On the Feasibility of Attribute-Based Encryption on Constrained IoT Devices for Smart Systems

Author(s):  
Benedetto Girgenti ◽  
Pericle Perazzo ◽  
Carlo Vallati ◽  
Francesca Righetti ◽  
Gianluca Dini ◽  
...  
2021 ◽  
Vol 170 ◽  
pp. 151-163
Author(s):  
Pericle Perazzo ◽  
Francesca Righetti ◽  
Michele La Manna ◽  
Carlo Vallati

Author(s):  
Fei Meng ◽  
Leixiao Cheng ◽  
Mingqiang Wang

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.


Author(s):  
M. Mazhar Rathore ◽  
Anand Paul ◽  
Awais Ahmad ◽  
Gwanggil Jeon

Recently, a rapid growth in the population in urban regions demands the provision of services and infrastructure. These needs can be come up wit the use of Internet of Things (IoT) devices, such as sensors, actuators, smartphones and smart systems. This leans to building Smart City towards the next generation Super City planning. However, as thousands of IoT devices are interconnecting and communicating with each other over the Internet to establish smart systems, a huge amount of data, termed as Big Data, is being generated. It is a challenging task to integrate IoT services and to process Big Data in an efficient way when aimed at decision making for future Super City. Therefore, to meet such requirements, this paper presents an IoT-based system for next generation Super City planning using Big Data Analytics. Authors have proposed a complete system that includes various types of IoT-based smart systems like smart home, vehicular networking, weather and water system, smart parking, and surveillance objects, etc., for dada generation. An architecture is proposed that includes four tiers/layers i.e., 1) Bottom Tier-1, 2) Intermediate Tier-1, 3) Intermediate Tier 2, and 4) Top Tier that handle data generation and collections, communication, data administration and processing, and data interpretation, respectively. The system implementation model is presented from the generation and collection of data to the decision making. The proposed system is implemented using Hadoop ecosystem with MapReduce programming. The throughput and processing time results show that the proposed Super City planning system is more efficient and scalable.


2021 ◽  
Vol 22 (2) ◽  
Author(s):  
Haixia Yu ◽  
Ion Cosmin Mihai ◽  
Anand Srivastava

With the development of smart meters, like Internet of Things (IoT), various kinds of electronic devices are equipped with each smart city. The several aspects of smart cities are accessible and these technologies enable us to be smarter. The utilization of the smart systems is very quick and valuable source to fulfill the requirement of city development. There are interconnection between various IoT devices and huge amount of data is generated when they communicate each other over the internet. It is very challenging task to effectively integrate the IoT services and processing big data. Therefore, a system for smart city development is proposed in this paper which is based on the IoT utilizing the analytics of big data. A complete system is proposed which includes various types of IoT-based smart systems like smart home, vehicular networking, and smart parking etc., for data generation. The Hadoop ecosystem is utilized for the implementation of the proposed system. The evaluation of the system is done in terms of throughput and processing time. The proposed technique is 20% to 65% better than the existing techniques in terms of time required for processing. In terms of obtained throughput, the proposed technique outperforms the existing technique by 20% to 60%.


2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Tao Zhang ◽  
Xiongfei Song ◽  
Lele Zheng ◽  
Yani Han ◽  
Kai Zhang ◽  
...  

Mobile crowdsensing systems use the extraction of valuable information from the data aggregation results of large-scale IoT devices to provide users with personalized services. Mobile crowdsensing combined with edge computing can improve service response speed, security, and reliability. However, previous research on data aggregation paid little attention to data verifiability and time sensitivity. In addition, existing edge-assisted data aggregation schemes do not support access control of large-scale devices. In this study, we propose a time-sensitive and verifiable data aggregation scheme (TSVA-CP-ABE) supporting access control for edge-assisted mobile crowdsensing. Specifically, in our scheme, we use attribute-based encryption for access control, where edge nodes can help IoT devices to calculate keys. Moreover, IoT devices can verify outsourced computing, and edge nodes can verify and filter aggregated data. Finally, the security of the proposed scheme is theoretically proved. The experimental results illustrate that our scheme outperforms traditional ones in both effectiveness and scalability under time-sensitive constraints.


2019 ◽  
Vol 4 (1) ◽  
pp. 237
Author(s):  
Nurhidayah Muhammad ◽  
Jasni Mohamad Zain

The purpose of this paper is to propose a conceptual model for data security in the Internet of thing devices. Estimated by Jumoki in early 2018 to 2022, there will be about 18 billion connected IoT devices. Therefore many issue related to IoT devices were discussed especially data security. Cryptography with lightweight features is one of the focus area by researchers to develop a powerful cryptography scheme for IoT devices. Lightweight cryptography scheme has been discussed and proposed widely recently. There are AES, PRESENT, Hash algorithm declared as a lightweight algorithm under consideration in ISO/IEC 29192 “Lightweight Cryptography”. Unfortunately these lightweight algorithm is one-to-one communication cryptography technique. This algorithm is very practical to implement for individuals or for small group communication but unpractical when implemented in a big company where many users can become a bottleneck. Therefore we propose a lightweight Ciphertext Policy-Attribute Based Encryption (CP-ABE) algorithm to implement in IoT devices. CP-ABE algorithm is one-to-many technique suitable for secure grouping communication, but this algorithm is not a lightweight feature. Therefore this paper proposes a lightweight CP-ABE algorithm for IoT devices.  


