scholarly journals Privacy and E-Learning: A Pending Task

2021 ◽  
Vol 13 (16) ◽  
pp. 9206
Author(s):  
Marc Alier ◽  
Maria Jose Casañ Guerrero ◽  
Daniel Amo ◽  
Charles Severance ◽  
David Fonseca

Most educational software programs use and gather personal information and metadata from students. Additionally, most of the educational software programs are no longer operated by the learning institutions but are run by third-party agencies. This means that in the decade since 2020, information about students is stored and handled outside premises and control of learning institutions. The personal information about students and their activity while they interact with learning management systems and online learning tools is increasingly in custody of cloud computing platforms, software-as-a-service providers, and learning tool vendors. There is an increasing will to use all the data and metadata from the activity of the students for research, to develop education management strategies, pedagogy approaches, and develop behavior control tools or learning tools informed by behavior analysis from learning analytics. Many times, these studies lack the ethical and moral perspective. In addition, there is an increasing number of cases in which this information has leaked or has been used in a shady way. Additionally, this information will be around for a long time, tied to the future digital profiles of the students whose data has been leaked. This paper hypothesizes that there has been an ongoing process of technological evolution that leads to a loss of control over personal information, which makes it even more difficult to protect user confidentiality and ensuring privacy, that data surveillance has entered the world of education, and that the current legal frameworks are not enough to really protect the student’s personal information. The paper analyzes how this situation came to pass, and why this is wrong. We conclude with some proposals to address it from its different root dimensions: technical, cultural, legal, and organizational.

2021 ◽  
Vol 13 (1) ◽  
pp. 20-39
Author(s):  
Ahmed Aloui ◽  
Okba Kazar

In mobile business (m-business), a client sends its exact locations to service providers. This data may involve sensitive and private personal information. As a result, misuse of location information by the third party location servers creating privacy issues for clients. This paper provides an overview of the privacy protection techniques currently applied by location-based mobile business. The authors first identify different system architectures and different protection goals. Second, this article provides an overview of the basic principles and mechanisms that exist to protect these privacy goals. In a third step, the authors provide existing privacy protection measures.


Author(s):  
Abdul Razaque ◽  
Mohamed Frej ◽  
Bandar Alotaibi ◽  
Munif Alotaibi

Cloud computing has become a prominent technology due to its important utility service; this service concentrates on outsourcing data to organizations and individual consumers. Cloud computing has considerably changed the manner in which individuals or organizations store, retrieve, and organize their personal information. Despite the manifest development in cloud computing, there are still some concerns regarding the level of security and issues related to adopting cloud computing that prevent users from fully trusting this useful technology. Hence, for the sake of reinforcing the trust between Cloud Clients (CC) and Cloud Service Providers (CSP), as well as safeguarding the CC’s data in the cloud, several security paradigms of cloud computing based on a Third-Party Auditor (TPA) have been introduced. The TPA, as a trusted party, is responsible for checking the integrity of the CC’s data and all the critical information associated with it. However, the TPA could become an adversary and could aim to deteriorate the privacy of the CC’s data by playing a malicious role. In this paper, we present the state-of-art of cloud computing’s privacy-preserving models (PPM) based on a TPA. Three TPA factors of paramount significance have been discussed: TPA involvement, security requirements, and security threats caused by vulnerabilities. Moreover, TPA’s privacy preserving models have been comprehensively analyzed and categorized into different classes with an emphasis on their dynamicity. Finally, we discuss the limitations of the models and present our recommendations for their improvement.


2021 ◽  
Vol 77 (4) ◽  
pp. 73-85
Author(s):  
Glenn Baxter ◽  
Panarat Srisaeng ◽  
Graham Wild

Airlines around the world are increasingly focusing on the environmentally sustainable management of wastes produced as a by-product of their operations. The objective of this work was to analyze Finnair’s non-hazardous waste (NHW) types and quantities, their NHW management strategies, and the methods used to mitigate the environmental impact of their NHW, over the period 2008 to 2019. To achieve these objectives, the study was underpinned by an in-depth mixed methods research design; this incorporated a quantitative longitudinal study and a qualitative document analysis. The results revealed that despite significant growth of their operations, Finnair’s annual NHWs have declined over the study period. Finnair’s annual NHWs decreased from 5,710 tonnes in 2008 to 4,212.01 tonnes in 2019. The primary waste disposal methods used by the airline are waste-to-energy recovery and waste recycling, both in-house and by external third-party service providers. Smaller quantities of wastes are composted. Since 2015, the company has had a policy of not disposing wastes to landfill.


