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particularly suited for complex and dynamic 
environments such as IoT (Internet of Things).
The key components of ABAC include: 
1. Attributes: Attributes are characteristics or 
properties associated with subjects, objects, and the 
environment. They can include user roles, device 
properties, user location, time of access, or any other 
relevant information. Attributes provide contextual 
information for making access control decisions. 
2. Policies: ABAC policies define the rules and 
conditions that determine whether access should be 
granted or denied based on the attributes. Policies are 
typically expressed in the form of policy statements or 
rules, specifying the combination of attributes and 
their values required for access. 

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3. Policy Decision Point (PDP): The PDP is 
responsible for evaluating the policies and making 
access control decisions. It receives attribute 
information 
about 
the 
subject, 
object, 
and 
environment, compares it against the defined policies, 
and determines whether access should be allowed or 
denied. 
4. Policy Enforcement Point (PEP): The PEP enforces 
the access control decisions made by the PDP. It is 
responsible 
for 
intercepting 
access 
requests, 
forwarding them to the PDP for evaluation, and 
enforcing the resulting access control decisions by 
either granting or denying access. 
5. Policy Information Point (PIP): The PIP serves as a 
source of attribute information for the PDP. It 
retrieves attribute values from various sources, such as 
user directories, databases, or external systems, and 
provides them to the PDP for policy evaluation. 
ABAC offers several benefits: 
1. Flexibility and Granularity: ABAC provides fine-
grained access control by considering multiple 
attributes in access decisions. It allows for more 
precise control over who can access which resources 
based on specific attributes, providing greater 
flexibility in defining access policies. 
2. Context-Aware Access Control: ABAC takes into 
account the contextual information of the access 
request, such as user roles, device properties, or 
environmental conditions. This enables dynamic 
access control decisions based on the current context, 
making it well-suited for dynamic environments like 
IoT. 
3. Scalability: ABAC is highly scalable as it can 
accommodate a large number of attributes and 
policies. It can handle complex access control 
requirements in large-scale IoT deployments with 
numerous devices, users, and resources. 
4. Policy Reusability: ABAC allows for the reuse of 
policies across different resources and scenarios. 
Policies can be defined once and applied to multiple 
resources or contexts, simplifying policy management 
and reducing duplication. 
5. Compliance and Auditing: ABAC enables 
organizations to enforce access control policies that 
align with regulatory requirements and industry 
standards. It facilitates auditing and compliance 
monitoring by providing a detailed record of the 
attributes and policies involved in access decisions. 
ABAC is a powerful access control model that offers 
flexibility, 
granularity, 
and 
context-awareness, 
making it well-suited for IoT environments with 
diverse devices, users, and dynamic access 
requirements. It enables organizations to implement 
robust and adaptable access control mechanisms to 
protect resources and sensitive data in IoT ecosystems 
4. Literature Review
C.Q et.al [2022] focus on the structural design and 
material selection of the optoelectronic composite 
cable for HDMI data transmission, and compare the 
task-based and message-based bus modes under the 
concurrent system, and determine the message-based 
soft bus mode. (Chord)’s application service location 
strategy, which solves the search problem under the 
irregular distribution of services in large-scale 
distributed networks[13] 
P. Assumpção et.al[2022] proposes the thoughtful 
employment of cloud computing resources to address 
the 
abovementioned 
problems, 
applying 
microservices and cloud computing for validating 
blockchain security and monitoring the protection of 
physical environments. Our contributions focus on 
two main aspects: a microservices-based architecture 
to deal with data receiving, analysis, and storage 
while enhancing availability; and the integration of 
blockchains as a security mechanism to verify data 
integrity and authenticity using smart contracts. 
Moreover, our proposal also discusses the challenges 
involving blockchains in a Big Data scenario and 
appropriate mechanisms to deal with scalability and 
performance constraints. Finally, we present a 

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complete implementation of our architecture using 
the AWS cloud environment and Hyperledger Fabric 
platform. Our tests demonstrate how microservices 
can help increase blockchain throughput. We argue 
that our architecture proposal and its implementation 
constitute a suitable solution for modern monitoring 
systems and serve as a reference model for future 
works.[14] 
Ifran et.al [2022] proposed system can detect the 
changes of water level, rainfall intensity and the 
system also can predict when flooding will occur. 
