Survey on IoT Privacy, Data Protection and Security Concerns

Abstract

The proliferation of Internet of Things (IoT) devices has transformed the way we interact with the digital world, offering unprecedented connectivity and convenience. However, this rapid expansion brings forth profound challenges concerning privacy, data protection, and security. This survey paper comprehensively explores the multifaceted landscape of IoT, dissecting its architecture, and delving into the intricate web of concerns surrounding user privacy, data safeguarding, and system security.Beginning with an examination of the IoT architecture, we dissect the interconnected layers, ranging from sensors to cloud platforms, illustrating the intricate pathways of data flow. The survey meticulously unfolds the privacy challenges embedded in the constant data collection, tracking, and profiling mechanisms intrinsic to IoT devices. Drawing on real-world examples, we underscore the tangible consequences of privacy breaches and the potential erosion of user trust.In the realm of data protection, we delve into the complexities of safeguarding data integrity, confidentiality, and availability within the IoT ecosystem. Regulatory frameworks, notably the General Data Protection Regulation (GDPR), are scrutinized for their impact on shaping data protection practices. Concurrently, the paper uncovers common security threats in IoT, emphasizing vulnerabilities in devices and the looming risks associated with unauthorized access and data breaches.Navigating through the regulatory landscape, the survey provides an overview of existing standards and regulations governing IoT. Case studies spotlight instances of privacy breaches, data protection lapses, and security vulnerabilities, offering practical insights into the implications of these incidents. Mitigation strategies, encompassing encryption, authentication, and access control, are explored to address the identified concerns.As the paper concludes, it synthesizes the key findings, emphasizing the urgency of continued efforts to fortify IoT against privacy, data protection, and security challenges. The survey anticipates future trends and challenges, offering a roadmap for researchers, policymakers, and industry stakeholders to collectively forge a secure and privacy-aware IoT landscape.

Introduction

I. INTRODUCTION

The Internet of Things (IoT) stands at the forefront of a technological revolution, orchestrating an interconnected ecosystem where everyday devices communicate, collect, and exchange data. This proliferation of IoT devices, ranging from smart thermostats to industrial sensors, promises to reshape industries, enhance efficiency, and elevate the quality of life for individuals. However, this transformative potential is accompanied by a myriad of concerns that demand meticulous attention—chief among them are issues related to privacy, data protection, and security.

The very essence of IoT lies in the pervasive connectivity of devices, fostering an environment where data flows seamlessly between sensors, edge devices, and centralized cloud platforms. This interconnected architecture, while offering unparalleled insights and functionalities, simultaneously raises intricate challenges concerning the privacy of individuals. The constant stream of data generated by IoT devices, encompassing personal behaviors, preferences, and even physical locations, invites scrutiny into the ethical dimensions of data collection and usage.

Simultaneously, the extensive collection and processing of data in the IoT ecosystem present a complex landscape for ensuring the protection of sensitive information. Data breaches, unauthorized access, and the potential compromise of critical systems underscore the urgency of robust data protection measures. Regulatory frameworks, exemplified by the General Data Protection Regulation (GDPR), exert a significant influence on shaping data protection practices in the IoT space.

Security, a linchpin in the reliability and trustworthiness of any technological system, becomes even more critical in the context of IoT. Vulnerabilities in IoT devices, if exploited, can have far-reaching consequences, not only compromising individual privacy but also posing tangible risks to safety and the integrity of critical infrastructure.

Against this backdrop, this survey paper embarks on a comprehensive exploration of IoT privacy, data protection, and security concerns. Through a systematic analysis of the architecture, regulatory landscape, and real-world case studies, we aim to dissect the intricate web of challenges and potential solutions. As the IoT landscape continues to evolve, this survey aims to contribute a nuanced understanding of the existing issues, laying the groundwork for future research, policy development, and industry practices to fortify the foundation of a responsible, secure, and privacy-conscious IoT.

