Search results for: workflow privacy

Authors: Robnier Reyes, Andrew J. P. Marques, Joel Ramjist, Chris R. Pasarikovski, Victor X. D. Yang

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Over the past three decades, surgical robotic systems have demonstrated their ability to improve surgical outcomes. The LBR Med is a collaborative robotic arm that is meant to work with a surgeon to streamline surgical workflow. It has 7 degrees of freedom and thus can be easily oriented. Position and torque sensors at each joint allow it to maintain a position accuracy of 150 µm with real-time force and torque feedback, making it ideal for complex surgical procedures. Spinal fusion procedures involve the placement of as many as 20 pedicle screws, requiring a great deal of accuracy due to proximity to the spinal canal and surrounding vessels. Any deviation from intended path can lead to major surgical complications. Assistive surgical robotic systems are meant to serve as collaborative devices easing the workload of the surgeon, thereby improving pedicle screw placement by mitigating fatigue related inaccuracies. Moreover, robotic spinal systems have shown marked improvements over conventional freehanded techniques in both screw placement accuracy and fusion quality and have greatly reduced the need for screw revision, intraoperatively and post-operatively. However, current assistive spinal fusion robots, such as the ROSA Spine, are limited in functionality to positioning surgical instruments. While they offer a small degree of improvement in pedicle screw placement accuracy, they do not alleviate surgeon fatigue, nor do they provide real-time force and torque feedback during screw insertion. We propose a semi-autonomous surgical robot workflow for spinal fusion where the surgeon guides the robot to its initial position and orientation, and the robot drives the pedicle screw accurately into the vertebra. Here, we demonstrate feasibility by inserting pedicle screws into ex-vivo bovine rib bone. The robot monitors position, force and torque with respect to predefined values selected by the surgeon to ensure the highest possible spinal fusion quality. The workflow alleviates the strain on the surgeon by having the robot perform the screw placement while the ability to monitor the process in real-time keeps the surgeon in the system loop. The approach we have taken in terms of level autonomy for the robot reflects its ability to safely collaborate with the surgeon in the operating room without external navigation systems.

Keywords: ex vivo bovine bone, pedicle screw, surgical robot, surgical workflow

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Authors: Shu-Lu Hsu, Fang-Yi Chu

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With the advances in information and communications technology, mobile context-aware applications have become powerful marketing tools. In Apple online store, there are numerous mobile applications (APPs) developed for destination tour. This study investigated the determinants of adoption of context-aware APPs for destination tour services. A model is proposed based on Technology Acceptance Model and privacy concern theory. The model was empirically tested based on a sample of 259 users of a tourism APP published by Kaohsiung Tourism Bureau, Taiwan. The results showed that the fitness of the model is well and, among all the factors, the perceived usefulness and perceived ease of use have the most significant influences on the intention to adopt context-aware destination APPs. Finally, contrary to the findings of previous literature, the effect of privacy concern on the adoption intention of context-aware APP is insignificant.

Keywords: mobile application, context-aware, privacy concern, TAM

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Authors: Mugabe Nzarama Gabriel

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In Rwanda, many healthcare organizations are still using a paper based patients’ data record system although it still present weaknesses to share health patients’ information across different services when necessary. In developed countries, the EHR has been put in place to revolutionize the paper based record system but still the EHR has some challenges related to privacy, security, or interoperability. The purpose of this research was to assess the existing patients’ data record system in healthcare sector in Rwanda, see what an EHR can improve to the system in place and assess the acceptance of EHR as system which is interoperable, very secure and interoperable and see whether stakeholders are ready to adopt the system. The case based methodology was used and TAM theoretical framework to design the questionnaire for the survey. A judgmental sample across two cases, CHUB and Hopital de Nemba, has been selected and SPSS has been used for descriptive statistics. After a qualitative analysis, the findings showed that the paper based record is useful, gives complete information about the patient, protects the privacy of patients but it is still less secure and less interoperable. The respondents shown that they are ready to use the proposed EHR System and want it secure, capable of enforcing the privacy but still they are not all ready for the interoperability. A conclusion has been formulated; recommendations and further research have been proposed.

Keywords: EHR system, healthcare service, TAM, privacy, interoperability

Procedia PDF Downloads 238

Authors: A. Dinelka Panagoda, Bathiya Bandara, Chamod Wijetunga, Chathura Malinda, Lakmal Rupasinghe, Chethana Liyanapathirana

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This research takes us forward with the concepts of Federated Learning and Software-Defined Networking (SDN) to introduce an efficient malware detection technique and provide a mitigation mechanism to give birth to a resilient and automated healthcare sector network system by also adding the feature of extended privacy preservation. Due to the daily transformation of new malware attacks on hospital Integrated Clinical Environment (ICEs), the healthcare industry is at an undefinable peak of never knowing its continuity direction. The state of blindness by the array of indispensable opportunities that new medical device inventions and their connected coordination offer daily, a factor that should be focused driven is not yet entirely understood by most healthcare operators and patients. This solution has the involvement of four clients in the form of hospital networks to build up the federated learning experimentation architectural structure with different geographical participation to reach the most reasonable accuracy rate with privacy preservation. While the logistic regression with cross-entropy conveys the detection, SDN comes in handy in the second half of the research to stack up the initial development phases of the system with malware mitigation based on policy implementation. The overall evaluation sums up with a system that proves the accuracy with the added privacy. It is no longer needed to continue with traditional centralized systems that offer almost everything but not privacy.

