• Vị trí trong bài: Đoạn 5, dòng 1-3
• Giải thích: “Elderly people, who may be less familiar with technology, often become targets for cybercriminals who exploit their limited digital literacy.”

Câu 5: C

• Dạng câu hỏi: Multiple Choice
• Từ khóa: GDPR, implemented
• Vị trí trong bài: Đoạn 8, dòng 1-2
• Giải thích: Passage nói rõ “The European Union’s General Data Protection Regulation (GDPR), implemented in 2018”.

Câu 6: FALSE

• Dạng câu hỏi: True/False/Not Given
• Từ khóa: Data breaches, only small companies, never major corporations
• Vị trí trong bài: Đoạn 3, dòng cuối
• Giải thích: Passage nói “major corporations and government agencies have experienced significant breaches”, điều này mâu thuẫn trực tiếp với câu hỏi.

Câu 7: FALSE

• Dạng câu hỏi: True/False/Not Given
• Từ khóa: Children, fully understand, risks
• Vị trí trong bài: Đoạn 5, dòng cuối
• Giải thích: “Children are particularly vulnerable as they may not comprehend the value of their personal data or the risks” – từ “may not comprehend” cho thấy trẻ em không hiểu đầy đủ rủi ro.

Câu 8: TRUE

• Dạng câu hỏi: True/False/Not Given
• Từ khóa: schools, digital citizenship
• Vị trí trong bài: Đoạn 7, dòng 1-2
• Giải thích: “Many schools now include digital citizenship and online safety in their curricula” khớp hoàn toàn với câu hỏi.

Câu 9: NOT GIVEN

• Dạng câu hỏi: True/False/Not Given
• Từ khóa: All countries, adopted legislation, similar to GDPR
• Vị trí trong bài: Đoạn 8
• Giải thích: Passage chỉ nói “Similar legislation has appeared in other regions” nhưng không nói “all countries”, không có đủ thông tin để xác nhận hoặc bác bỏ.

Câu 10: firewalls

• Dạng câu hỏi: Sentence Completion
• Từ khóa: protective measures, encryption
• Vị trí trong bài: Đoạn 3, dòng 2-3
• Giải thích: “These measures include encryption technologies, secure passwords, firewalls, and regular security updates.”

Câu 11: identity theft

• Dạng câu hỏi: Sentence Completion
• Từ khóa: data compromised, individuals might experience
• Vị trí trong bài: Đoạn 4, dòng 1-2
• Giải thích: “individuals may face identity theft, financial fraud, or unwanted surveillance.”

Câu 12: phishing email

• Dạng câu hỏi: Sentence Completion
• Từ khóa: targeting employee, access company networks
• Vị trí trong bài: Đoạn 6, dòng 3-4
• Giải thích: “A single phishing email successfully targeting an employee can provide criminals with access to entire corporate networks.”

Câu 13: convenience

• Dạng câu hỏi: Sentence Completion
• Từ khóa: users prioritize, over security
• Vị trí trong bài: Đoạn 9, dòng 2-3
• Giải thích: “many users still prioritize convenience over security” và cụm từ “convenience-security trade-off” được nhắc đến sau đó.

Passage 2 – Giải Thích

Câu 14: NO

• Dạng câu hỏi: Yes/No/Not Given
• Từ khóa: online behavior, consistently matches, stated concerns
• Vị trí trong bài: Đoạn 1, dòng 2-4
• Giải thích: Passage mô tả “privacy paradox” – “their actual online behavior frequently contradicts these stated preferences”, rõ ràng là không khớp.

Câu 15: YES

• Dạng câu hỏi: Yes/No/Not Given
• Từ khóa: abstract nature, less worried
• Vị trí trong bài: Đoạn 2, dòng 3-5
• Giải thích: “the abstract nature of data collection makes its consequences feel distant and intangible…making it psychologically easier to ignore or downplay.”

Câu 16: NOT GIVEN

• Dạng câu hỏi: Yes/No/Not Given
• Từ khóa: All tech companies, same business model
• Vị trí trong bài: Đoạn 3
• Giải thích: Passage nói về “Tech giants” và business model của họ nhưng không khẳng định “all” tech companies đều làm vậy.

Câu 17: YES

• Dạng câu hỏi: Yes/No/Not Given
• Từ khóa: Marginalized communities, greater risks
• Vị trí trong bài: Đoạn 6, dòng 1
• Giải thích: “Marginalized communities face disproportionate risks in this data-driven landscape” – từ “disproportionate” có nghĩa là bất cân xứng, tức là rủi ro cao hơn.