II. LITERATURE REVIEW

The literature surrounding privacy, data protection, and security concerns in the Internet of Things (IoT) offers valuable insights into the multifaceted challenges and evolving landscape of interconnected devices. Researchers have extensively explored the intricate relationship between the proliferation of IoT technologies and the imperative to safeguard user privacy. Studies emphasize the vulnerability of IoT ecosystems to security breaches, emphasizing the need for robust authentication mechanisms, secure communication protocols, and the implementation of encryption to protect sensitive data. Furthermore, the literature delves into the ethical considerations of data collection, emphasizing the importance of transparency, user consent, and the responsible use of IoT-generated information. Regulatory frameworks, such as the General Data Protection Regulation (GDPR), are frequently examined as crucial drivers shaping data protection practices in IoT. Scholars also discuss the role of emerging technologies, including blockchain and edge computing, in addressing security and privacy challenges. The synthesis of literature underscores the dynamic nature of IoT's privacy and security landscape, highlighting the ongoing need for research, collaboration, and adaptive measures to ensure a trustworthy and resilient IoT ecosystem.

III. METHODOLOGY

The methodology adopted for this survey paper involved a meticulous and systematic approach to gather, assess, and synthesize information pertaining to Internet of Things (IoT) privacy, data protection, and security concerns. To identify relevant literature, extensive searches were conducted on reputable academic databases, including IEEE Xplore, PubMed, and Google Scholar. The selection criteria encompassed the years 2010 to 2023, with a focus on recent developments in the rapidly evolving field of IoT. Peer-reviewed articles, conference papers, and scholarly publications that specifically addressed IoT architecture, privacy challenges, data protection practices, security vulnerabilities, regulatory frameworks, case studies, and mitigation strategies were included.

The data collection process involved the extraction of key findings and relevant information from the selected sources. Thematic analysis was employed as the primary analytical framework, identifying recurring themes and patterns across the literature. Thematic categories were aligned with distinct aspects of IoT privacy, data protection, and security concerns, allowing for a nuanced exploration of the interconnected challenges within the IoT ecosystem.

Quality assessment was a critical component of the methodology, wherein a critical appraisal of each selected source was conducted to evaluate the reliability and validity of the information. Factors such as research rigor, sample sizes, and the reputability of publishing sources were considered during this process. The inclusion of diverse perspectives was ensured by incorporating a mix of academic research, industry reports, and regulatory documents.

An iterative review process was employed to refine the methodology based on emerging insights and gaps identified during the literature review. Feedback from peers and subject matter experts played a pivotal role in enhancing the robustness of the survey methodology. Ethical considerations were paramount throughout the research process, with a commitment to proper attribution to original authors and sources, as well as transparency in reporting the methodology to enable readers to assess the reliability of the survey findings. Despite the meticulous approach, it is important to acknowledge certain limitations inherent in the scope of the survey. The dynamic nature of the IoT landscape may result in new developments after the literature cutoff date (January 2023), and the survey primarily focused on sources available in English, introducing potential language bias. These considerations provide a transparent framework for understanding the methodology employed in conducting this survey on IoT privacy, data protection, and security concerns.

IV. PRIVACY CONCERNS IN IOT

1. Privacy Concerns in IoT: The exponential growth of Internet of Things (IoT) devices has ushered in unprecedented levels of connectivity, convenience, and efficiency. However, this proliferation has also given rise to profound concerns regarding the privacy of individuals, as IoT devices constantly collect, process, and transmit vast amounts of personal data. This section delves into the intricate privacy challenges embedded in the IoT ecosystem, addressing issues such as continuous data collection, tracking mechanisms, and the potential for unauthorized surveillance.
2. Continuous Data Collection: One of the primary privacy concerns in IoT revolves around the continuous and often indiscriminate collection of data by connected devices. Sensors embedded in smart home devices, wearables, and industrial IoT systems routinely gather information about user behaviors, preferences, and environmental conditions. This constant data stream raises questions about the necessity of such extensive data collection, the purposes for which the data is used, and the implications for individual privacy.
3. Tracking Mechanisms and Profiling: IoT devices often employ sophisticated tracking mechanisms, monitoring users' activities and locations in real-time. This capability, while enabling personalized services and contextual awareness, raises significant privacy implications. Users may unknowingly become subjects of extensive profiling, with their habits, routines, and even physical locations being meticulously documented. The challenge lies in striking a balance between the utility of personalized services and the preservation of user privacy.
4. Unauthorized Surveillance and Data Misuse: The interconnected nature of IoT devices introduces the risk of unauthorized surveillance, where malicious actors may exploit vulnerabilities in devices to gain access to sensitive information. Unauthorized access not only compromises individual privacy but also poses broader security risks. Instances of data misuse, ranging from identity theft to manipulation of personal information for malicious purposes, underscore the need for robust security measures to protect against unauthorized intrusions.
5. Challenges in User Consent: Obtaining meaningful and informed consent from users for data collection and processing in the IoT ecosystem presents a considerable challenge. The complex and often opaque terms of service agreements, coupled with the sheer volume of data generated by interconnected devices, make it difficult for users to comprehend the full extent of data collection. Addressing this challenge involves developing transparent mechanisms for obtaining consent and empowering users to make informed decisions about their privacy.
6. Impact on Trust and Adoption: Privacy concerns in IoT have broader implications for the trust users place in these technologies. High-profile incidents of data breaches and privacy lapses erode user confidence, potentially hindering the widespread adoption of IoT solutions. Building and maintaining trust necessitate a proactive approach to addressing privacy concerns, encompassing both technical safeguards and clear communication of privacy practices to users.

