scholarly journals Anonymous Communication via Anonymous Identity-Based Encryption and Its Application in IoT

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Liaoliang Jiang ◽  
Tong Li ◽  
Xuan Li ◽  
Mohammed Atiquzzaman ◽  
Haseeb Ahmad ◽  
...  

Under the environment of the big data, the correlation between the data makes people have a greater demand for privacy. Moreover, the world has become more diversified and democratic than ever before. Freedom of speech is considered to be very important; thus, anonymity is also a very important security demand. The research of our paper proposes a scheme which can ensure both the privacy and the anonymity of a communication system, that is, the protection of message privacy while ensuring the users’ anonymity. It is based on anonymous identity-based encryption (IBE), by which the users’ metadata are protected. We implement our scheme in JAVA with Java pairing-based cryptography library (JPBC); the experiment shows that our scheme has significant advantage in efficiency compared with other anonymous communication system. Internet-of-Things (IoT) involves many devices, and privacy of devices is very significant. Anonymous communication system provides a secure environment without leaking metadata, which has many application scenarios in IoT.

Symmetry ◽  
2019 ◽  
Vol 11 (7) ◽  
pp. 913
Author(s):  
Lifeng Guo ◽  
Jing Wang ◽  
Wei-Chuen Yau

Security is a main concern for the Internet of Things (IoT) infrastructure as large volumes of data are collected and processed in the systems. Due to the limited resources of interconnected sensors and devices in the IoT systems, efficiency is one of the key considerations when deploying security solutions (e.g., symmetric/asymmetric encryption, authentication, etc.) in IoT. In this paper, we present an efficient Hierarchical Identity-Based Encryption (HIBE) system with short parameters for protecting data confidentiality in distributed IoT infrastructure. Our proposed HIBE system has the public parameters, private key, and ciphertext, each consisting of a constant number of group elements. We prove the full security of the HIBE system in the standard model using the dual system encryption technique. We also implement the proposed scheme and compare the performance with the original Lewko–Waters HIBE. To the best of our knowledge, our construction is the first HIBE system that achieves both full security in the standard model and short parameters in terms of the public parameters, private key, and ciphertext.


2019 ◽  
Vol 15 (7) ◽  
pp. 155014771986039 ◽  
Author(s):  
Baokang Zhao ◽  
Puguang Liu ◽  
Xiaofeng Wang ◽  
Ilsun You

Space-air-ground integrated Internet of things can improve the scope of Internet of things applications significantly by offering truly global coverage all over the world. While space-air-ground integrated Internet of things is promising to be very useful in many aspects, its deployment and application should overcome severe security threats, for example, interceptions, identity forgery, data tampering, and so on. Authentication is an essential step to protect the Internet of things security, and mutual authentication (i.e. two-way authentication) is especially important to ensure the security of both communication parties simultaneously. However, the intrinsical properties of network dynamics and wide coverage make the authentication concern in space-air-ground integrated Internet of things extremely challenging than traditional Internet of things networks. In this article, we propose MASIT, an identity-based efficient and lightweight mutual authentication scheme for space-air-ground integrated Internet of things. MASIT exploits the natural broadcast property of space-air-ground integrated Internet of things to speed up authentication process, and leverage the distinguished feature of IPv6 to support concurrent numerous nodes. Theoretically, we prove that MASIT is existential unforgeable secure under adaptively chosen message and identity Attacks. We also implement MASIT and other existing typical identity-based encryption schemes and evaluate their performance in real platforms. Experimental results showed that, MASIT outperforms the existing identity-based encryption schemes significantly, that is, the signature verification time can be reduced by 50% to 60%, and the user signature size can be reduced by 13% to 50%.


2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Yanli Ren ◽  
Min Dong ◽  
Zhihua Niu ◽  
Xiaoni Du

It is well known that the computation of bilinear pairing is the most expensive operation in pairing-based cryptography. In this paper, we propose a noninteractive verifiable outsourcing algorithm of bilinear pairing based on two servers in the one-malicious model. The outsourcer need not execute any expensive operation, such as scalar multiplication and modular exponentiation. Moreover, the outsourcer could detect any failure with a probability close to 1 if one of the servers misbehaves. Therefore, the proposed algorithm improves checkability and decreases communication cost compared with the previous ones. Finally, we utilize the proposed algorithm as a subroutine to achieve an anonymous identity-based encryption (AIBE) scheme with outsourced decryption and an identity-based signature (IBS) scheme with outsourced verification.


Author(s):  
Aravind Karrothu ◽  
Jasmine Norman

Fog networking supports the internet of things (IoT) concept, in which most of the devices used by humans on a daily basis will be connected to each other. Security issues in fog architecture are still a major research area as the number of security threats increases every day. Identity-based encryption (IBE) has a wide range of new cryptographic schemes and protocols that are particularly found to be suitable for lightweight architecture such as IoT and wireless sensor networks. This chapter focuses on these schemes and protocols in the background of wireless sensor networks. Also, this chapter analyses identity-based encryption schemes and the various attacks they are prone to.