Keywords: software-defined network, federated learning, privacy, integrated clinical environment, decentralized learning, malware detection, malware mitigation

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Authors: Bhaumik Tyagi, Mandeep Kaur, Kanika Singla

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The advancement of blockchain has facilitated scholars to remodel e-voting systems for future generations. Server-side attacks like SQL injection attacks and DOS attacks are the most common attacks nowadays, where malicious codes are injected into the system through user input fields by illicit users, which leads to data leakage in the worst scenarios. Besides, quantum attacks are also there which manipulate the transactional data. In order to deal with all the above-mentioned attacks, integration of blockchain, convolutional neural network (CNN), and Quantum Key Distribution is done in this very research. The utilization of blockchain technology in e-voting applications is not a novel concept. But privacy and security issues are still there in a public and private blockchains. To solve this, the use of a hybrid blockchain is done in this research. This research proposed cryptographic signatures and blockchain algorithms to validate the origin and integrity of the votes. The convolutional neural network (CNN), a normalized version of the multilayer perceptron, is also applied in the system to analyze visual descriptions upon registration in a direction to enhance the privacy of voters and the e-voting system. Quantum Key Distribution is being implemented in order to secure a blockchain-based e-voting system from quantum attacks using quantum algorithms. Implementation of e-voting blockchain D-app and providing a proposed solution for the privacy of voters in e-voting using Blockchain, CNN, and Quantum Key Distribution is done.

Keywords: hybrid blockchain, secure e-voting system, convolutional neural networks, quantum key distribution, one-time pad

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Authors: Deborah Garcia-Magna

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The use of new technologies has become widespread in the last decade, giving rise to various risks associated with the transfer of personal data and the publication of sensitive material on social media. There are already several supranational instruments that seek to protect the citizens involved in this growing traffic of personal information and, especially, the most vulnerable people, such as minors, who are also the ones who make the most intense use of these new means of communication. In this sense, the configuration of the concept of privacy as a legal right has necessarily been influenced by these new social uses and supranational instruments. The researcher considers correct the decision to introduce sexting as a new criminal behaviour in the Penal Code in 2015, but questions the concrete manner in which it has been made. To this end, an updated review of the various options that our legal system already offered is made, assessing whether these legal options adequately addressed the new social needs and guidelines from jurisprudence and other supranational instruments. Some important issues emerge as to whether the principles of fragmentarity and subsidiarity may be violated since the new article 197.7 of the Spanish Penal Code could refer to very varied behaviours and protect not only particularly vulnerable persons. In this sense, the research focuses on issues such as the concept of 'seriousness' of the infringement of privacy, the possible reckless conduct of the victim, who hang over its own private material to third parties, the affection to other legal rights such as freedom and sexual indemnity, the possible problems of concurrent offences, etc.

Keywords: criminal law reform, ECHR jurisprudence, right to privacy, sexting

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Authors: Andrei Bogdan Stanescu, Robert Stana

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Creating private and secure communication channels between employees has become a critical aspect in order to ensure organizational integrity and avoid leaks of sensitive information. With the widespread use of modern methods of disrupting communication between users, real use-cases of advanced encryption mechanisms have emerged to avoid cyber-attackers that are willing to intercept private conversations between critical employees in an organization. This paper aims to present a custom implementation of a messaging application named “Whisper” that uses end-to-end encryption (E2EE) mechanisms and blockchain-related components to protect sensitive conversations and mitigate the risks of information breaches inside organizations. The results of this research paper aim to expand the areas of applicability of E2EE algorithms and integrations with private blockchains in chat applications as a viable method of enhancing intra-organizational communication privacy.

Keywords: end-to-end encryption, mobile communication, cryptography, communication security, data privacy

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Authors: Mhaned Oubounyt, Jan Baumbach

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Differences in co-expression networks between two or multiple cells (sub)types across conditions is a pressing problem in single-cell RNA sequencing (scRNA-seq). A key challenge is to define those co-variations that differ between or among cell types and/or conditions and phenotypes to examine small regulatory networks that can explain mechanistic differences. To this end, we developed SCANet, an all-in-one Python package that uses state-of-the-art algorithms to facilitate the workflow of a combined single-cell GCN (Gene Correlation Network) and GRN (Gene Regulatory Networks) pipeline, including inference of gene co-expression modules from scRNA-seq, followed by trait and cell type associations, hub gene detection, co-regulatory networks, and drug-gene interactions. In an example case, we illustrate how SCANet can be applied to identify regulatory drivers behind a cytokine storm associated with mortality in patients with acute respiratory illness. SCANet is available as a free, open-source, and user-friendly Python package that can be easily integrated into systems biology pipelines.

