scholarly journals Privacy-Preserving Internet of Things: Techniques and Applications

2019 ◽  
Vol 8 (6) ◽  
pp. 3229-3234 ◽  
Keyword(s):  
Cloud Computing ◽  
Homomorphic Encryption ◽  
Fog Computing ◽  
Privacy Preserving ◽  
Sensitive Information ◽  
Multiparty Computation ◽  
Iot Applications ◽  
Attribute Based Encryption ◽  
Daily Behavior ◽  
Iot Devices

Privacy has become an imperative term in the recent technology developments. Lots of data are being collected through every digital activity of users. The expeditious development of IoT applications have raised the concern about the privacy of the IoT systems. The data collected via IoT sensors can reveal the daily behavior of the users, location, and other sensitive information. Hence, it is necessary to preserve the privacy of data collected by IoT devices. A large number of techniques and approaches have been implemented and used in different IoT based applications such as cloud computing based IoT, fog computing based IoT, blockchain based IoT and trajectory applications. In this paper, we present a detailed investigation of the existing approaches to preserve the privacy of data in IoT applications. The techniques like k-anonymity, secure multiparty computation, attribute based encryption and homomorphic encryption are analyzed. Finally, a comparative analysis of privacy preserving techniques with its applications are presented.

scholarly journals Privacy-Preserving Data Aggregation against False Data Injection Attacks in Fog Computing

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2659 ◽  
Author(s):  
Yinghui Zhang ◽  
Jiangfan Zhao ◽  
Dong Zheng ◽  
Kaixin Deng ◽  
Fangyuan Ren ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Data Aggregation ◽  
Homomorphic Encryption ◽  
Fog Computing ◽  
Cloud Service ◽  
Privacy Preserving ◽  
Location Awareness ◽  
False Data Injection ◽  
Injection Attacks ◽  
Iot Devices

As an extension of cloud computing, fog computing has received more attention in recent years. It can solve problems such as high latency, lack of support for mobility and location awareness in cloud computing. In the Internet of Things (IoT), a series of IoT devices can be connected to the fog nodes that assist a cloud service center to store and process a part of data in advance. Not only can it reduce the pressure of processing data, but also improve the real-time and service quality. However, data processing at fog nodes suffers from many challenging issues, such as false data injection attacks, data modification attacks, and IoT devices’ privacy violation. In this paper, based on the Paillier homomorphic encryption scheme, we use blinding factors to design a privacy-preserving data aggregation scheme in fog computing. No matter whether the fog node and the cloud control center are honest or not, the proposed scheme ensures that the injection data is from legal IoT devices and is not modified and leaked. The proposed scheme also has fault tolerance, which means that the collection of data from other devices will not be affected even if certain fog devices fail to work. In addition, security analysis and performance evaluation indicate the proposed scheme is secure and efficient.

scholarly journals Efficient Resource Allocation for Time-Sensitive IoT Applications in Cloud and Fog Environments

2019 ◽  
Vol 8 (3) ◽  
pp. 2356-2363
Keyword(s):  
Cloud Computing ◽  
Health Monitoring ◽  
Fog Computing ◽  
Autonomous Driving ◽  
Computing System ◽  
The Internet ◽  
Iot Applications ◽  
Efficient Resource ◽  
Iot Devices ◽  
Simulation And Evaluation

Nowadays, with the quick development of internet and cloud technologies, a big number of physical objects are linked to the Internet and every day, more objects are connected to the Internet. It provides great benefits that lead to a significant improvement in the quality of our daily life. Examples include: Smart City, Smart Homes, Autonomous Driving Cars or Airplanes and Health Monitoring Systems. On the other hand, Cloud Computing provides to the IoT systems a series of services such as data computing, processing or storage, analysis and securing. It is estimated that by the year 2025, approximately trillion IoT devices will be used. As a result, a huge amount of data is going to be generated. In addition, in order to efficiently and accurately work, there are situations where IoT applications (such as Self Driving, Health Monitoring, etc.) require quick responses. In this context, the traditional Cloud Computing systems will have difficulties in handling and providing services. To balance this scenario and to overcome the drawbacks of cloud computing, a new computing model called fog computing has proposed. In this paper, a comparison between fog computing and cloud computing paradigms were performed. The scheduling task for an IoT application in a cloud-fog computing system was considered. For the simulation and evaluation purposes, the CloudAnalyst simulation toolkit was used. The obtained numerical results showed the fog computing achieves better performance and works more efficient than Cloud computing. It also reduced the response time, processing time ,and cost of transfer data to the cloud.