2020 ◽  
pp. 109
Author(s):  
Syahrul Mubaroq ◽  
Inas Mufidatul Insyiroh

Coronavirus Disease 2019 (COVID-19) has spread throughout the world including Indonesia. The poor prevention and treatment of the initial phase results in a continuing increase in the number of positive cases and mortality caused by this virus. On the other hand, countries that have adopted policies that are fast and appropriate technology have been able to reduce the rate of additional cases and mortality rates. In this paper the authors conduct an analytical study of the application of technologies such as artificial intelligence, big data, and the internet of things in accelerating the detection, prevention, response, and recovery of COVID-19 cases in several countries and their possibilities to be applied in Indonesia. The authors suggest the Indonesian government to apply appropriate policies and technologies to reduce the high growth of COVID-19 cases.


2021 ◽  
Vol 8 (4) ◽  
pp. 685-733
Author(s):  
Jennifer Zwagerman

Technology advancements make life, work, and play easier and more enjoyable in many ways. Technology issues are also the cause of many headaches and dreams of living out the copier destruction scene from the movie “Office Space.” Whether it be user error or technological error, one key technology issue on many minds right now is how all the data produced every second of every day, in hundreds of different ways, is used by those that collect it. How much data are we talking about here? In 2018, the tech company Domo estimated that by 2020 “1.7 MB of data will be created every second” for every single person on Earth. In 2019, Domo’s annual report noted that “Americans use 4,416,720 GB of internet data including 188,000,000 emails, 18,100,000 texts and 4,497,420 Google searches every single minute.” And this was before the pandemic of 2020, which saw reliance on remote technology and the internet skyrocket. It is not just social media and working from home that generates data—the “Internet of Things” (“IoT”) is expanding exponentially. From our homes (smart appliances and thermostats), to entertainment (smart speakers and tablets), to what we wear (smartwatches and fitness devices), we are producing data constantly. Over 30 billion devices currently make up the IoT, and that number will double by 2025. The IoT is roughly defined as “devices—from simple sensors to smartphones and wearables—connected together.” That connection allows the devices to “talk” to each other across networks that stretch across the world, sharing information that in turn can be analyzed (alone or combined with data from other users) in ways that may be beneficial to the user or the broader economy. The key word in that last sentence is “may.” When it comes to the data that individuals and businesses across the world produce every second of every day, some of it—perhaps most of it—could be used in ways that are not beneficial to the user or the entire economy. Some data types can be used to cause harm in obvious ways, such as personal identifying information in cases of identity theft. While some data types may seem innocuous or harmful when viewed on their own, when combined with other data from the same user or even other users, it can be used in a wide variety of ways. While I find it beneficial to know how many steps I take in a day or how much time I sleep at night, I am not the only individual or entity with access to that information. The company that owns the device I wear also takes that information and uses it in ways that are beyond my control. Why would a company do that? In many instances, “[t]he data generated by the Internet of Things provides businesses with a wealth of information that—when properly collected, stored, and processed—gives businesses a depth of insight into user behavior never before seen.” Data security and privacy in general are issues that all companies manage as they work to protect the data we provide. Some types of data receive heightened protections, as discussed below, because they are viewed as personal, as private, or as potentially dangerous since unauthorized access to them could cause harm to the user/owner. Some states and countries have taken a step further, focusing not on industry-related data that needs particular types of protection, but in-stead looking at an individual’s overall right to privacy, particularly on the internet. Those protections are summarized below. It makes sense, you might say, to worry about financial or healthcare data remaining private and to not want every website you have ever visited to keep a file of information on you. But why might we care about the use of data in agricultural operations? Depending on who you ask, the answer may be that agricultural data needs no more care or concern than any other type of business data. Some argue that the use of “Big Data” in agriculture provides opportunities for smaller operations and shareholders. These opportunities include increased power in a market driven for many years by the mantra “bigger is better” and increased production of food staples across the world—both in a more environmentally-friendly fashion. While the benefits of technology and Big Data in the agricultural sector unarguably exist, questions remain as to how to best manage data privacy concerns in an industry where there is little specific law or regulation tied to collection, use, and ownership of this valuable agricultural production data. In the following pages, this Article discusses what types of data are currently being gathered in the agricultural sector and how some of that data can and is being used. In addition, it focuses on unique considerations tied to the use of agricultural data and why privacy concerns continue to increase for many producers. As the Article looks at potential solutions to privacy concerns, it summarizes privacy-related legislation that currently exists and ends by looking at whether any of the current privacy-related laws might be used or adapted within the agricultural sector to address potential misuse of agricultural data.


Nanoscale ◽  
2020 ◽  
Vol 12 (39) ◽  
pp. 20118-20130 ◽  
Author(s):  
Yike Liu ◽  
Chenguo Hu

New technologies such as the Internet of Things and big data have become the strategic focus of national development in the world.


The objective for the efficient functioning of the Indian democracy is purely dependent on the decisions made by the citizens of our country. To avoid duplicate or illegal votes we need a secure system which uniquely identifies our citizen. In India AADHAR uniquely identifies the citizens of INDIA by their thumb impression and also provides the other details like Date of birth, address, gender, father’s name, Spouse details etc. The election process is carried out in 3 steps Creation of voter list, actual voting process, and counting of votes. Creation of voter list can be done by database which is efficient to store big data with the person’s name and his AADHAR number. In actual voting process verification can be done by using fingerprint recognition and votes should be stored depending on ward numbers. Counting is the last process which can be done very easily if previous steps are digitized. In the world of Internet of things a voter should be able to cast his vote from anywhere by validating his credentials. This paper describes a voting system with 3 possible ways for voter to cast his vote


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