2022 ◽  
Vol 2022 ◽  
pp. 1-13
Author(s):  
Aliaa M. Alabdali

With the growing need of technology into varied fields, dependency is getting directly proportional to ease of user-friendly smart systems. The advent of artificial intelligence in these smart systems has made our lives easier. Several Internet of Things- (IoT-) based smart refrigerator systems are emerging which support self-monitoring of contents, but the systems lack to achieve the optimized run time and data security. Therefore, in this research, a novel design is implemented with the hardware level of integration of equipment with a more sophisticated software design. It was attempted to design a new smart refrigerator system, which has the capability of automatic self-checking and self-purchasing, by integrating smart mobile device applications and IoT technology with minimal human intervention carried through Blynk application on a mobile phone. The proposed system automatically makes periodic checks and then waits for the owner’s decision to either allow the system to repurchase these products via Ethernet or reject the purchase option. The paper also discussed the machine level integration with artificial intelligence by considering several features and implemented state-of-the-art machine learning classifiers to give automatic decisions. The blockchain technology is cohesively combined to store and propagate data for the sake of data security and privacy concerns. In combination with IoT devices, machine learning, and blockchain technology, the proposed model of the paper can provide a more comprehensive and valuable feedback-driven system. The experiments have been performed and evaluated using several information retrieval metrics using visualization tools. Therefore, our proposed intelligent system will save effort, time, and money which helps us to have an easier, faster, and healthier lifestyle.


2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Suhui Liu ◽  
Jiguo Yu ◽  
Chunqiang Hu ◽  
Mengmeng Li

Cloud-assisted Internet of Things (IoT) significantly facilitate IoT devices to outsource their data for high efficient management. Unfortunately, some unsettled security issues dramatically impact the popularity of IoT, such as illegal access and key escrow problem. Traditional public-key encryption can be used to guarantees data confidentiality, while it cannot achieve efficient data sharing. The attribute-based encryption (ABE) is the most promising way to ensure data security and to realize one-to-many fine-grained data sharing simultaneously. However, it cannot be well applied in the cloud-assisted IoT due to the complexity of its decryption and the decryption key leakage problem. To prevent the abuse of decryption rights, we propose a multiauthority ABE scheme with white-box traceability in this paper. Moreover, our scheme greatly lightens the overhead on devices by outsourcing the most decryption work to the cloud server. Besides, fully hidden policy is implemented to protect the privacy of the access policy. Our scheme is proved to be selectively secure against replayable chosen ciphertext attack (RCCA) under the random oracle model. Some theory analysis and simulation are described in the end.


Author(s):  
Rachna Jain

Cyber physical systems integrate actuators or sensors with networking technologies. Latest innovations in the area lead to cyber social systems or cyber physical social systems. Industry 4.0 amalgamates all major technologies including internet of things, big data, cloud computing, and smart systems under CPS. Cyber physical systems comprise of physical layer devices connected to the internet. It has vast applications in the areas like manufacturing, healthcare, energy, automation, robotics, smart building, meteorology, and transportation. Cyber and physical components interaction, training and adaptation ability, interoperability using IoT devices, information security using firewalls and cryptosystems, system robustness, and intervention of human inside and out of the loop are the major focusing areas in any CPS. In this chapter, application areas and challenges faced by cyber physical systems are discussed in detail.


Author(s):  
Mutwalibi Nambobi ◽  
Kanyana Ruth ◽  
Adam A. Alli ◽  
Rajab Ssemwogerere

The age of autonomous sensing has dominated almost every industry today. Our lives have been engaged with multiple sensors embedded in our smartphones to achieve sensing of all sorts starting from proximity sensing to social sensing. Our possessions (cars, fridges, oven) have sensors embedded in them. The art of autonomous IoT has shifted from a mere detection of events or changes in the environment to dominant systems for social sensing, big data analytics, and smart things. Recently, sensing systems have adapted connectivity resulting in input mechanisms for big data analytics and smart systems resulting in pervasive systems. Currently, a range of sensors has come to existence, for example, mobile phone sensors that measure blood pressure at patients' figure tip, or the sensors that be used to detect deforestation. In this chapter, the authors provide a technical view upon which autonomous IoT devices can be implemented and enlist opportunities and challenges of the same.


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