scholarly journals Leveraging Fog Computing for a Secure and Smart Healthcare

2019 ◽  
Vol 8 (2) ◽  
pp. 6117-6122
Keyword(s):  
Cloud Computing ◽  
Homomorphic Encryption ◽  
Fog Computing ◽  
Healthcare Services ◽  
Decision Fusion ◽  
Sensor Data ◽  
Smart Sensors ◽  
Healthcare Applications ◽  
Smart Healthcare ◽  
Iot Devices

From hairbrushes to scales, all devices have sensors embedded in them to collect and communicate data. Smart Healthcare is proving to be an exciting and dynamic area with lots of room for new innovations and the increasing consumer demand for proactive health monitoring devices. Having India poised to spend a lot on healthcare, recent innovations using IoT devices and big data analytics can propel the healthcare industry into the future. Smart healthcare providers are leveraging cloud computing with fog computing to optimize their healthcare services. These smart healthcare applications depend mainly on the raw sensor data collected, aggregated, and analyzed by the smart sensors. Smart sensors these days generate myriad amount of data like text, image, audio, and video that require real-time or batch processing. Aggregating these diverse data from various types of resources remains a dispute till date. To resolve this issue, we have proposed a softwarized infrastructure that integrates cloud computing and fog computing, message brokers, and Tor for supple, safe, viable, and a concealed IoT exploitation for smart healthcare applications and services. Our proposed platform employs machine-to-machine (M2M) messaging, data fusion and decision fusion, and uses rule-based beacons for seamless data management. Our proposed flexBeacon system provides an IoT infrastructure that is nimble, secure, flexible, private, and reasonable. We have also proposed an M2M transceiver and microcontroller for flawless data incorporation of smart healthcare applications and services. Based on the IoT devices’ technical capabilities and resource availability, some systems are capable of making use of homomorphic encryption and zero knowledge proofs. The proposed flexBeacon platform offers seamless management and data aggregation without loss of accuracy. The cost of implementing a softwarized IoT for smart healthcare is also greatly reduced.

scholarly journals Privacy-Preserving IoT Data Aggregation Based on Blockchain and Homomorphic Encryption

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2452
Author(s):  
Faiza Loukil ◽  
Chirine Ghedira-Guegan ◽  
Khouloud Boukadi ◽  
Aïcha-Nabila Benharkat
Keyword(s):  
Data Aggregation ◽  
Homomorphic Encryption ◽  
Privacy Preserving ◽  
Security And Privacy ◽  
Sensitive Information ◽  
Aggregation Process ◽  
Smart Contract ◽  
Reasonable Choice ◽  
Iot Devices

Data analytics based on the produced data from the Internet of Things (IoT) devices is expected to improve the individuals’ quality of life. However, ensuring security and privacy in the IoT data aggregation process is a non-trivial task. Generally, the IoT data aggregation process is based on centralized servers. Yet, in the case of distributed approaches, it is difficult to coordinate several untrustworthy parties. Fortunately, the blockchain may provide decentralization while overcoming the trust problem. Consequently, blockchain-based IoT data aggregation may become a reasonable choice for the design of a privacy-preserving system. To this end, we propose PrivDA, a Privacy-preserving IoT Data Aggregation scheme based on the blockchain and homomorphic encryption technologies. In the proposed system, each data consumer can create a smart contract and publish both terms of service and requested IoT data. Thus, the smart contract puts together into one group potential data producers that can answer the consumer’s request and chooses one aggregator, the role of which is to compute the group requested result using homomorphic computations. Therefore, group-level aggregation obfuscates IoT data, which complicates sensitive information inference from a single IoT device. Finally, we deploy the proposal on a private Ethereum blockchain and give the performance evaluation.

scholarly journals A Fog Computing-based Framework for Privacy Preserving IoT Environments

2020 ◽  
Vol 17 (3) ◽  
pp. 306-315
Author(s):  
Dhiah el Diehn Abou-Tair ◽  
Simon Büchsenstein ◽  
Ala’ Khalifeh
Keyword(s):  
Cloud Computing ◽  
Storage Capacity ◽  
Fog Computing ◽  
Security Analysis ◽  
Vital Signs ◽  
Privacy Preserving ◽  
Security And Privacy ◽  
Computing Power ◽  
Privacy Threats ◽  
Iot Devices