Keywords: single-cell, co-expression networks, drug-gene interactions, co-regulatory networks

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Authors: Neeley Current, Fatih Demir, Kenneth Haggerty, Blake Naughton, Isa Jahnke

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Educational systems seek reform using data-intensive continuous improvement processes known as strategic improvement plans (SIPs). Schools turn to digital systems to monitor, analyze and report SIPs. One technical challenge of these digital systems focuses on integrating a highly diverse set of data sources. Another challenge is to create a learnable sociotechnical system to help administrators, principals and teachers add, manipulate and interpret data. This study explores to what extent one particular system is usable and useful for strategic planning activities and whether intended users see the benefit of the system achieve the goal of improving workflow related to strategic planning in schools. In a three-phase study, researchers used sociotechnical design methods to understand the current workflow, technology use, and processes of teachers and principals surrounding their strategic improvement planning. Additionally, design review and task analysis usability methods were used to evaluate task completion, usability, and user satisfaction of the system. The resulting socio-technical models illustrate the existing work processes and indicate how and at which places in the workflow the newly developed system could have an impact. The results point to the potential of the system but also indicate that it was initially too complicated for use. However, the diverse users see the potential benefits, especially to overcome the diverse set of data sources, and that the system could fill a gap for schools in planning and conducting strategic improvement plans.

Keywords: continuous improvement process, education reform, strategic improvement planning, sociotechnical design, software development, usability

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Authors: Rizwan Rizwan

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Secure Multiparty Computation is an emerging area of research within the cryptographic community, enabling secure collaboration among multiple parties while safeguarding their sensitive data. Secure Multiparty Computation has been extensively studied in the context of plane geometry, its application to complex solid geometry shapes remains relatively unexplored. This research paper aims to bridge this gap by proposing a solution for the secure multiparty computation of intersecting tetrahedra. We present an approach to calculate the volume of intersecting tetrahedra securely while preserving the privacy of the input data provided by each participating party. The proposed solution leverages accepted simulation paradigms to prove the privacy of the computation. We thoroughly analyze the computational and communication complexities of our approach, demonstrating that they closely align with the minimum theoretical complexity for the problems at hand. This optimal nature of our solution ensures efficient and secure collaborative geometric computations.

Keywords: cryptography, secure multiparty computation, solid geometry, protocol, simulation paradigm

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Authors: O. Iyare, A. H. Afolayan, O. T. Oluwadare, B. K. Alese

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Access to advanced medical services has been one of the medical challenges faced by our present society especially in distant geographical locations which may be inaccessible. Then the need for telemedicine arises through which live videos of a doctor can be streamed to a patient located anywhere in the world at any time. Patients’ medical records contain very sensitive information which should not be made accessible to unauthorized people in order to protect privacy, integrity and confidentiality. This research work focuses on a more robust security measure which is biometric (fingerprint) as a form of access control to data of patients by the medical specialist/practitioner.

Keywords: biometrics, telemedicine, privacy, patient information

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Authors: Sarthak Mishra, Astha Sinha

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There’s no doubt about the convenience of making commercial and business transactions over the Internet under the new business model known as the e-Commerce. The term 'Electronic commerce' or e-Commerce refers to the use of an electronic medium to carry out commercial transactions. E-Commerce is one of the parts of Information Science framework and its uses are gradually becoming popular. Thus, the threat of security issues in Information Science has now become an important subject of discussion amongst the concerned users. These two issues i.e. security and privacy are required to be looked into through social, organizational, technical and economic perspectives. The current paper analyses the effect of these two issues in the arena of e-commerce. Here, no specification has been discussed rather an attempt has been made to provide a general overview. Further, attempts have been made to discuss the security and privacy issues in relation to the E-Commerce financial transactions. We shall also discuss in particular different steps required to be taken before online shopping and also shall discuss the purpose of security and privacy in E-Commerce and why it has currently become the need of the present hour. Lastly, an attempt has been made to discuss the plausible future course of development of this practice and its impact upon the global economy and if any changes should be bought about to ensure a smooth evolution of the practice. This paper has adopted a descriptive methodology to undertake its major area of study, wherein the major source of information has been via the secondary resources. Also, the study is of a comparative nature wherein the position of the various national regimes have compared with regards to the research question.