With the support of IoT technology, the system can 
send an information about water level and rainfall 
data to mobile phones installed with AWS 
applications. In this study, the communication system 
was designed into two parts, namely the sender 
module and the receiver module. In the sender 
module we used the programmable Atmega328P 
microcontroller for processing the data from the JSN-
SR04. This sensor will read into water level values and 
rainfall sensors into rainfall intensity values, then the 
data will be sent to the receiving module using the 
Long Range (LoRa) module. In the receiver module 
using the programmable ESP32 microcontroller, the 
microcontroller and LoRa in this module will process 
the data that has been sent by the sending module and 
classified into flood levels and precipitation levels and 
then the data is sent to the AWS application installed 
on the mobile phone. In addition, in this receiver 
module there is an OLED that functions to display 
data, relays and sirens to provide warnings in the 
form of sounds when the flood level or water level is 
at level 3. Based on the results of implementation and 
testing at the ciyasana dam, data on flood and rainfall 
levels are at level 1 by following the provisions in the 
ciyasana dam.[15] 
Black soldier fly larvae (BSFL) is an emerging insect-
based waste management agent as it provides effective 
biowaste conversion. Though effective, it requires 
certain environmental conditions that needs to be 
monitored regularly to make sure the BSFL can 
process the waste effectively. But, BSFL farmers are 
not always on site and the human resource is limited. 
Thus, remote monitoring system is needed to ease the 
monitoring process. By using the Internet of Things 
(IoT) for environmental condition monitoring, data 
collection from the sensors needs to be obtained in 
real-time. To do so, a scalable IoT messaging protocol 
called Message Queuing Telemetry Tracking (MQTT) 
for the data communication is implemented. As the 
data will continuously be sent, a cloud server using 
Amazon Web Service Elastic Computing 2 (AWS EC2) 
virtual instance will be used to build the MQTT 
Broker and to run the data processing program that 
will processed the data before it is saved to a MySQL 
database. Using this system, data from the sensors 
located on the farm is successfully sent to the MQTT 
broker, and the saved data in database is showing the 
same result as the sent data. It was also found that the 
average delay for data transmission is 0.8125 seconds. 
Thus, the proposed system has successfully perform 
real time data communication using the MQTT 
protocol for BSFL monitoring system.[16] 
S. Ameer et .al [2022] used two approaches to develop 
two different hybrid models for smart home IoT. We 
followed a role-centric approach and an attribute-
centric approach to develop HyBAC$_{RC}$ and 
HyBAC$_{AC}$, respectively. We formally define 
these models and illustrate their features through a 
use case scenario demonstration. We further provide a 
proof-of-concept implementation for each model in 
Amazon Web Services (AWS) IoT platform. Finally, 
we conduct a theoretical comparison between the two 
models proposed in this paper in addition to the 
EGRBAC model (RBAC model for smart home IoT) 
and HABAC model (ABAC model for smart home 
IoT), which were previously developed to meet smart 
homes' challenges.[17] [18] 
5. Future Directions and Research Challenges: 

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Future directions and research challenges in 
Attribute-Based Access Control (ABAC) revolve 
around enhancing its capabilities, addressing 
emerging needs, and overcoming existing limitations. 
Here are some key areas of focus: 
1. Scalability: As IoT and cloud computing continue 
to expand, ABAC systems need to handle large-scale 
deployments efficiently. Research efforts are aimed at 
developing scalable architectures, algorithms, and 
technologies that can support the growing number of 
devices, 
users, 
and 
resources 
in 
ABAC 
environments[19] . 
2. Interoperability: ABAC systems often need to 
interact with different platforms, services, and 
technologies. Achieving interoperability between 
ABAC solutions and other access control models (such 
as role-based access control or attribute-based access 
control) is a research challenge. Standardization 
efforts and the development of common frameworks 
and protocols can facilitate interoperability. 
3. Context Awareness: ABAC can benefit from 
increased context awareness to make more informed 
access control decisions. Research focuses on 
integrating contextual information, such as location, 
time, user behavior, or environmental factors, into 
ABAC policies and decision-making processes. 
Context-aware ABAC can provide adaptive and 
dynamic access control in dynamic environments like 
IoT. 
4. Privacy and Consent Management: ABAC involves 
the collection and processing of attributes, which can 
include sensitive information. Research explores 
privacy-preserving 
mechanisms 
and 
consent 
management frameworks to ensure that attribute 
disclosure and usage align with privacy regulations 
and user preferences. Techniques such as attribute 
masking, selective attribute disclosure, and attribute-
based consent management are areas of ongoing 
research[20] . 