2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Weiqi Zhang ◽  
Guisheng Yin ◽  
Yuhai Sha ◽  
Jishen Yang

The rapid development of the Global Positioning System (GPS) devices and location-based services (LBSs) facilitates the collection of huge amounts of personal information for the untrusted/unknown LBS providers. This phenomenon raises serious privacy concerns. However, most of the existing solutions aim at locating interference in the static scenes or in a single timestamp without considering the correlation between location transfer and time of moving users. In this way, the solutions are vulnerable to various inference attacks. Traditional privacy protection methods rely on trusted third-party service providers, but in reality, we are not sure whether the third party is trustable. In this paper, we propose a systematic solution to preserve location information. The protection provides a rigorous privacy guarantee without the assumption of the credibility of the third parties. The user’s historical trajectory information is used as the basis of the hidden Markov model prediction, and the user’s possible prospective location is used as the model output result to protect the user’s trajectory privacy. To formalize the privacy-protecting guarantee, we propose a new definition, L&A-location region, based on k -anonymity and differential privacy. Based on the proposed privacy definition, we design a novel mechanism to provide a privacy protection guarantee for the users’ identity trajectory. We simulate the proposed mechanism based on a dataset collected in real practice. The result of the simulation shows that the proposed algorithm can provide privacy protection to a high standard.


Electronics ◽  
2021 ◽  
Vol 10 (19) ◽  
pp. 2359
Author(s):  
Yingwen Chen ◽  
Bowen Hu ◽  
Hujie Yu ◽  
Zhimin Duan ◽  
Junxin Huang

The IoT devices deployed in various application scenarios will generate massive data with immeasurable value every day. These data often contain the user’s personal privacy information, so there is an imperative need to guarantee the reliability and security of IoT data sharing. We proposed a new encrypted data storing and sharing architecture by combining proxy re-encryption with blockchain technology. The consensus mechanism based on threshold proxy re-encryption eliminates dependence on the third-party central service providers. Multiple consensus nodes in the blockchain network act as proxy service nodes to re-encrypt data and combine converted ciphertext, and personal information will not be disclosed in the whole procedure. That eliminates the restrictions of using decentralized network to store and distribute private encrypted data safely. We implemented a lot of simulated experiments to evaluate the performance of the proposed framework. The results show that the proposed architecture can meet the extensive data access demands and increase a tolerable time latency. Our scheme is one of the essays to utilize the threshold proxy re-encryption and blockchain consensus algorithm to support IoT data sharing.


Electronics ◽  
2021 ◽  
Vol 10 (21) ◽  
pp. 2721
Author(s):  
Abdul Razaque ◽  
Mohamed Ben Haj Frej ◽  
Bandar Alotaibi ◽  
Munif Alotaibi

Cloud computing has become a prominent technology due to its important utility service; this service concentrates on outsourcing data to organizations and individual consumers. Cloud computing has considerably changed the manner in which individuals or organizations store, retrieve, and organize their personal information. Despite the manifest development in cloud computing, there are still some concerns regarding the level of security and issues related to adopting cloud computing that prevent users from fully trusting this useful technology. Hence, for the sake of reinforcing the trust between cloud clients (CC) and cloud service providers (CSP), as well as safeguarding the CC’s data in the cloud, several security paradigms of cloud computing based on a third-party auditor (TPA) have been introduced. The TPA, as a trusted party, is responsible for checking the integrity of the CC’s data and all the critical information associated with it. However, the TPA could become an adversary and could aim to deteriorate the privacy of the CC’s data by playing a malicious role. In this paper, we present the state of the art of cloud computing’s privacy-preserving models (PPM) based on a TPA. Three TPA factors of paramount significance are discussed: TPA involvement, security requirements, and security threats caused by vulnerabilities. Moreover, TPA’s privacy preserving models are comprehensively analyzed and categorized into different classes with an emphasis on their dynamicity. Finally, we discuss the limitations of the models and present our recommendations for their improvement.