Keywords: business-business transaction (B2B), business-consumer transaction (B2C), e-commerce, online transaction, privacy and security threats

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Authors: Derick M. Rakgoale, Topside E. Mathonsi, Vusumuzi Malele

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Cloud computing offers distributed online and on-demand computational services from anywhere in the world. Cloud computing services have grown immensely over the past years, especially in the past year due to the Coronavirus pandemic. Cloud computing has changed the working environment and introduced work from work phenomenon, which enabled the adoption of technologies to fulfill the new workings, including cloud services offerings. The increased cloud computing adoption has come with new challenges regarding data privacy and its integrity in the cloud environment. Previously advanced encryption algorithms failed to reduce the memory space required for cloud computing performance, thus increasing the computational cost. This paper reviews the existing encryption algorithms used in cloud computing. In the future, artificial neural networks (ANN) algorithm design will be presented as a security solution to ensure data integrity, confidentiality, privacy, and availability of user data in cloud computing. Moreover, MATLAB will be used to evaluate the proposed solution, and simulation results will be presented.

Keywords: cloud computing, data integrity, confidentiality, privacy, availability

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Authors: Zaide Montes Ortiz, Jorge Alberto Molina, Alejandro Reyes

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Insects are extremely successful organisms. A sophisticated olfactory system is in part responsible for their survival and reproduction. The detection of volatile organic compounds can positively or negatively affect many behaviors in insects. Compounds such as carbon dioxide (CO2), ammonium, indol, and lactic acid are essential for many species of mosquitoes like Anopheles gambiae in order to locate vertebrate hosts. For instance, in A. gambiae, the olfactory receptor AgOR2 is strongly activated by indol, which accounts for almost 30% of human sweat. On the other hand, in some insects of agricultural importance, the detection and identification of pheromone receptors (PRs) in lepidopteran species has become a promising field for integrated pest management. For example, with the disruption of the pheromone receptor, BmOR1, mediated by transcription activator-like effector nucleases (TALENs), the sensitivity to bombykol was completely removed affecting the pheromone-source searching behavior in male moths. Then, the detection and identification of olfactory receptors in the genomes of insects is fundamental to improve our understanding of the ecological interactions, and to provide alternatives in the integrated pests and vectors management. Hence, the objective of this study is to propose a bioinformatic workflow to enhance the detection and identification of potential olfactory receptors in genomes of relevant insects. Applying Hidden Markov models (Hmms) and different computational tools, potential candidates for pheromone receptors in Tuta absoluta were obtained, as well as potential carbon dioxide receptors in Rhodnius prolixus, the main vector of Chagas disease. This study showed the validity of a bioinformatic workflow with a potential to improve the identification of certain olfactory receptors in different orders of insects.

Keywords: bioinformatic workflow, insects, olfactory receptors, protein prediction

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Authors: Shayan Mohajer Hamidi

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Federated Learning (FL) has emerged as a promising paradigm for training machine learning models on distributed data without the need for centralized data aggregation. In the realm of wireless communications, FL has the potential to leverage the vast amounts of data generated by wireless devices to improve model performance and enable intelligent applications. However, the fairness aspect of FL in wireless communications remains largely unexplored. This abstract presents an idea for fair federated learning in wireless communications, addressing the challenges of imbalanced data distribution, privacy preservation, and resource allocation. Firstly, the proposed approach aims to tackle the issue of imbalanced data distribution in wireless networks. In typical FL scenarios, the distribution of data across wireless devices can be highly skewed, resulting in unfair model updates. To address this, we propose a weighted aggregation strategy that assigns higher importance to devices with fewer samples during the aggregation process. By incorporating fairness-aware weighting mechanisms, the proposed approach ensures that each participating device's contribution is proportional to its data distribution, thereby mitigating the impact of data imbalance on model performance. Secondly, privacy preservation is a critical concern in federated learning, especially in wireless communications where sensitive user data is involved. The proposed approach incorporates privacy-enhancing techniques, such as differential privacy, to protect user privacy during the model training process. By adding carefully calibrated noise to the gradient updates, the proposed approach ensures that the privacy of individual devices is preserved without compromising the overall model accuracy. Moreover, the approach considers the heterogeneity of devices in terms of computational capabilities and energy constraints, allowing devices to adaptively adjust the level of privacy preservation to strike a balance between privacy and utility. Thirdly, efficient resource allocation is crucial for federated learning in wireless communications, as devices operate under limited bandwidth, energy, and computational resources. The proposed approach leverages optimization techniques to allocate resources effectively among the participating devices, considering factors such as data quality, network conditions, and device capabilities. By intelligently distributing the computational load, communication bandwidth, and energy consumption, the proposed approach minimizes resource wastage and ensures a fair and efficient FL process in wireless networks. To evaluate the performance of the proposed fair federated learning approach, extensive simulations and experiments will be conducted. The experiments will involve a diverse set of wireless devices, ranging from smartphones to Internet of Things (IoT) devices, operating in various scenarios with different data distributions and network conditions. The evaluation metrics will include model accuracy, fairness measures, privacy preservation, and resource utilization. The expected outcomes of this research include improved model performance, fair allocation of resources, enhanced privacy preservation, and a better understanding of the challenges and solutions for fair federated learning in wireless communications. The proposed approach has the potential to revolutionize wireless communication systems by enabling intelligent applications while addressing fairness concerns and preserving user privacy.