Privacy is becoming an indispensable component in the emerging Internet of Things (IoT) context. However, the IoT based devices and tools are exposed to several security and privacy threats, especially that these devices are mainly used to gather data about users’ habits, vital signs, surround environment, etc., which makes them a lucrative target to intruders. Up to date, conventional security and privacy mechanisms are not well optimized for IoT devices due to their limited energy, storage capacity, communication functionality and computing power, which influenced researchers to propose new solutions and algorithms to handle these limitations. Fog and cloud computing have been recently integrated in IoT environment to solve their resources’ limitations, thus facilitating new life scenarios-oriented applications. In this paper, a security and privacy preserving framework is proposed, which utilizes Fog and cloud computing in conjunction with IoT devices that aims at securing the users’ data and protecting their privacy. The framework has been implemented and tested using available technologies. Furthermore, a security analysis has been verified by simulating several hypothetical attack scenarios, which showed the effectiveness of the proposed framework and its capability of protecting the users’ information.

scholarly journals Ciphertext-policy attribute-based encryption with hidden sensitive policy from keyword search techniques in smart city

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Fei Meng ◽  
Leixiao Cheng ◽  
Mingqiang Wang
Keyword(s):  
Smart City ◽  
Keyword Search ◽  
Sensitive Information ◽  
Security Model ◽  
Computational Overhead ◽  
Diffie Hellman ◽  
Attribute Based Encryption ◽  
Iot Devices ◽  
Ciphertext Policy ◽  
Access Policies

AbstractCountless data generated in Smart city may contain private and sensitive information and should be protected from unauthorized users. The data can be encrypted by Attribute-based encryption (CP-ABE), which allows encrypter to specify access policies in the ciphertext. But, traditional CP-ABE schemes are limited because of two shortages: the access policy is public i.e., privacy exposed; the decryption time is linear with the complexity of policy, i.e., huge computational overheads. In this work, we introduce a novel method to protect the privacy of CP-ABE scheme by keyword search (KS) techniques. In detail, we define a new security model called chosen sensitive policy security: two access policies embedded in the ciphertext, one is public and the other is sensitive and hidden. If user's attributes don't satisfy the public policy, he/she cannot get any information (attribute name and its values) of the hidden one. Previous CP-ABE schemes with hidden policy only work on the “AND-gate” access structure or their ciphertext size or decryption time maybe super-polynomial. Our scheme is more expressive and compact. Since, IoT devices spread all over the smart city, so the computational overhead of encryption and decryption can be shifted to third parties. Therefore, our scheme is more applicable to resource-constrained users. We prove our scheme to be selective secure under the decisional bilinear Diffie-Hellman (DBDH) assumption.

scholarly journals Efficient Secure Multiparty Computation Protocol for Sequencing Problem over Insecure Channel

2013 ◽  
Vol 2013 ◽  
pp. 1-5 ◽  
Author(s):  
Yi Sun ◽  
Qiaoyan Wen ◽  
Yudong Zhang ◽  
Hua Zhang ◽  
Zhengping Jin
Keyword(s):  
Homomorphic Encryption ◽  
Privacy Preserving ◽  
Secure Multiparty Computation ◽  
Online Auction ◽  
Multiparty Computation ◽  
Sequencing Problem ◽  
The Core ◽  
Secure Protocol ◽  
Core Issue

As a powerful tool in solving privacy preserving cooperative problems, secure multiparty computation is more and more popular in electronic bidding, anonymous voting, and online auction. Privacy preserving sequencing problem which is an essential link is regarded as the core issue in these applications. However, due to the difficulties of solving multiparty privacy preserving sequencing problem, related secure protocol is extremely rare. In order to break this deadlock, this paper first presents an efficient secure multiparty computation protocol for the general privacy-preserving sequencing problem based on symmetric homomorphic encryption. The result is of value not only in theory, but also in practice.