Author(s):  
D.I. Gray ◽  
J.I. Reid ◽  
D.J. Horne

A group of 24 Hawke's Bay hill country farmers are working with service providers to improve the resilience of their farming systems. An important step in the process was to undertake an inventory of their risk management strategies. Farmers were interviewed about their farming systems and risk management strategies and the data was analysed using descriptive statistics. There was considerable variation in the strategies adopted by the farmers to cope with a dryland environment. Importantly, these strategies had to cope with three types of drought and also upside risk (better than expected conditions), and so flexibility was critical. Infra-structure was important in managing a dryland environment. Farmers chose between increased scale (increasing farm size) and geographic dispersion (owning a second property in another location) through to intensification (investing in subdivision, drainage, capital fertiliser, new pasture species). The study identified that there may be scope for further investment in infra-structural elements such as drainage, deeper rooting alternative pasture species and water harvesting, along with improved management of subterranean clover to improve flexibility. Many of the farmers used forage crops and idling capacity (reduced stocking rate) to improve flexibility; others argued that maintaining pasture quality and managing upside risk was a better strategy in a dryland environment. Supplementary feed was an important strategy for some farmers, but its use was limited by contour and machinery constraints. A surprisingly large proportion of farmers run breeding cows, a policy that is much less flexible than trading stock. However, several farmers had improved their flexibility by running a high proportion of trading cattle and buffer mobs of ewe hoggets and trade lambs. To manage market risk, the majority of farmers are selling a large proportion of their lambs prime. Similarly, cattle are either sold prime or store onto the grass market when prices are at a premium. However, market risk associated with the purchase of supplements and grazing was poorly managed.


Author(s):  
Jin Han ◽  
Jing Zhan ◽  
Xiaoqing Xia ◽  
Xue Fan

Background: Currently, Cloud Service Provider (CSP) or third party usually proposes principles and methods for cloud security risk evaluation, while cloud users have no choice but accept them. However, since cloud users and cloud service providers have conflicts of interests, cloud users may not trust the results of security evaluation performed by the CSP. Also, different cloud users may have different security risk preferences, which makes it difficult for third party to consider all users' needs during evaluation. In addition, current security evaluation indexes for cloud are too impractical to test (e.g., indexes like interoperability, transparency, portability are not easy to be evaluated). Methods: To solve the above problems, this paper proposes a practical cloud security risk evaluation method of decision-making based on conflicting roles by using the Analytic Hierarchy Process (AHP) with Aggregation of Individual priorities (AIP). Results: Not only can our method bring forward a new index system based on risk source for cloud security and corresponding practical testing methods, but also can obtain the evaluation result with the risk preferences of conflicting roles, namely CSP and cloud users, which can lay a foundation for improving mutual trusts between the CSP and cloud users. The experiments show that the method can effectively assess the security risk of cloud platforms and in the case where the number of clouds increased by 100% and 200%, the evaluation time using our methodology increased by only by 12% and 30%. Conclusion: Our method can achieve consistent decision based on conflicting roles, high scalability and practicability for cloud security risk evaluation.


2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 639-639
Author(s):  
Karen Roberto ◽  
Brandy Renee McCann ◽  
Tina Savla ◽  
Emily Hoyt ◽  
Rosemary Blieszner ◽  
...  

Abstract Most family caregivers provide appropriate care and a supportive environment for their older relatives with dementia (PwD), yet the stress and strain associated with caregiving can trigger potentially harmful responses. Although much has been written about dealing with memory problems, researchers know less about how caregivers cope with difficult behaviors such as hallucinations, violent outbursts, or refusing food, medicine, or bathing. Interviews with 30 relatives providing care to community-dwelling PwD in rural Virginia revealed that caregivers typically used four behavior management strategies: reasoning with PwD; redirecting PwD’s attention; forceful actions, such as shouting at PwD; and withdrawing from interactions. Forceful management strategies and withdrawing from interactions were usually employed after reasoning and redirection failed to elicit desired behavior. Understanding whether caregivers’ expectations of PwD’s capacities are realistic, and why and when caregivers use various behavior management strategies, can help service providers develop appropriate educational interventions for frustrated caregivers.


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