Câu 18: NO

• Dạng câu hỏi: Yes/No/Not Given
• Từ khóa: Individual consent frameworks, sufficient
• Vị trí trong bài: Đoạn 10, dòng 1-2
• Giải thích: “scholars and activists who argue that individual consent frameworks are inadequate for addressing systemic data security challenges” – từ “inadequate” có nghĩa là không đủ.

Câu 19: B (Hyperbolic discounting)

• Dạng câu hỏi: Matching Information
• Từ khóa: value immediate benefits, future consequences
• Vị trí trong bài: Đoạn 2, dòng 2-3
• Giải thích: “The concept of hyperbolic discounting suggests that people disproportionately value immediate rewards over future benefits.”

Câu 20: A (Surveillance capitalism)

• Dạng câu hỏi: Matching Information
• Từ khóa: Converting human experience into data, commercial purposes
• Vị trí trong bài: Đoạn 3, dòng 2-4
• Giải thích: “This economic system converts human experience into behavioral data, which is then processed and sold.”

Câu 21: C (Chilling effect)

• Dạng câu hỏi: Matching Information
• Từ khóa: people self-censor, being watched
• Vị trí trong bài: Đoạn 7, dòng 2-3
• Giải thích: “This ‘chilling effect’ can stifle creativity, inhibit free expression, and alter authentic behavior.”

Câu 22: D (Lock-in effects)

• Dạng câu hỏi: Matching Information
• Từ khóa: leaving service becomes difficult, social and practical reasons
• Vị trí trong bài: Đoạn 9, dòng cuối
• Giải thích: “create ‘lock-in effects’ that make it difficult for individuals to opt out without significant social and practical costs.”

Câu 23: metadata

• Dạng câu hỏi: Summary Completion
• Từ khóa: personal information including, interaction patterns
• Vị trí trong bài: Đoạn 4, dòng 3-5
• Giải thích: “Metadata such as the timing of posts, patterns of interaction…”

Câu 24: engagement metrics

• Dạng câu hỏi: Summary Completion
• Từ khóa: shape content to maximize
• Vị trí trong bài: Đoạn 4, dòng cuối
• Giải thích: “shape the content users see in ways that maximize engagement metrics.”

Câu 25: micro-target

• Dạng câu hỏi: Summary Completion
• Từ khóa: Political campaigns, techniques to…voters
• Vị trí trong bài: Đoạn 5, dòng 1-2
• Giải thích: “Political campaigns have adopted these same techniques to micro-target voters.”

Câu 26: political manipulation

• Dạng câu hỏi: Summary Completion
• Từ khóa: When data used for, threatens democratic institutions
• Vị trí trong bài: Đoạn 5, dòng cuối
• Giải thích: “When personal data becomes a tool for political manipulation, the social implications…threaten foundational democratic institutions.”

Passage 3 – Giải Thích

Câu 27: B

• Dạng câu hỏi: Multiple Choice
• Từ khóa: contemporary scholarship, views data security
• Vị trí trong bài: Đoạn 1, dòng 2-4
• Giải thích: Passage nói rõ “Contemporary critical scholarship increasingly conceptualizes data security…as a nexus where techno-social assemblages, political economy, and power asymmetries converge.”

Câu 28: B

• Dạng câu hỏi: Multiple Choice
• Từ khóa: materiality of data infrastructure, demonstrates
• Vị trí trong bài: Đoạn 2, dòng 1-2
• Giải thích: “The materiality of data infrastructure reveals how security concerns are embedded in physical systems that reflect and reinforce existing geopolitical hierarchies.”

Câu 29: C

• Dạng câu hỏi: Multiple Choice
• Từ khóa: security theater, refers to
• Vị trí trong bài: Đoạn 4, dòng 2-5
• Giải thích: “Organizations implement visible security measures…that create an appearance of action without addressing fundamental vulnerabilities.”

Câu 30: B

• Dạng câu hỏi: Multiple Choice
• Từ khóa: Machine learning systems, black boxes, because
• Vị trí trong bài: Đoạn 6, dòng 2-3
• Giải thích: “Machine learning systems…operate as ‘black boxes’ whose decision-making processes remain opaque even to their creators.”

Câu 31: C

• Dạng câu hỏi: Multiple Choice
• Từ khóa: Indigenous communities, data sovereignty, emphasizes
• Vị trí trong bài: Đoạn 9, dòng 2-4
• Giải thích: “Indigenous communities…may conceptualize data sovereignty quite differently, emphasizing collective rights and relationships to land and heritage.”