In navigating the intricate landscape of privacy concerns in IoT, finding a delicate equilibrium between the benefits of interconnected devices and the preservation of individual privacy becomes paramount. Future developments in IoT should prioritize privacy-enhancing technologies, robust security measures, and user-centric approaches to data collection and processing. The ongoing discourse on privacy in IoT serves as a foundation for developing ethical and responsible practices that align with the evolving expectations of users in an increasingly connected world.

V. DATA PROTECTION IN IOT

The interconnected nature of the Internet of Things (IoT) presents a complex landscape for ensuring the protection of sensitive data. As IoT devices collect, process, and transmit vast amounts of information, safeguarding data integrity, confidentiality, and availability becomes imperative. This section explores the intricacies of data protection in the IoT ecosystem, addressing challenges, regulatory influences, and the role of emerging technologies.

1. Data Collection and Processing Challenges: IoT devices operate by collecting and processing diverse datasets, ranging from environmental conditions to personal health information. The sheer volume and diversity of data pose challenges for ensuring comprehensive data protection. Questions arise about the necessity of certain data points, the duration of   data retention, and the secure handling of information throughout its lifecycle.

2. Confidentiality and Encryption: Preserving the confidentiality of data is a cornerstone of data protection in IoT. Encryption mechanisms play a pivotal role in securing the communication channels between devices and data repositories. Ensuring end-to-end encryption helps mitigate the risks associated with data interception, unauthorized access, and the potential compromise of sensitive information.

3. Integrity and Secure Data Transmission: Maintaining data integrity is essential to prevent unauthorized alterations or tampering. Secure data transmission protocols, such as secure sockets layer (SSL) and transport layer security (TLS), are crucial for ensuring that data remains unaltered during transit. The integrity of data is particularly critical in contexts where inaccuracies could lead to severe consequences, such as in healthcare or industrial settings.

VI. SECURITY CHALLENGES AND SOLUTIONS

The rapid proliferation of Internet of Things (IoT) devices has ushered in an era of unprecedented connectivity and convenience. However, this interconnected landscape also introduces a host of security challenges, ranging from device vulnerabilities to potential threats against critical infrastructure. This section explores the key security challenges in IoT and outlines proactive solutions to fortify the ecosystem against evolving threats.

A. Device Vulnerabilities

One of the primary security challenges in IoT stems from vulnerabilities inherent in connected devices. IoT devices, often constrained by resource limitations, may lack robust security features, making them susceptible to exploitation. Common vulnerabilities include weak authentication mechanisms, insecure firmware, and a lack of timely security updates.

Solution: Implementing security-by-design principles is paramount in addressing device vulnerabilities. This involves incorporating robust authentication protocols, regularly updating device firmware to patch known vulnerabilities, and adopting secure coding practices during the development phase. Additionally, establishing industry-wide standards for secure IoT device development can contribute to a more resilient ecosystem.

B. Unauthorized Access and Identity Management

The interconnected nature of IoT poses risks of unauthorized access to devices and networks. Inadequate identity management mechanisms can lead to unauthorized individuals gaining control over devices, potentially compromising sensitive data or causing disruptions in device functionality.

