Blockchain Technology - Based Solutions for IOT Security

Blockchain innovation has picked up expanding consideration from investigating and industry over the later a long time. It permits actualizing in its environment the smart-contracts innovation which is utilized to robotize and execute deals between clients. Blockchain is proposed nowadays as the unused specialized foundation for a few sorts of IT applications. Blockchain would aid avoid the duplication of information because it right now does with Bitcoin and other cryptocurrencies. Since of the numerous hundreds of thousands of servers putting away the Bitcoin record, it’s impossible to assault and alter. An aggressor would need to change the record of 51 percent of all the servers, at the precise same time. The budgetary fetched of such an assault would distantly exceed the potential picks up. The same cannot be said for our private data that lives on single servers possessed by Google and Amazon. In this paper, we outline major Blockchain technology that based as solutions for IOT security. We survey and categorize prevalent security issues with respect to IoT data privacy, in expansion to conventions utilized for organizing, communication, and administration. We diagram security necessities for IoT together with the existing scenarios for using blockchain in IoT applications.

Oblivious algebraic data types

Secure computation allows multiple parties to compute joint functions over private data without leaking any sensitive data, typically using powerful cryptographic techniques. Writing secure applications using these techniques directly can be challenging, resulting in the development of several programming languages and compilers that aim to make secure computation accessible. Unfortunately, many of these languages either lack or have limited support for rich recursive data structures, like trees. In this paper, we propose a novel representation of structured data types, which we call oblivious algebraic data types, and a language for writing secure computations using them. This language combines dependent types with constructs for oblivious computation, and provides a security-type system which ensures that adversaries can learn nothing more than the result of a computation. Using this language, authors can write a single function over private data, and then easily build an equivalent secure computation according to a desired public view of their data.

Hierarchical Federated Learning for Edge-Aided Unmanned Aerial Vehicle Networks

Federated learning (FL) allows UAVs to collaboratively train a globally shared machine learning model while locally preserving their private data. Recently, the FL in edge-aided unmanned aerial vehicle (UAV) networks has drawn an upsurge of research interest due to a bursting increase in heterogeneous data acquired by UAVs and the need to build the global model with privacy; however, a critical issue is how to deal with the non-independent and identically distributed (non-i.i.d.) nature of heterogeneous data while ensuring the convergence of learning. To effectively address this challenging issue, this paper proposes a novel and high-performing FL scheme, namely, the hierarchical FL algorithm, for the edge-aided UAV network, which exploits the edge servers located in base stations as intermediate aggregators with employing commonly shared data. Experiment results demonstrate that the proposed hierarchical FL algorithm outperforms several baseline FL algorithms and exhibits better convergence behavior.

An Analysis of Children's Content on YouTube in the Context of Sharenting

Parental responsibility will be evaluated from the children's perspective, and the pre-birth rights of the child will be discussed in a juridical and social context. Within this scope, 375 videos, viewed between March 17, 2019 and December 23, 2020, will be studied in-depth using the content analysis method. As the aforementioned YouTube channel mainly targets younger child groups and the E.K.M. is also 6, it is of great importance to discuss the suitability of the experienced digital games' educative and instructive features for children, as well as if they consist of elements of violence and horror. Parental responsibility will be evaluated together with a selection of digital games and game displays. Having numerous followers in Turkey, the ‘Sesegel Çocuk' channel will be probed extensively since the channel has a potential to act as a role model for its target audience. Digital parenting and the sharenting phenomenon will be extensively analyzed with regard to privacy, personal data confidentiality and security, protection of emotional and private data, and protection of personal rights.

A Survey on Emerging Security Issues, Challenges, and Solutions for Internet of Things (IoTs)

The internet of things is a cutting-edge technology that is vulnerable to all sorts of fictitious solutions. As a new phase of computing emerges in the digital world, it intends to produce a huge number of smart gadgets that can host a wide range of applications and operations. IoT gadgets are a perfect target for cyber assaults because of their wide dispersion, availability/accessibility, and top-notch computing power. Furthermore, as numerous IoT devices gather and investigate private data, they become a gold mine for hostile actors. Hence, the matter of fact is that security, particularly the potential to diagnose compromised nodes, as well as the collection and preservation of testimony of an attack or illegal activity, have become top priorities. This chapter delves into the timeline and the most challenging security and privacy issues that exist in the present scenario. In addition to this, some open issues and future research directions are also discussed.

Monetizing your personal data

What is your private data worth, to you and to the companies willing to pay you for it?

Outsourced Mutual Private Set Intersection Protocol for Edge-Assisted IoT

The development of edge computing and Internet of Things technology has brought convenience to our lives, but the sensitive and private data collected are also more vulnerable to attack. Aiming at the data privacy security problem of edge-assisted Internet of Things, an outsourced mutual Private Set Intersection protocol is proposed. The protocol uses the ElGamal threshold encryption algorithm to rerandomize the encrypted elements to ensure all the set elements are calculated in the form of ciphertext. After that, the protocol maps the set elements to the corresponding hash bin under the execution of two hash functions and calculates the intersection in a bin-to-bin manner, reducing the number of comparisons of the set elements. In addition, the introduction of edge servers reduces the computational burden of participating users and achieves the fairness of the protocol. Finally, the IND-CPA security of the protocol is proved, and the performance of the protocol is compared with other relevant schemes. The evaluation results show that this protocol is superior to other related protocols in terms of lower computational overhead.