Keywords: federated learning, wireless communications, fairness, imbalanced data, privacy preservation, resource allocation, differential privacy, optimization

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Authors: Pantaleon Lutta, Mohamed Sedky, Mohamed Hassan

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The inability of organizations to put in place management control measures for Internet of Things (IoT) complexities persists to be a risk concern. Policy makers have been left to scamper in finding measures to combat these security and privacy concerns. IoT forensics is a cumbersome process as there is no standardization of the IoT products, no or limited historical data are stored on the devices. This paper highlights why IoT forensics is a unique adventure and brought out the legal challenges encountered in the investigation process. A quadrant model is presented to study the conflicting aspects in IoT forensics. The model analyses the effectiveness of forensic investigation process versus the admissibility of the evidence integrity; taking into account the user privacy and the providers’ compliance with the laws and regulations. Our analysis concludes that a semi-automated forensic process using machine learning, could eliminate the human factor from the profiling and surveillance processes, and hence resolves the issues of data protection (privacy and confidentiality).

Keywords: cloud forensics, data protection Laws, GDPR, IoT forensics, machine Learning

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Authors: João Filipe Papel, Tatsuji Munaka

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With society's aging and the number of elderly with dementia rising, researchers have been actively studying how to support the elderly in the early stages of dementia with the objective of allowing them to have a better life quality and as much as possible independence. To make this possible, most researchers in this field are using the Internet Of Things to monitor the elderly activities and assist them in performing them. The most common sensor used to monitor the elderly activities is the Camera sensor due to its easy installation and configuration. The other commonly used sensor is the sound sensor. However, we need to consider privacy when using these sensors. This research aims to develop a system capable of predicting the early stages of dementia based on monitoring and controlling the elderly activities of daily living. To make this system possible, some issues need to be addressed. First, the issue related to elderly privacy when trying to detect their Activities of Daily Living. Privacy when performing detection and monitoring Activities of Daily Living it's a serious concern. One of the purposes of this research is to achieve this detection and monitoring without putting the privacy of the elderly at risk. To make this possible, the study focuses on using an approach based on using Magnet Sensors to collect binary data. The second is to use the data collected by monitoring Activities of Daily Living to predict the early stages of Dementia. To make this possible, the research team suggests developing a proprietary ontology combined with both data-driven and knowledge-driven.

Keywords: dementia, activity recognition, magnet sensors, ontology, data driven and knowledge driven, IoT, activities of daily living

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Authors: Tolga Yazıcı

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As a matter of the fact that online social networks like Twitter, Facebook and MySpace have experienced an extensive growth in recent years. Social media offers individuals with a tool for communicating and interacting with one another. These social networks enable people to stay in touch with other people and express themselves. This process makes the users of online social networks active creators of content rather than being only consumers of traditional media. That’s why millions of people show strong desire to learn the methods and tools of digital content production and necessary communication skills. However, the booming interest in communication and interaction through online social networks and high level of eagerness to invent and implement the ways to participate in content production raise some privacy and security concerns. This presentation aims to open the assumed revolutionary, democratic and liberating nature of the online social media up for discussion by reviewing some recent political developments in Turkey. Firstly, the role of Internet and online social networks in mobilizing collective movements through social interactions and communications will be questioned. Secondly, some cases from Gezi and Okmeydanı Protests and also December 17-25 period will be presented in order to illustrate misinformation and manipulation in social media and violation of individual privacy through online social networks in order to damage social unity and stability contradictory to democratic nature of online social networking.

Keywords: online social media networks, democratic participation, social movements, social polarization, privacy of individuals, Turkey

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Authors: Eugenio Ferrer Santiago

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The growing complexities of the modern world on high-end gadgets, software applications, scams, identity theft, and Artificial Intelligence (AI) make the “uninformed” the weak and vulnerable to be victims of cybercrimes. Artificial Intelligence is not a new thing in our daily lives; the principles of database management, logical programming, and garbage in and garbage out are all connected to AI. The Philippines had in place legal safeguards against the abuse of cyberspace, but self-regulation of key industry players and self-protection by individuals are primordial to attain the success of these initiatives. Data protection, Data Privacy, and Research Ethics must work hand in hand during the policy process in the course of urban planning practice in different environments. This paper focuses on the interconnection of data protection, data privacy, and research ethics in coming up with clear-cut policies against perpetrators in the urban planning professional practice relevant in sustainable communities and smart cities. This paper shall use expository methodology under qualitative research using secondary data from related literature, interviews/blogs, and the World Wide Web resources. The claims and recommendations of this paper will help policymakers and implementers in the policy cycle. This paper shall contribute to the body of knowledge as a simple treatise and communication channel to the reading community and future researchers to validate the claims and start an intellectual discourse for better knowledge generation for the good of all in the near future.