Solution: Implementing strong identity management practices, including secure authentication and access control mechanisms, is essential. Utilizing multi-factor authentication, biometrics, and encryption for identity verification enhances the security posture of IoT devices. Regularly reviewing and updating access control policies ensures that only authorized entities can interact with IoT devices and their associated data.

C. Data Integrity and Privacy Concerns

Ensuring the integrity of data transmitted and processed by IoT devices is crucial for maintaining user trust and preventing malicious manipulations. Privacy concerns arise when sensitive data is inadequately protected, leading to potential unauthorized access or data breaches.

Solution: Employing end-to-end encryption for data transmission and storage safeguards data integrity and protects user privacy. Privacy-enhancing technologies, such as differential privacy and homomorphic encryption, can be integrated to minimize the risk of data exposure while still allowing for valuable insights to be derived.

D. Distributed Denial of Service (DDoS) Attacks

The interconnected nature of IoT devices creates a vast attack surface that can be exploited for large-scale Distributed Denial of Service (DDoS) attacks. Attackers may compromise numerous devices to overwhelm targeted networks, leading to service disruptions and potential cascading effects.

Solution: Implementing robust network security measures, including intrusion detection and prevention systems, can mitigate the impact of DDoS attacks. Additionally, manufacturers and operators should prioritize securing device communication protocols and implement rate limiting to detect and prevent anomalous patterns indicative of potential DDoS attempts.

E. Lack of Standardization and Interoperability

The absence of standardized security practices and interoperability among diverse IoT devices contributes to security challenges. Heterogeneous ecosystems make it challenging to enforce consistent security measures across devices from different manufacturers.

Solution: Establishing industry-wide security standards and promoting interoperability frameworks is essential for creating a cohesive and secure IoT ecosystem. Collaboration between stakeholders, including manufacturers, regulatory bodies, and cybersecurity experts, can facilitate the development and adoption of standardized security practices.

VII. CASE STUDIES

Certainly, here are a few additional case studies that shed light on various aspects of IoT, including privacy, data protection, and security concerns:

A. Ring Doorbell Data Sharing Controversy (2019)

1. Incident Overview: Ring, a popular smart doorbell manufacturer, faced scrutiny in 2019 when reports revealed its data-sharing practices with third-party entities, including law enforcement agencies. Concerns were raised about user consent, the extent of data shared, and the potential impact on individual privacy.
2. Lessons Learned: The Ring case underscores the importance of transparent data-sharing practices and user consent in IoT. Manufacturers should provide clear information to users about data-sharing arrangements and enable granular control over their data. Policymakers may need to establish guidelines to ensure responsible data-sharing practices in the IoT ecosystem.

B. IoT-based Ransomware Attack on a Smart Thermostat (2017)

1. Incident Overview: In 2017, researchers demonstrated a proof-of-concept ransomware attack on an IoT-enabled smart thermostat. The attack exploited vulnerabilities in the device's firmware, encrypting the thermostat's controls and demanding a ransom for restoration. While a controlled experiment, it highlighted the potential risks of ransomware in the IoT space.
2. Lessons Learned: This case emphasizes the importance of securing firmware in IoT devices and the need for manufacturers to implement security patches promptly. Regular security audits, secure coding practices, and the ability to update device firmware are crucial in mitigating the risk of ransomware attacks on IoT devices.

C. Amazon Alexa Voice Data Privacy Concerns (2019)

1. Incident Overview: Reports emerged in 2019 revealing that Amazon's Alexa voice assistant stored and retained audio recordings of users' interactions, raising concerns about privacy and data protection. Users expressed unease about the extent of data collection and the potential exposure of sensitive conversations.
2. Lessons Learned: The Amazon Alexa case highlights the importance of transparent data handling practices in voice-enabled IoT devices. Manufacturers should provide clear privacy policies, robust data anonymization practices, and mechanisms for users to manage and delete their voice recordings. Striking a balance between functionality and privacy is crucial in voice-activated IoT systems.

D. Smart City Surveillance Cameras (Various Incidents)

1. Incident Overview: Several instances globally have raised concerns about the deployment of smart city surveillance cameras with facial recognition technology. Privacy advocates have expressed worries about mass surveillance, potential misuse of collected data, and the lack of clear regulations governing the use of such technologies.
2. Lessons Learned: Deploying surveillance technologies in smart cities requires careful consideration of privacy implications. Policymakers must establish clear regulations governing the use of surveillance tools, ensuring transparency, accountability, and safeguards against potential misuse. Public discourse and stakeholder engagement are crucial in shaping responsible smart city initiatives.