Câu 32: D

• Dạng câu hỏi: Matching Features
• Từ khóa: Infrastructural colonialism
• Vị trí trong bài: Đoạn 2, dòng cuối
• Giải thích: “This infrastructural colonialism demonstrates…externalizing the ecological and social costs of data processing onto marginalized populations.”

Câu 33: B

• Dạng câu hỏi: Matching Features
• Từ khóa: Predictive policing
• Vị trí trong bài: Đoạn 3, dòng giữa
• Giải thích: “law enforcement agencies deploy predictive policing algorithms…create feedback loops that concentrate scrutiny on already over-policed communities.”

Câu 34: C

• Dạng câu hỏi: Matching Features
• Từ khóa: Algorithmic opacity
• Vị trí trong bài: Đoạn 6, dòng 3
• Giải thích: “This algorithmic opacity presents profound challenges for accountability and contestability” – opacity nghĩa là sự không minh bạch.

Câu 35: F

• Dạng câu hỏi: Matching Features
• Từ khóa: Data cooperatives
• Vị trí trong bài: Đoạn 7, dòng giữa
• Giải thích: “Data cooperatives explore alternative governance models where individuals collectively control data assets.”

Câu 36: A

• Dạng câu hỏi: Matching Features
• Từ khóa: Intergenerational dimension
• Vị trí trong bài: Đoạn 10, dòng giữa
• Giải thích: “This intergenerational dimension raises profound ethical questions about consent, as current decisions about data sharing…have consequences that extend beyond the lifespans of those making them.”

Câu 37: Biometric data

• Dạng câu hỏi: Short-answer Questions
• Từ khóa: type of data, cannot be changed, unlike passwords
• Vị trí trong bài: Đoạn 10, dòng 3
• Giải thích: “Biometric data, once compromised, cannot be changed like passwords.”

Câu 38: Quantum computing

• Dạng câu hỏi: Short-answer Questions
• Từ khóa: emerging technology, break current encryption standards
• Vị trí trong bài: Đoạn 11, dòng 3-4
• Giải thích: “Quantum computers could potentially break current encryption standards.”

Câu 39: Participatory design

• Dạng câu hỏi: Short-answer Questions
• Từ khóa: design methodology, involves affected communities
• Vị trí trong bài: Đoạn 12, dòng 2
• Giải thích: “Participatory design methodologies that involve affected communities in shaping data systems.”

Câu 40: political project

• Dạng câu hỏi: Short-answer Questions
• Từ khóa: achieving meaningful data security, fundamentally, type of project
• Vị trí trong bài: Đoạn 12, dòng cuối
• Giải thích: “Ultimately, achieving meaningful data security demands recognizing it as fundamentally a political project.”

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5. Từ Vựng Quan Trọng Theo Passage

Passage 1 – Essential Vocabulary

Từ vựng	Loại từ	Phiên âm	Nghĩa tiếng Việt	Ví dụ từ bài	Collocation
digital footprint	n	/ˈdɪdʒɪtl ˈfʊtprɪnt/	dấu vết kỹ thuật số	Every time you browse, you leave behind a digital footprint	leave a digital footprint
data breach	n	/ˈdeɪtə briːtʃ/	vi phạm dữ liệu, rò rỉ dữ liệu	Data breaches have become alarmingly common	experience/suffer a data breach
encryption	n	/ɪnˈkrɪpʃn/	mã hóa	Encryption technologies protect personal information	end-to-end encryption
identity theft	n	/aɪˈdentəti θeft/	trộm cắp danh tính	Individuals may face identity theft	victim of identity theft
cybercriminal	n	/ˈsaɪbəkrɪmɪnl/	tội phạm mạng	Cybercriminals exploit limited digital literacy	sophisticated cybercriminals
phishing email	n	/ˈfɪʃɪŋ ˈiːmeɪl/	email lừa đảo	A phishing email can provide access to networks	fall for a phishing email
firewall	n	/ˈfaɪəwɔːl/	tường lửa	Security measures include firewalls	install/configure a firewall
erode public trust	v phrase	/ɪˈrəʊd ˈpʌblɪk trʌst/	làm xói mòn lòng tin công chúng	Data breaches can erode public trust	seriously erode trust
digital citizenship	n	/ˈdɪdʒɪtl ˈsɪtɪznʃɪp/	quyền công dân số	Schools include digital citizenship in curricula	teach digital citizenship
privacy policy	n	/ˈprɪvəsi ˈpɒləsi/	chính sách bảo mật	More people are reading privacy policies	review/update privacy policy
vulnerable population	n	/ˈvʌlnərəbl pɒpjuˈleɪʃn/	nhóm dân cư dễ bị tổn thương	Children are particularly vulnerable	protect vulnerable populations
regulatory framework	n	/ˈreɡjələtəri ˈfreɪmwɜːk/	khung quy định	Regulatory frameworks have emerged globally	establish a regulatory framework

