scholarly journals An Efficient Pairing-Free Certificateless Searchable Public Key Encryption for Cloud-Based IIoT

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Mimi Ma ◽  
Min Luo ◽  
Shuqin Fan ◽  
Dengguo Feng

The Industrial Internet of Things (IIoT), as a special form of Internet of Things (IoT), has great potential in realizing intelligent transformation and industrial resource utilization. However, there are security and privacy concerns about industrial data, which is shared on an open channel via sensor devices. To address these issues, many searchable encryption schemes have been presented to provide both data privacy-protection and data searchability. However, due to the use of expensive pairing operations, most previous schemes were inefficient. Recently, a certificateless searchable public-key encryption (CLSPE) scheme was designed by Lu et al. to remove the pairing operation. Unfortunately, we find that Lu et al.’s scheme is vulnerable to user impersonation attacks. To enhance the security, a new pairing-free dual-server CLSPE (DS-CLSPE) scheme for cloud-based IIoT deployment is designed in this paper. In addition, we provide security and efficiency analysis for DS-CLSPE. The analysis results show that DS-CLSPE can resist chosen keyword attacks (CKA) and has better efficiency than other related schemes.

2021 ◽  
Vol 17 (3) ◽  
pp. 25-45
Author(s):  
Muthukumaran V. ◽  
Manimozhi I. ◽  
Praveen Sundar P. V. ◽  
Karthikeyan T. ◽  
Magesh Gopu

Organizations have moved from the conventional industries to smart industries by embracing the approach of industrial internet of things (IIoT), which has provided an avenue for the integration of smart devices and communication technologies. In this context, this work presents a public key encryption with equality test based on DLP with decomposition problems over near-ring. The proposed method is highly secure, and it solves the problem of quantum algorithm attacks in industrial internet of thing systems. Further, the proposed system is highly secure, and it prevents the chosen-ciphertext attack in type-I adversary and it is indistinguishable against the random oracle model for the type-II adversary. The proposed scheme is highly secure, and the security analysis measures are comparatively stronger than existing techniques.


Author(s):  
Ganesh Gopal Deverajan ◽  
V. Muthukumaran ◽  
Ching‐Hsien Hsu ◽  
Marimuthu Karuppiah ◽  
Yeh‐Ching Chung ◽  
...  

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.


Author(s):  
Keith M. Martin

In this chapter, we introduce public-key encryption. We first consider the motivation behind the concept of public-key cryptography and introduce the hard problems on which popular public-key encryption schemes are based. We then discuss two of the best-known public-key cryptosystems, RSA and ElGamal. For each of these public-key cryptosystems, we discuss how to set up key pairs and perform basic encryption and decryption. We also identify the basis for security for each of these cryptosystems. We then compare RSA, ElGamal, and elliptic-curve variants of ElGamal from the perspectives of performance and security. Finally, we look at how public-key encryption is used in practice, focusing on the popular use of hybrid encryption.


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