VIII. MITIGATION STRATEGIES

Effectively addressing the security and privacy challenges within the Internet of Things (IoT) ecosystem requires a comprehensive approach. The following mitigation strategies encompass technical, policy, and user-centric measures to enhance the resilience of IoT devices and systems:

A. Security by Design

1. Implementation: Integrate security measures into the design and development phases of IoT devices and systems.
2. Focus Areas: Prioritize secure coding practices, authentication mechanisms, and encryption protocols to establish a robust security foundation.

B. Regular Security Updates

1. Implementation: Establish mechanisms for timely and automated security updates for IoT devices.
2. Importance: Regular updates patch vulnerabilities, addressing emerging threats and enhancing the overall security posture of connected devices.

C. User Education and Awareness

1. Education Initiatives: Develop educational programs for users, emphasizing the importance of secure device configurations and privacy settings.
2. Empowerment: Informed users are better equipped to make privacy-conscious decisions, contributing to a more secure IoT environment.

D. Authentication and Access Control

1. Strong Authentication: Implement multi-factor authentication and biometric verification for user and device authentication.
2. Access Control: Define and enforce granular access control policies to restrict unauthorized access to IoT devices and data.

E. Encryption for Data Transmission and Storage

1. End-to-End Encryption: Employ end-to-end encryption mechanisms for data transmitted between IoT devices and storage.
2. Data-at-Rest Encryption: Securely encrypt stored data on devices and in cloud repositories to prevent unauthorized access.

F. Privacy-Enhancing Technologies

1. Differential Privacy: Implement differential privacy mechanisms to protect individual privacy while still enabling valuable data analysis.
2. Homomorphic Encryption: Explore the use of homomorphic encryption to perform computations on encrypted data without revealing the underlying information.

G. Secure Network Communication Protocols

1. Secure Protocols: Use secure communication protocols such as SSL/TLS for data transmission between IoT devices and backend systems.
2. Network Segmentation: Employ network segmentation to isolate critical systems and minimize the potential impact of security incidents.

H. Regulatory Compliance and Standards

1. Compliance: Adhere to relevant data protection regulations, such as GDPR, and industry-specific standards for IoT security.
2. Industry Collaboration: Engage with industry groups to establish and promote security standards that enhance the overall security of IoT ecosystems.

I. Supply Chain Security Practices

1. Vendor Assessment: Conduct thorough security assessments of IoT device vendors and suppliers.
2. Secure Development Guidelines: Encourage adherence to secure development guidelines and supply chain transparency to mitigate potential vulnerabilities introduced during the manufacturing process.

J. Incident Response and Threat Intelligence

1. Preparedness: Develop and regularly update incident response plans to address security incidents promptly.
2. Threat Intelligence: Stay informed about emerging threats through threat intelligence feeds, enabling proactive mitigation measures.

K. Edge Computing for Localized Processing

1. Edge Devices: Leverage edge computing to process data locally on devices, reducing reliance on centralized cloud platforms.
2. Data Minimization: Implement data minimization strategies to collect only essential information, minimizing the potential impact of data breaches.

L. Collaboration and Information Sharing

1. Community Engagement: Foster collaboration within the IoT community for sharing threat intelligence, best practices, and lessons learned.
2. Industry Partnerships: Establish partnerships between manufacturers, regulators, and cybersecurity experts to collectively address evolving security challenges.

These mitigation strategies collectively contribute to building a more resilient and secure IoT ecosystem. The adoption of these measures requires collaboration among manufacturers, policymakers, and end-users to create a sustainable framework that prioritizes privacy, data protection, and overall security.

IX. FUTURE TRENDS AND CHALLENGES

The Internet of Things (IoT) is poised for significant developments in the coming years, bringing both opportunities and challenges. Here are some anticipated future trends and challenges in the IoT landscape:

A. AI and Machine Learning Integration

1. Trend: Increased integration of artificial intelligence (AI) and machine learning (ML) into IoT systems.
2. Impact: Enhanced data analytics, predictive capabilities, and autonomous decision-making in real-time.
3. Challenge: Addressing the ethical implications of AI, ensuring transparency, and managing the complexity of AI-driven IoT ecosystems.