5. Trust and Assurance: Ensuring the trustworthiness 
and assurance of ABAC systems is critical. Research 
focuses on developing methods for assessing and 
verifying the correctness, security, and reliability of 
ABAC policies, decision-making processes, and 
enforcement mechanisms. Techniques like formal 
verification, policy analysis, and testing can help 
enhance trust and assurance in ABAC systems. 
6. Dynamic Policy Management: ABAC policies may 
need to be updated dynamically to adapt to changing 
requirements or evolving contexts. Research explores 
techniques for efficient policy management, including 
policy versioning, policy conflict resolution, and 
policy lifecycle management. Dynamic policy 
management mechanisms can facilitate the agility and 
flexibility of ABAC systems. 
7. Usability and User Experience: ABAC should 
provide a user-friendly experience for system 
administrators and end-users. Research efforts focus 
on improving the usability of policy specification and 
management interfaces, policy language readability, 
and user-centric policy administration. User-centered 
design principles and usability studies contribute to 
enhancing the practical adoption of ABAC[21]. 
8. Cross-Domain ABAC: ABAC is increasingly being 
applied in cross-domain scenarios where access 
control policies need to span multiple organizations or 
administrative 
boundaries. 
Research 
explores 
techniques for enabling secure collaboration, policy 
harmonization, and attribute exchange across 
different domains. Cross-domain ABAC frameworks 
and trust models are areas of active research. 
Addressing these research challenges will contribute 
to the advancement and maturation of ABAC, 
enabling its broader adoption in diverse domains, 
including IoT, cloud computing, and enterprise 
systems. The ongoing efforts to enhance scalability, 
interoperability, context awareness, privacy, trust, 
and usability will shape the future of ABAC and its 
ability to meet the evolving access control needs of 
complex and dynamic environments. 
5.1 Emerging Trends in ABAC for IoT –
Emerging trends in Attribute-Based Access Control 
(ABAC) for the Internet of Things (IoT) are driven by 

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the unique characteristics and requirements of IoT 
environments. Here are some notable trends in ABAC 
for IoT:[22] 
1. Edge Computing and ABAC: With the proliferation 
of IoT devices generating massive amounts of data, 
edge computing has gained prominence. ABAC can be 
extended to edge devices, enabling localized access 
control and reducing reliance on centralized systems. 
This trend aims to enhance efficiency, reduce latency, 
and improve resilience in IoT deployments. 
2. Contextual Attribute-Based Access Control 
(CABAC): Context plays a crucial role in IoT 
environments. CABAC extends traditional ABAC by 
incorporating real-time contextual information, such 
as device status, location, environmental conditions, 
and user behavior, into access control decisions. This 
trend enhances the adaptive and dynamic nature of 
access control in IoT. 
3. Blockchain and ABAC Integration: Blockchain 
technology provides decentralized and tamper-
resistant data storage and transaction mechanisms. 
Integrating ABAC with blockchain can enhance the 
security and trustworthiness of access control in IoT 
scenarios. It enables secure attribute exchange, 
auditing, 
and 
provenance 
tracking, 
ensuring 
transparency and integrity in access control decisions. 
4. Privacy-Preserving ABAC: IoT environments often 
involve sensitive data and privacy concerns. Privacy-
preserving ABAC techniques, such as attribute-based 
encryption, secure multi-party computation, and 
differential privacy, are emerging to address privacy 
challenges. These techniques enable secure attribute 
sharing and access control without disclosing sensitive 
information[23]. 
5. Machine Learning and ABAC: Machine learning 
techniques are being employed to enhance access 
control in IoT. Machine learning algorithms can 
analyze large-scale attribute data, identify patterns, 
and make intelligent access control decisions. This 
trend aims to improve the accuracy, efficiency, and 
adaptability of access control in dynamic and complex 
IoT environments. 
6. Threat Intelligence and ABAC: As IoT devices 
become targets for various threats, integrating threat 
intelligence into ABAC becomes crucial. ABAC 
systems can leverage threat intelligence feeds, 
anomaly detection, and risk assessment techniques to 
enhance access control decisions. This trend enables 
proactive protection against emerging threats in IoT 
deployments. 
7. Federated ABAC: In IoT ecosystems involving 
multiple organizations and domains, federated ABAC 
models are emerging. Federated ABAC allows for 
attribute-based trust relationships, attribute exchange, 
and policy interoperability between different 
administrative domains. This trend enables secure and 
controlled collaboration and resource sharing in 
cross-domain IoT scenarios. 