Keywords: data privacy, data protection, urban planning, research ethics

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Authors: Martin Georgiev, Milena Nanova, Damyan Damov

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Architects, engineers, and developers need to analyse and implement a wide spectrum of data in different formats, if they want to produce viable residential developments. Usually, this data comes from a number of different sources and is not well structured. The main objective of this research project is to provide parametric tools working with real geodesic data that can generate residential solutions. Various codes, regulations and design constraints are described by variables and prioritized. In this way, we establish a common workflow for architects, geodesists, and other professionals involved in the building and investment process. This collaborative medium ensures that the generated design variants conform to various requirements, contributing to a more streamlined and informed decision-making process. The quantification of distinctive characteristics inherent to typical residential structures allows a systematic evaluation of the generated variants, focusing on factors crucial to designers, such as daylight simulation, circulation analysis, space utilization, view orientation, etc. Integrating real geodesic data offers a holistic view of the built environment, enhancing the accuracy and relevance of the design solutions. The use of generative algorithms and parametric models offers high productivity and flexibility of the design variants. It can be implemented in more conventional CAD and BIM workflow. Experts from different specialties can join their efforts, sharing a common digital workspace. In conclusion, our research demonstrates that a generative parametric approach based on real geodesic data and collaborative decision-making could be introduced in the early phases of the design process. This gives the designers powerful tools to explore diverse design possibilities, significantly improving the qualities of the building investment during its entire lifecycle.

Keywords: architectural design, residential buildings, urban development, geodesic data, generative design, parametric models, workflow optimization

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Authors: Pankhudi Khandelwal

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The revenue models of digital giants such as Facebook and Google, use targeted advertising for revenues. Such a model requires huge amounts of consumer data. While the data protection law deals with the protection of personal data, however, this data is acquired by the companies on the basis of consent, performance of a contract, or legitimate interests. This paper analyses the role that competition law can play in evading these loopholes for the protection of data and privacy of online consumers. Digital markets have certain distinctive features such as network effects and feedback loop, which gives incumbents of these markets a first-mover advantage. This creates a situation where the winner takes it all, thus creating entry barriers and concentration in the market. It has been also seen that this dominant position is then used by the undertakings for leveraging in other markets. This can be harmful to the consumers in form of less privacy, less choice, and stifling innovation, as seen in the cases of Facebook Cambridge Analytica, Google Shopping, and Google Android. Therefore, the article aims to provide a legal framework wherein the data protection law and competition law can come together to provide a balance in regulating digital markets. The issue has become more relevant in light of the Facebook decision by German competition authority, where it was held that Facebook had abused its dominant position by not complying with data protection rules, which constituted an exploitative practice. The paper looks into the jurisdictional boundaries that the data protection and competition authorities can work from and suggests ex ante regulation through data protection law and ex post regulation through competition law. It further suggests a change in the consumer welfare standard where harm to privacy should be considered as an indicator of low quality.

Keywords: data protection, dominance, ex ante regulation, ex post regulation

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Authors: Danilo Di Donato

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The continuous new releases of free and open source software (FOSS) and the high costs of proprietary software -whose monopoly is characterized by closed codes and the low level of implementation and customization of software by end-users- impose a reflection on possible tools that can be chosen and adopted for the design and the representation of new steel constructions. The paper aims to show experimentation carried out to verify the actual potential and the effective applicability of FOSS supports to the BIM modeling of steel structures, particularly considering the goal of a possible workflow in order to achieve high level of development (LOD); allow effective interchange methods between different software. To this end, the examined software packages are those with open source or freeware licenses, in order to evaluate their use in architectural praxis. The test has primarily involved the experimentation of Freecad -the only Open Source software that allows a complete and integrated BIM workflow- and then the results have been compared with those of two proprietary software, Sketchup and TeklaBim Sight, which are released with a free version, but not usable for commercial purposes. The experiments carried out on Open Source, and freeware software was then compared with the outcomes that are obtained by two proprietary software, Sketchup Pro and Tekla Structure which has special modules particularly addressed to the design of steel structures. This evaluation has concerned different comparative criteria, that have been defined on the basis of categories related to the reliability, the efficiency, the potentiality, achievable LOD and user-friendliness of the analyzed software packages. In order to verify the actual outcomes of FOSS BIM for the steel structure projects, these results have been compared with a simulation related to a real case study and carried out with a proprietary software BIM modeling. Therefore, the same design theme, the project of a shelter of public space, has been developed using different software. Therefore the purpose of the contribution is to assess what are the developments and potentialities inherent in FOSS BIM, in order to estimate their effective applicability to professional practice, their limits and new fields of research they propose.