B. 5G Network Expansion

1. Trend: Widespread adoption and expansion of 5G networks to support the growing number of connected devices.
2. Impact: Higher data transfer speeds, lower latency, and improved connectivity for IoT applications.
3. Challenge: Ensuring robust security in 5G networks, addressing potential privacy concerns, and managing the infrastructure upgrade.

C. Edge and Fog Computing Growth

1. Trend: Increasing use of edge and fog computing for decentralized data processing.
2. Impact: Reduced latency, improved data privacy, and efficient use of network resources.
3. Challenge: Standardizing edge computing protocols, addressing security concerns, and managing the complexity of distributed computing.

D. Blockchain for Enhanced Security

1. Trend: Growing adoption of blockchain technology to enhance the security of IoT networks and transactions.
2. Impact: Improved data integrity, secure device authentication, and decentralized trust mechanisms.
3. Challenge: Overcoming scalability issues, integrating blockchain with existing IoT systems, and addressing regulatory concerns.

E. IoT Interoperability Standards

1. Trend: Development and adoption of standardized protocols for improved interoperability.
2. Impact: Seamless communication between diverse IoT devices and platforms.
3. Challenge: Achieving global consensus on standards, ensuring backward compatibility, and addressing the heterogeneity of IoT ecosystems.

F. Autonomous IoT Devices

1. Trend: Advancements in autonomous IoT devices capable of self-configuration, self-optimization, and self-healing.
2. Impact: Reduced maintenance efforts, improved reliability, and increased efficiency.
3. Challenge: Ensuring the security of autonomous systems, addressing ethical concerns, and managing the complexity of self-managing devices.

G. Sustainable IoT Solutions

1. Trend: Growing emphasis on sustainable and eco-friendly IoT solutions.
2. Impact: Reduced environmental footprint, energy-efficient devices, and responsible manufacturing practices.
3. Challenge: Balancing sustainability with technological advancements, addressing electronic waste concerns, and establishing industry-wide sustainability standards.

H. Privacy-Preserving Technologies

1. Trend: Increased focus on privacy-preserving technologies to address growing privacy concerns.
2. Impact: Enhanced user privacy, transparent data handling practices, and compliance with evolving privacy regulations.
3. Challenge: Balancing data utility with privacy preservation, building user trust, and adapting to changing privacy expectations.

I. Human Augmentation and IoT

1. Trend: Integration of IoT devices in human augmentation technologies and wearables.
2. Impact: Advancements in healthcare, personalized services, and improved human-machine interactions.
3. Challenge: Ensuring the security of sensitive health data, addressing ethical considerations, and developing standards for wearable device security.

J. Regulatory and Ethical Frameworks

1. Trend: Continued development and refinement of regulatory and ethical frameworks for IoT.
2. Impact: Clear guidelines for manufacturers, improved user protections, and establishment of international standards.
3. Challenge: Achieving global consensus on regulations, keeping pace with technological advancements, and balancing innovation with regulatory compliance.

Navigating these trends and challenges will require collaboration among industry stakeholders, policymakers, and researchers. As IoT continues to shape the future of technology, a proactive and adaptive approach will be crucial to harness its potential responsibly.

Conclusion

In conclusion, the Internet of Things (IoT) represents a paradigm shift in the way we interact with technology, offering unprecedented connectivity and convenience. However, this transformative landscape is not without its challenges. Privacy concerns, data protection issues, and security vulnerabilities underscore the need for a proactive and adaptive approach to ensure the responsible evolution of IoT. As the volume of interconnected devices continues to grow, the central role of privacy and the imperative of robust data protection practices become increasingly evident. Embracing a security-by-design philosophy, anticipating future trends, and fostering collaboration among stakeholders are essential components of a sustainable IoT ecosystem. The empowerment of users through education and transparent practices is critical for cultivating a privacy-conscious culture. As we navigate the complexities of IoT, it is imperative to strike a delicate balance between technological innovation and ethical considerations to harness its full potential while safeguarding individual privacy and ensuring a secure connected future.

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Copyright

Copyright © 2023 Sakshi Rai, Ujawal Rai, Chetan Randhye, Achal Amrutkar, Prof. Manisha More. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.