8. Standards and Interoperability: To facilitate the 
adoption and interoperability of ABAC in IoT, 
standardization efforts are underway. Standards 
organizations and industry alliances are working 
towards defining common data models, protocols, and 
interfaces for attribute exchange and policy 
enforcement. 
This 
trend 
aims 
to 
promote 
compatibility and seamless integration between 
ABAC-enabled IoT systems[24] [25] 
These emerging trends reflect the ongoing efforts to 
enhance the effectiveness, efficiency, and security of 
ABAC in IoT environments. They address the unique 
challenges posed by the scale, heterogeneity, and 
dynamic nature of IoT deployments, enabling robust 
and flexible access control mechanisms in the IoT 
ecosystem. 
6. Conclusion: 
In conclusion, Attribute-Based Access Control (ABAC) 
plays a crucial role in securing and managing access to 
resources in the context of the Internet of Things (IoT) 
on the AWS platform. ABAC offers a flexible and 
dynamic access control model that leverages 
attributes associated with users, devices, and resources 
to make access decisions. ABAC for AWS IoT 
provides several benefits, including fine-grained 

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access control, context-aware decision-making, and 
policy-driven authorization. It enables organizations 
to define access policies based on attributes such as 
device type, location, ownership, and user roles, 
allowing for more precise control over IoT resources. 
By adopting ABAC in an AWS IoT environment, 
organizations can enhance security, protect sensitive 
data, and ensure compliance with regulatory 
requirements. ABAC enables organizations to enforce 
access control policies that align with their specific 
business needs and risk tolerance. Furthermore, 
ABAC for AWS IoT offers integration with other 
AWS services such as AWS Identity and Access 
Management (IAM) and AWS IoT Core, providing a 
comprehensive access control framework for IoT 
deployments. This integration enables organizations 
to leverage the full potential of the AWS ecosystem 
while maintaining granular control over access to IoT 
resources. As the IoT landscape continues to evolve 
and expand, ABAC for AWS IoT is likely to play a 
crucial role in ensuring secure and efficient access 
management. The ongoing advancements in ABAC 
technologies, interoperability standards, and industry 
initiatives will further enhance the capabilities and 
adoption of ABAC in the context of AWS IoT. In 
conclusion, ABAC for AWS IoT offers a powerful 
access control solution that addresses the unique 
challenges 
of 
IoT 
environments, 
providing 
organizations with a robust framework to secure their 
IoT deployments on the AWS platform.
II.
REFERENCES 
[1]
R. Mishra, R. Mishra and R. Shukla, 
"Development of Cloud Centric Healthcare 
Monitoring System For Cardiac Patients 
embedded in IoT Platform," 2023 11th 
International Conference on Emerging Trends 
in Engineering & Technology - Signal and 
Information Processing (ICETET - SIP), Nagpur, 
India, 2023, pp. 1-6. doi: 10.1109/ICETET 
SIP58143.2023.10151587 
[2]
A. Gupta, N. Dhanda and K. K. Gupta, "Ingest 
and Visualize CSV Files using AWS Platform 
For Transition from Unstructured to Structured 
Data," 2023 11th International Conference on 
Emerging Trends in Engineering & Technology 
- Signal and Information Processing (ICETET - 
SIP), Nagpur, India, 2023, pp. 1-6. doi: 
10.1109/ICETET-SIP58143.2023.10151634 
[3]
N. Ivanovic, B. Nast, A. Reiz and K. Sandkuhl, 
"Technologies for a Diagnostic Technique for 
HVAC Systems Using IoT and Cloud-Based 
Architecture," 
2023 
International 
Interdisciplinary PhD Workshop (IIPhDW), 
Wismar, Germany, 2023, pp. 1-6. doi: 
10.1109/IIPhDW54739.2023.10124398 
[4]
B. S. Jebaraj, S. Sekar, S. S, P. S, J. Yu and G. T, 
"IoT-based Automatic LPG Refilling and 
Leakage Detection System," 2023 International 
Conference on Innovative Data Communication 
Technologies 
and 
Application 
(ICIDCA), 
Uttarakhand, India, 2023, pp. 858-862. doi: 
10.1109/ICIDCA56705.2023.10099790 
[5]
H. Singh and S. K. Mand, "Difficulties and 
Potential 
Ulnerabilities 
in 
the 
IOT 
Architecture," 2023 International Conference 
on 
Artificial 
Intelligence 
and 
Smart 
Communication (AISC), Greater Noida, India, 
2023, 
pp. 