Survey on DDoS Attacks and Defense Mechanisms in Cloud and Fog Computing

2018 ◽  
Vol 10 (3) ◽  
pp. 61-83 ◽  
Author(s):  
Deepali Chaudhary ◽  
Kriti Bhushan ◽  
B.B. Gupta
Keyword(s):  
Cloud Computing ◽  
Defense Mechanisms ◽  
Low Cost ◽  
Fog Computing ◽  
Smart Devices ◽  
Cloud Environment ◽  
Security Issue ◽  
Process Data ◽  
Ddos Attack ◽  
Iot Devices

This article describes how cloud computing has emerged as a strong competitor against traditional IT platforms by offering low-cost and “pay-as-you-go” computing potential and on-demand provisioning of services. Governments, as well as organizations, have migrated their entire or most of the IT infrastructure to the cloud. With the emergence of IoT devices and big data, the amount of data forwarded to the cloud has increased to a huge extent. Therefore, the paradigm of cloud computing is no longer sufficient. Furthermore, with the growth of demand for IoT solutions in organizations, it has become essential to process data quickly, substantially and on-site. Hence, Fog computing is introduced to overcome these drawbacks of cloud computing by bringing intelligence to the edge of the network using smart devices. One major security issue related to the cloud is the DDoS attack. This article discusses in detail about the DDoS attack, cloud computing, fog computing, how DDoS affect cloud environment and how fog computing can be used in a cloud environment to solve a variety of problems.

scholarly journals Device-Based Security to Improve User Privacy in the Internet of Things †

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2664 ◽  
Author(s):  
Luis Belem Pacheco ◽  
Eduardo Pelinson Alchieri ◽  
Priscila Mendez Barreto
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Single Point ◽  
Data Access ◽  
Cloud Services ◽  
Sensitive Information ◽  
User Privacy ◽  
Privacy And Security ◽  
Iot Devices ◽  
And Control

The use of Internet of Things (IoT) is rapidly growing and a huge amount of data is being generated by IoT devices. Cloud computing is a natural candidate to handle this data since it has enough power and capacity to process, store and control data access. Moreover, this approach brings several benefits to the IoT, such as the aggregation of all IoT data in a common place and the use of cloud services to consume this data and provide useful applications. However, enforcing user privacy when sending sensitive information to the cloud is a challenge. This work presents and evaluates an architecture to provide privacy in the integration of IoT and cloud computing. The proposed architecture, called PROTeCt—Privacy aRquitecture for integratiOn of internet of Things and Cloud computing, improves user privacy by implementing privacy enforcement at the IoT devices instead of at the gateway, as is usually done. Consequently, the proposed approach improves both system security and fault tolerance, since it removes the single point of failure (gateway). The proposed architecture is evaluated through an analytical analysis and simulations with severely constrained devices, where delay and energy consumption are evaluated and compared to other architectures. The obtained results show the practical feasibility of the proposed solutions and demonstrate that the overheads introduced in the IoT devices are worthwhile considering the increased level of privacy and security.

Security Assertion of IoT Devices Using Cloud of Things Perception

2019 ◽  
Vol 11 (4) ◽  
pp. 17-31
Author(s):  
Mamata Rath ◽  
Bibudhendu Pati
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Communication Systems ◽  
Future Internet ◽  
Computing Systems ◽  
Iot Security ◽  
Security Assurance ◽  
Iot Applications ◽  
The Future ◽  
Iot Devices

Adoption of Internet of Things (IoT) and Cloud of Things (CoT) in the current developing technology era are expected to be more and more invasive, making them important mechanism of the future Internet-based communication systems. Cloud of Things and Internet of Things (IoT) are two emerging as well as diversified advanced domains that are diversified in current technological scenario. Paradigm where Cloud and IoT are merged together is foreseen as disruptive and as an enabler of a large number of application scenarios. Due to the adoption of the Cloud and IoT paradigm a number of applications are gaining important technical attention. In the future, it is going to be more complicated a setup to handle security in technology. Information till now will severely get changed and it will be very tough to keep up with varying technology. Organisations will have to repeatedly switch over to new skill-based technology with respect to higher expenditure. Latest tools, methods and enough expertise are highly essential to control threats and vulnerability to computing systems. Keeping in view the integration of Cloud computing and IoT in the new domain of Cloud of things, the said article provides an up-to-date eminence of Cloud-based IoT applications and Cloud of Things with a focus on their security and application-oriented challenges. These challenges are then synthesized in detail to present a technical survey on various issues related to IoT security, concerns, adopted mechanisms and their positive security assurance using Cloud of Things.

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