Keywords: BIM, steel buildings, FOSS, LOD

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Authors: Mohamed Saad, Huda Ismail

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The purpose of this research is to examine the impact of cryptocurrency classification on money laundering crimes and to analyze how the preferences of criminals differ according to the type of digital currency used. Specifically, we aim to explore the roles of stablecoins, utility coins, and privacy tokens in facilitating or hindering money laundering activities and to identify the key factors that influence the choices of criminals in using these cryptocurrencies. To achieve our research objectives, we used a dataset for the most highly traded cryptocurrencies (32 currencies) that were published on the coin market cap for 2022. In addition to conducting a comprehensive review of the existing literature on cryptocurrency and money laundering, with a focus on stablecoins, utility coins, and privacy tokens, Furthermore, we conducted several Multivariate analyses. Our study reveals that the classification of cryptocurrency plays a significant role in money laundering activities, as criminals tend to prefer certain types of digital currencies over others, depending on their specific needs and goals. Specifically, we found that stablecoins are more commonly used in money laundering due to their relatively stable value and low volatility, which makes them less risky to hold and transfer. Utility coins, on the other hand, are less frequently used in money laundering due to their lack of anonymity and limited liquidity. Finally, privacy tokens, such as Monero and Zcash, are increasingly becoming a preferred choice among criminals due to their high degree of privacy and untraceability. In summary, our study highlights the importance of understanding the nuances of cryptocurrency classification in the context of money laundering and provides insights into the preferences of criminals in using digital currencies for illegal activities. Based on our findings, our recommendation to the policymakers is to address the potential misuse of cryptocurrencies for money laundering. By implementing measures to regulate stable coins, strengthening cross-border cooperation, fostering public-private partnerships, and increasing cooperation, policymakers can help prevent and detect money laundering activities involving digital currencies.

Keywords: crime, cryptocurrency, money laundering, tokens.

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Authors: Julio Manuel De Luis Ruiz, Javier Sedano Cibrián, RubéN Pérez Álvarez, Raúl Pereda García, Felipe Piña García

Abstract:

Nowadays it is common to resort to aerial photography to carry out the prospection and/or exploration of archaeological sites. In this sense, the classic 3D models are being applied to investigate the direction towards which the generally subterranean structures of an archaeological site may continue and therefore, to help in making the decisions that define the location of new excavations. In recent years, Unmanned Aerial Vehicles (UAVs) have been applied as the vehicles that carry the sensor. This implies certain advantages, such as the possibility of including low-cost sensors, given that these vehicles can carry the sensor at relatively low altitudes. Due to this, low-cost dual sensors have recently begun to be used. This new equipment can collaborate with classic Digital Elevation Models (DEMs) in the exploration of archaeological sites, but this entails the need for a methodological setting to optimise the acquisition, processing and exploitation of the information provided by low-cost dual sensors. This research focuses on the design of an appropriate workflow to obtain 3D models with low-cost sensors carried on UAVs, both in the RGB and thermal domains. All the foregoing has been applied to the archaeological site of Juliobriga, located in Cantabria (Spain).

Keywords: process optimization, RGB models, thermal models, , UAV, workflow

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Authors: Umair Shafique, Hafiz Usman Zia, Fiaz Majeed, Samina Naz, Javeria Ahmed, Maleeha Zainab

Abstract:

The Internet of Things (IoT) has become a hot topic for the last couple of years. This innovative technology has shown promising progress in various areas, and the world has witnessed exponential growth in multiple application domains. Researchers are working to investigate its aptitudes to get the best from it by harnessing its true potential. But at the same time, IoT networks open up a new aspect of vulnerability and physical threats to data integrity, privacy, and confidentiality. It's is due to centralized control, data silos approach for handling information, and a lack of standardization in the IoT networks. As we know, blockchain is a new technology that involves creating secure distributed ledgers to store and communicate data. Some of the benefits include resiliency, integrity, anonymity, decentralization, and autonomous control. The potential for blockchain technology to provide the key to managing and controlling IoT has created a new wave of excitement around the idea of putting that data back into the hands of the end-users. In this manuscript, we have proposed a model that combines blockchain and IoT networks to address potential security and privacy issues in the healthcare domain. Then we try to describe various application areas, challenges, and future directions in the healthcare sector where blockchain platforms merge with IoT networks.

Keywords: IoT, blockchain, cryptocurrency, healthcare, consensus, data

Procedia PDF Downloads 142

Authors: Ekrem Canli, Thomas Glade

Abstract:

The precise prediction of rainfall in space and time is a key element to most landslide early warning systems. Unfortunately, the spatial variability of rainfall in many early warning applications is often disregarded. A common simplification is to use uniformly distributed rainfall to characterize aerial rainfall intensity. With spatially differentiated rainfall information, real-time comparison with rainfall thresholds or the implementation in process-based approaches might form the basis for improved landslide warnings. This study suggests an automated workflow from the hourly, web-based collection of rain gauge data to the generation of spatially differentiated rainfall predictions based on kriging. Because the application of kriging is usually a labor intensive task, a simplified and consequently automated variogram modeling procedure was applied to up-to-date rainfall data. The entire workflow was carried out purely with open source technology. Validation results, albeit promising, pointed out the challenges that are involved in pure distance based, automated geostatistical interpolation techniques for ever-changing environmental phenomena over short temporal and spatial extent.