Passage 2 – Essential Vocabulary

Từ vựng	Loại từ	Phiên âm	Nghĩa tiếng Việt	Ví dụ từ bài	Collocation
privacy paradox	n	/ˈprɪvəsi ˈpærədɒks/	nghịch lý quyền riêng tư	Social scientists term this the privacy paradox	illustrate/demonstrate the paradox
hyperbolic discounting	n	/haɪpəˈbɒlɪk dɪsˈkaʊntɪŋ/	chiết khấu theo hàm hyperbol (ưu tiên lợi ích trước mắt)	Hyperbolic discounting values immediate rewards	concept of hyperbolic discounting
surveillance capitalism	n	/səˈveɪləns ˈkæpɪtəlɪzəm/	chủ nghĩa tư bản giám sát	Scholar Zuboff calls this surveillance capitalism	critique surveillance capitalism
commodification	n	/kəˌmɒdɪfɪˈkeɪʃn/	sự hàng hóa hóa	The commodification of personal data	increasing commodification
metadata	n	/ˈmetədeɪtə/	siêu dữ liệu	Metadata reveals intimate details about users	collect/analyze metadata
micro-target	v	/ˈmaɪkrəʊ ˈtɑːɡɪt/	nhắm mục tiêu vi mô	Political campaigns micro-target voters	ability to micro-target
algorithmic decision-making	n	/ælɡəˈrɪðmɪk dɪˈsɪʒn meɪkɪŋ/	ra quyết định bằng thuật toán	Algorithmic decision-making systems perpetuate bias	rely on algorithmic decision-making
chilling effect	n	/ˈtʃɪlɪŋ ɪˈfekt/	hiệu ứng làm lạnh (tự kiểm duyệt)	Surveillance creates a chilling effect	have a chilling effect on
lock-in effect	n	/lɒk ɪn ɪˈfekt/	hiệu ứng khóa chặt	Convenience creates lock-in effects	overcome lock-in effects
privacy-enhancing technology	n	/ˈprɪvəsi ɪnˈhɑːnsɪŋ tekˈnɒlədʒi/	công nghệ tăng cường quyền riêng tư	Privacy-enhancing technologies offer solutions	develop privacy-enhancing technologies
collective privacy	n	/kəˈlektɪv ˈprɪvəsi/	quyền riêng tư tập thể	The concept of collective privacy	protect collective privacy
data literacy	n	/ˈdeɪtə ˈlɪtərəsi/	hiểu biết về dữ liệu	Improving data literacy empowers individuals	promote data literacy
engagement metrics	n	/ɪnˈɡeɪdʒmənt ˈmetrɪks/	các chỉ số tương tác	Content is shaped to maximize engagement metrics	track engagement metrics
political manipulation	n	/pəˈlɪtɪkl mənɪpjuˈleɪʃn/	thao túng chính trị	Data becomes a tool for political manipulation	vulnerable to political manipulation
marginalized community	n	/ˈmɑːdʒɪnəlaɪzd kəˈmjuːnəti/	cộng đồng bị thiệt thòi	Marginalized communities face disproportionate risks	support marginalized communities