374-377. 
doi: 
10.1109/AISC56616.2023.10085640 
[6]
D. D. N. Nguyen, K. Sood, Y. Xiang, L. Gao, L. 
Chi and S. Yu, "Towards IoT Node 
Authentication Mechanism in Next Generation 
Networks," in IEEE Internet of Things Journal 
doi: 10.1109/JIOT.2023.3262822 
[7]
J. A. Beltran, P. Mudholkar, M. Mudholkar, V. 
Tripathi, C. Valderrama-Zapata and M. 
Lourense, "Security Issues and Challenges in 
Internet of Things (IoT) System," 2022 5th 
International Conference on Contemporary 
Computing and Informatics (IC3I), Uttar 
Pradesh, 
India, 
2022, 
pp. 
57-60 
doi: 
10.1109/IC3I56241.2022.10072600 

---

International Journal of Scientific Research in Science and Technology (www.ijsrst.com) | Volume 10 | Issue 3 
Pragya Bharti et al Int J Sci Res Sci & Technol. May-June-2023, 10 (3) : 995-1009 
1008 
[8]
L. Praharaj, S. Ameer, M. Gupta and R. Sandhu, 
"Attributes Aware Relationship-based Access 
Control for Smart IoT Systems," 2022 IEEE 8th 
International Conference on Collaboration and 
Internet Computing (CIC), Atlanta, GA, USA, 
2022, 
pp. 
72-81. 
doi: 
10.1109/CIC56439.2022.00021 
[9]
L. Raju, V. Gurunath, R. Darran and S. V, "IOT 
based Energy Management System using STM32 
and AWS IOT," 2022 IEEE 2nd International 
Symposium on Sustainable Energy, Signal 
Processing and Cyber Security (iSSSC), 
Gunupur, Odisha, India, 2022, pp. 1-5. doi: 
10.1109/iSSSC56467.2022.10051258 
[10]
S. Hanumanthakari, S. K. Pullela, S. N. Bhukya, 
K. Vijayalakshmi, S. R. Ahmad and N. Kumar, 
"IoT based Patients Monitoring System in 
Healthcare 
Service," 
2022 
International 
Conference on Automation, Computing and 
Renewable Systems (ICACRS), Pudukkottai, 
India, 
2022, 
pp. 
1324-1329. 
doi: 
10.1109/ICACRS55517.2022.10029295 
[11]
A. A. B. Amarasinghe G, G. M. H. Gamagedara 
S, P. K.K, H. D. A. Subawickrama E, K. Y. 
Abeywardena and K. Yapa, "SUPPLYDECK – A 
Blockchain-Based Pharmaceutical Supply Chain 
Management," 
2022 
4th 
International 
Conference on Advancements in Computing 
(ICAC), Colombo, Sri Lanka, 2022, pp. 84-89. 
doi: 10.1109/ICAC57685.2022.10025093 
[12]
D. Pérez, M. Rivera, F. Fuentes-Peñailillo, A. 
Díaz, R. Pérez and J. Villar, "Traceability System 
for an Agricultural Supply Network based on 
Blockchain," 
2022 
IEEE 
International 
Conference on Automation/XXV Congress of 
the Chilean Association of Automatic Control 
(ICA-ACCA), Curicó, Chile, 2022, pp. 1-6. doi: 
10.1109/ICA-ACCA56767.2022.10006240 
[13]
C. Qu, "Realization of the Network Distributed 
Platform AWS System in the Transmission 
Structure Assistance Technology," 2022 Sixth 
International Conference on I-SMAC (IoT in 
Social, Mobile, Analytics and Cloud) (I-SMAC), 
Dharan, Nepal, 2022, pp. 279-282. doi: 
10.1109/I-SMAC55078.2022.9987338 
[14]
P. Assumpção, C. Oliveira, P. Ortiz, W. Melo 
and L. Carmo, "A Secure Cloud-based 
Architecture for monitoring Cyber-Physical 
Critical Infrastructures," 2022 6th Cyber 
Security in Networking Conference (CSNet), 
Rio de Janeiro, Brazil, 2022, pp. 1-7. doi: 
10.1109/CSNet56116.2022.9955607 
[15]
Irfan, R. Mardiati and M. R. Effendi, "Early 
Warning System of Flood Disaster Using JSN-
SR04 and Rainfall Sensor Based on Internet of 
Things," 2022 8th International Conference on 
Wireless and Telematics (ICWT), Yogyakarta, 
Indonesia, 
2022, 
pp. 