Keywords: kriging, landslide early warning system, spatial rainfall prediction, variogram modelling, web scraping

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Authors: Virpi Oksman

Abstract:

Drones are new phenomenon in public spaces. Adoption of this kind of new technologies requires public acceptance. Drones and other unmanned aerial systems may have various impacts on people’s living environments, and the public is exposed to possible disadvantages of drones. Public acceptance may be expressed as positive or negative attitude by majority of the citizens towards the new technology or service or as rapid adoption of it in everyday life. In various parts of the globe, in cities and in rural areas, drones as emerging technologies are perceived quite differently. Public acceptance studies of drones have been conducted mostly in highly urbanized environments like in Singapore and in European cities. This paper presents results of a Nordic survey study (N=1000) conducted in Sweden and in Finland. The survey aims at understanding the level of acceptance of different uses of drones in public spaces and the main concerns and benefits related to emerging UAM technologies. The study shows that even though the general attitude towards drones is quite positive, privacy and safety, and noise levels are the main concerns by Nordic citizens. Also, for what purpose and by whom the drones are operated affects the acceptability significantly. The study concludes, that there is need for regulations that safeguard public interests. In addition, considering privacy in design, and quiet environmentally friendly drones support public acceptance of drones.

Keywords: public acceptance, privacy, safety, survey

Procedia PDF Downloads 141

Authors: Nisreen Ardda

Abstract:

Fenestrations are one of the main building envelope elements that play an important role in home social-ecological l factors. They play a vital role in providing natural lighting and ventilation, visual, thermal, and acoustical comfort, and also provide weather-tightness, privacy, a feeling of openness. In most home buildings, fenestrations are controlled manually by the occupants, which significantly impacts occupants' comfort and energy use. Culture plays a central role in the Palestinians window operation behavior. Improved windows design that provides the desired privacy while maintaining the appropriate function of fenestration (natural lighting, thermal comfort, and visual openness) is becoming a necessity. Therefore, this paper proposes a window typology to achieve the social and environmental factors in residential buildings in the West Bank. The window typology and reference building were designed in Rivet 2021, and natural ventilation was carried out in Design Builder 4.3.0.039. The results showed that the proposed typology provides the desired privacy and the feeling of openness without compromising natural ventilation as the existing window did.

Keywords: window design, passive design, sustainable built environment, building material

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Authors: Swati Kishor Zode, Rahul Ambekar

Abstract:

Data mining is the extraction of fascinating examples on the other hand information from enormous measure of information and choice is made as indicated by the applicable information extracted. As of late, with the dangerous advancement in internet, stockpiling of information and handling procedures, privacy preservation has been one of the major (higher) concerns in data mining. Various techniques and methods have been produced for protection saving data mining. In the situation of Clinical Decision Support System, the choice is to be made on the premise of the data separated from the remote servers by means of Internet to diagnose the patient. In this paper, the fundamental thought is to build the precision of Decision Support System for multiple diseases for different maladies and in addition protect persistent information while correspondence between Clinician side (Client side) also, the Server side. A privacy preserving protocol for clinical decision support network is proposed so that patients information dependably stay scrambled amid diagnose prepare by looking after the accuracy. To enhance the precision of Decision Support System for various malady C5.0 classifiers and to save security, a Homomorphism encryption algorithm Paillier cryptosystem is being utilized.

Keywords: classification, homomorphic encryption, clinical decision support, privacy

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Authors: Huang Dennis, Aurelio Aziel, Burra Venkata Durga Kumar

Abstract:

Nowadays, smartphones and mobile operating systems have been popularly widespread in our daily lives. As people use smartphones, they tend to store more private and essential data on their devices, because of this it is very important to develop more secure mobile operating systems and cloud storage to secure the data. However, several factors can cause security risks in mobile operating systems such as malware, malicious app, phishing attacks, ransomware, and more, all of which can cause a big problem for users as they can access the user's private data. Those problems can cause data loss, financial loss, identity theft, and other serious consequences. Other than that, during the pandemic, people will use their mobile devices more and do all sorts of transactions online, which may lead to more victims of online scams and inexperienced users being the target. With the increase in attacks, researchers have been actively working to develop several countermeasures to enhance the security of operating systems. This study aims to provide an overview of the security and privacy issues in mobile operating systems, identifying the potential risk of operating systems, and the possible solutions. By examining these issues, we want to provide an easy understanding to users and researchers to improve knowledge and develop more secure mobile operating systems.

Keywords: mobile operating system, security, privacy, Malware

Procedia PDF Downloads 48