Passage 3 – Essential Vocabulary

Từ vựng	Loại từ	Phiên âm	Nghĩa tiếng Việt	Ví dụ từ bài	Collocation
socio-technical assemblage	n	/ˌsəʊsiəʊ ˈteknɪkl əˈsemblɪdʒ/	tổ hợp kỹ thuật-xã hội	Data security as a socio-technical assemblage	complex socio-technical assemblage
infrastructural colonialism	n	/ˌɪnfrəˈstrʌktʃərəl kəˈləʊniəlɪzəm/	chủ nghĩa thực dân về cơ sở hạ tầng	This demonstrates infrastructural colonialism	forms of infrastructural colonialism
hegemonic function	n	/heɡəˈmɒnɪk ˈfʌŋkʃn/	chức năng thống trị	Discourse serves hegemonic functions	perform hegemonic functions
biometric database	n	/ˌbaɪəʊˈmetrɪk ˈdeɪtəbeɪs/	cơ sở dữ liệu sinh trắc học	Borders rely on biometric databases	establish biometric databases
algorithmic opacity	n	/ælɡəˈrɪðmɪk əʊˈpæsəti/	sự mờ đục của thuật toán	Algorithmic opacity challenges accountability	problem of algorithmic opacity
datafication	n	/ˌdeɪtəfɪˈkeɪʃn/	sự dữ liệu hóa	The datafication of intimacy	increasing datafication
biopolitical governance	n	/ˌbaɪəʊpəˈlɪtɪkl ˈɡʌvənəns/	quản trị sinh chính trị	Creates new forms of biopolitical governance	systems of biopolitical governance
obfuscation tactic	n	/ˌɒbfʌˈskeɪʃn ˈtæktɪk/	chiến thuật làm mờ	Individual obfuscation tactics	employ obfuscation tactics
data cooperative	n	/ˈdeɪtə kəʊˈɒpərətɪv/	hợp tác xã dữ liệu	Data cooperatives explore alternative models	form data cooperatives
oligopolistic structure	n	/ˌɒlɪɡəpəˈlɪstɪk ˈstrʌktʃə/	cấu trúc độc quyền nhóm	The oligopolistic structure of tech sector	maintain oligopolistic structure
epistemic justice	n	/epɪˈstiːmɪk ˈdʒʌstɪs/	công lý tri thức	Concerns center on epistemic justice	pursue epistemic justice
decolonial critique	n	/diːkəˈləʊniəl krɪˈtiːk/	phê phán phi thực dân	Decolonial critiques highlight limitations	apply decolonial critique
intergenerational dimension	n	/ˌɪntədʒenəˈreɪʃənl daɪˈmenʃn/	chiều hướng liên thế hệ	The intergenerational dimension raises questions	consider intergenerational dimensions
quantum computing	n	/ˈkwɒntəm kəmˈpjuːtɪŋ/	máy tính lượng tử	Quantum computing could break encryption	advances in quantum computing
participatory design	n	/pɑːˈtɪsɪpətəri dɪˈzaɪn/	thiết kế có sự tham gia	Participatory design involves communities	adopt participatory design
techno-solutionism	n	/ˌteknəʊ səˈluːʃənɪzəm/	chủ nghĩa giải pháp công nghệ	Moving beyond techno-solutionism	critique of techno-solutionism
digital public infrastructure	n	/ˈdɪdʒɪtl ˈpʌblɪk ˈɪnfrəstrʌktʃə/	cơ sở hạ tầng công cộng số	Create digital public infrastructure	invest in digital public infrastructure
predictive policing	n	/prɪˈdɪktɪv pəˈliːsɪŋ/	cảnh sát dự đoán	Predictive policing algorithms encode bias	systems of predictive policing

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Kết bài

Bài thi IELTS Reading mẫu về chủ đề “Social implications of data security” này đã cung cấp cho bạn một trải nghiệm luyện tập toàn diện với ba passages có độ khó tăng dần. Chủ đề bảo mật dữ liệu và tác động xã hội của nó không chỉ là một đề tài nóng trong kỳ thi IELTS mà còn là kiến thức thực tế vô cùng quan trọng trong thời đại số hóa hiện nay.

Qua 40 câu hỏi đa dạng với 7 dạng bài khác nhau, bạn đã được thực hành các kỹ năng quan trọng như scanning, skimming, paraphrasing, và suy luận logic. Phần đáp án chi tiết kèm giải thích cụ thể giúp bạn hiểu rõ tại sao một đáp án đúng và cách xác định thông tin trong passage một cách chính xác. Đặc biệt, bảng từ vựng theo từng passage cung cấp hơn 40 từ và cụm từ quan trọng với phiên âm, nghĩa, ví dụ và collocations, giúp bạn mở rộng vốn từ học thuật hiệu quả.

Để tối đa hóa hiệu quả học tập, hãy xem lại những câu bạn làm sai, phân tích kỹ phần giải thích, và ghi chú lại các từ vựng mới. Luyện tập thường xuyên với các đề thi đa dạng về chủ đề sẽ giúp bạn tự tin hơn và đạt band điểm mong muốn trong kỳ thi IELTS Reading thực tế. Tương tự The impact of social media on public opinion và The role of digital transformation in global trade, những chủ đề về công nghệ và xã hội đều đòi hỏi khả năng đọc hiểu sâu và vốn từ vựng học thuật phong phú.

Chúc bạn ôn tập hiệu quả và đạt kết quả cao trong kỳ thi IELTS sắp tới!