1-7. 
doi: 
10.1109/ICWT55831.2022.9935139 
[16]
S. A. Tsaabitah, M. O. Hasanuddin, K. H. 
Burhan, A. D. Permana and W. Trusaji, "Data 
Communication using MQTT for Black Soldier 
Fly Larvae Monitoring System," 2022 8th 
International Conference on Wireless and 
Telematics (ICWT), Yogyakarta, Indonesia, 
2022, 
pp. 
1-5. 
doi: 
10.1109/ICWT55831.2022.9935472 
[17]
E. J. Mohamad et al., "Smart Farming IoT Based 
Management during Post Covid-19," 2022 2nd 
International Conference on Emerging Smart 
Technologies and Applications (eSmarTA), Ibb, 
Yemen, 
2022, 
pp. 
1-7. 
doi: 
10.1109/eSmarTA56775.2022.9935480 
[18]
S. Ameer, J. Benson and R. sandhu, "Hybrid 
Approaches (ABAC and RBAC) Toward Secure 
Access Control in Smart Home IoT," in IEEE 
Transactions on Dependable and Secure 
Computing, 
2022. 
doi: 
10.1109/TDSC.2022.3216297 
[19]
E. Drutter, M. Miličević, A. K. Skelin and M. 
Bonković, "Augmented Reality Based Sensor 
Data 
Visualization 
for 
Plant 
Growth 
Monitoring," 2022 International Conference on 
Software, Telecommunications and Computer 

---

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1009 
Networks (SoftCOM), Split, Croatia, 2022, pp. 
1-7.doi: 10.23919/SoftCOM55329.2022.9911471 
[20]
K. Zen, S. Mohanan, S. Tarmizi, N. Annuar and 
N. U. Sama, "Latency Analysis of Cloud 
Infrastructure for Time-Critical IoT Use Cases," 
2022 
Applied 
Informatics 
International 
Conference (AiIC), Serdang, Malaysia, 2022, pp. 
111-116. doi: 10.1109/AiIC54368.2022.9914601 
[21]
S. Vaddadi, V. Srinivas, N. A. Reddy, G. H, R. D 
and 
A. 
Devipriya, 
"Factory 
Inventory 
Automation using Industry 4.0 Technologies," 
2022 IEEE IAS Global Conference on Emerging 
Technologies (GlobConET), Arad, Romania, 
2022, 
pp. 
734-738. 
doi: 
10.1109/GlobConET53749.2022.9872416 
[22]
A. Azizan, N. M. Din, D. R. M. Dzaki, A. D. I. A. 
Kadir and N. Shafie, "Implementation of an IoT 
Cloud-based Elderly Care Health Monitoring 
Dashboard," 2022 4th International Conference 
on Smart Sensors and Application (ICSSA), 
Kuala Lumpur, Malaysia, 2022, pp. 150-154. doi: 
10.1109/ICSSA54161.2022.9870939 
[23]
K. Harris, W. Henry and R. Dill, "A Network-
based IoT Covert Channel," 2022 4th 
International 
Conference 
on 
Computer 
Communication and the Internet (ICCCI), 
Chiba, 
Japan, 
2022, 
pp. 
91-99. 
doi: 
10.1109/ICCCI55554.2022.9850247 
[24]
S. Vaheed, P. Nayak, P. S. Rajput, T. U. Snehit, 
Y. S. Kiran and L. Kumar, "Building IoT-
Assisted 
Indoor 
Air 
Quality 
Pollution 
Monitoring System," 2022 7th International 
Conference on Communication and Electronics 
Systems (ICCES), Coimbatore, India, 2022, pp. 
484-489. 
doi: 
10.1109/ICCES54183.2022.9835822 
[25]
Bhatt, S., Pham, T.K., Gupta, M., Benson, J., 
Park, J., & Sandhu, R.S. (2021). Attribute-Based 
Access Control for AWS Internet of Things and 
Secure Industries of the Future. IEEE Access, 9, 
107200-107223. 
Cite this article as : 
Pragya Bharti, Jeetendra Singh Yadav, "Attribute 
- Based Access Control for AWS Internet of 
Things- A Review ", International Journal of 
Scientific Research in Science and Technology 
(IJSRST), Online ISSN : 2395-602X, Print ISSN : 
2395-6011, Volume 10 Issue 3, pp. 995-1009, 
May-June 2023. 
Journal URL : https://ijsrst.com/IJSRST5231040