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- Type:
- Article
- Description/Abstract:
- This paper looks at the opportunities and challenges of implementing blockchain technology across the medical sector and provides a clear view which can enable blockchain for more extents. After a notable research on underlying blockchain technology which offers distributed governance, immutable audit trail, provenance of data, robustness and privacy, we contrasted blockchain innovations and identified prominent applications of it in historically decentralized healthcare sectors. As the healthcare industry faces many challenges like unauthorised data sharing, lack of data transparency, ransomware, data breaches and cyber crimes, blockchain is one of the best ways to enhance data sharing and to mitigate prominent cyber crimes. By proper designing of a decentralized and immutable blockchain network where the data is dispersed among credentialed social insurance experts guarantees that cybercriminals cannot touch single patient’s confidential data, which facilitates encryption or cryptography of personal data where no patient’s emergency data is at extreme hazard. Blockchain trust-worthy cloud is one of the most powerful and secure ways of storing high confidential data. After analysing Blockchain implementations and identifying its potential in healthcare, we conclude with several promising directions for future research.
- Creator/Author:
- Ponnakanti, Hari Priya; Ozer, Murat, and Gonen, Bilal
- Submitter:
- Jess Kropczynski
- Date Uploaded:
- 05/15/2020
- Date Modified:
- 05/15/2020
- Date Created:
- 2020-04-14
- License:
- All rights reserved
- Type:
- Article
- Description/Abstract:
- National Institute of Standards and Technology (NIST) recommends that organizations perform cyber risk assessments regularly to identify security vulnerabilities and to control levels of exposure to threats. We discuss a method to customize the ranking of cyber threats based on the organization’s maturity level of implementing NIST controls and we use FAIR model’s LEF component as a measure of the severity of cyber threats. The methodology integrates NIST maturity levels to calculate the resistance strength factor and produce the LEF values for each threat. The LEF value is then used to represent the severity level of the threat to the specific organization. This hybrid risk assessment approach will help stakeholders make data-informed decisions on improving security measures and provide accurate values that represent the current security state of their organization.
- Creator/Author:
- Bakare, Adeyinka and Said, Hazem
- Submitter:
- Jess Kropczynski
- Date Uploaded:
- 05/15/2020
- Date Modified:
- 05/15/2020
- Date Created:
- 2020-04-14
- License:
- All rights reserved
- Type:
- Article
- Description/Abstract:
- Signature-based intrusion detection methods report high accuracy with a low false alarm rate. However, they do not perform well when faced with new or emerging threats. This work focuses on anomaly-based data driven methods to identify potential zero-day-attacks using a specific class of neural networks known as the autoencoder.
- Creator/Author:
- Li, Chengcheng; Lee, Kijung; Mathur, Nitin, and Gonen, Bilal
- Submitter:
- Jess Kropczynski
- Date Uploaded:
- 05/15/2020
- Date Modified:
- 05/15/2020
- Date Created:
- 2020-04-14
- License:
- All rights reserved
- Type:
- Article
- Description/Abstract:
- Previous studies have offered a variety of explanations on the relationship between democracy and the internet. Some argue that with free access to information, knowledge sharing without any constraint, and the spread of political knowledge, the internet will help change people’s political attitudes and spread democracy. Other studies found that authoritarian regimes by censoring the internet, tracking the political activist, prosecuting the dissidents, and using the internet to spread their propaganda limit the democratization. Also, some studies explored the effects of diffusion of false news through the internet and especially via social media. However, most of these studies concentrate on regions, specific states or authoritarian regimes. No study has investigated the influence of the internet in partly free countries defined by the Freedom House. Moreover, very little is known about the effects of online censorship on the development, stagnation, or decline of democracy. To fully understand the impact of the internet and online censorship on democratization in partly free countries, we must explore these relationships in these countries. Drawing upon the International Telecommunication Union, Freedom House, and World Bank reports and using machine learning methods, this study sheds new light on the effects of the internet on democratization in partly free countries. The findings suggest that internet penetration and online censorship both have a negative impact on democracy scores and the internet’s effect on democracy scores is conditioned by online censorship. Moreover, results from random forest suggest that online censorship is the most important variable followed by governance index and education on democracy scores.
- Creator/Author:
- Varlioglu, M. Said and Sagir, Mustafa
- Submitter:
- Jess Kropczynski
- Date Uploaded:
- 05/15/2020
- Date Modified:
- 05/15/2020
- Date Created:
- 2020-04-14
- License:
- All rights reserved
- Type:
- Article
- Description/Abstract:
- The paper focuses on exploring the social networks of technology caregivers and caregivees and also work on learning their preferred mode of information exchange. Responses from the participants of the study will throw light on the relationships between different efficacies (discussed in detail in the paper) that may have an impact on an individual’s decision. Participant’s responses are recorded through well constructed surveys that have been distributed around by word of mouth or specific social media platforms which will also prove if being a power user has any effect on the end result. The responses will be analyzed and the various efficacy constructs such as self efficacy, community collective efficacy will be kept in mind.
- Creator/Author:
- Kaushik, Sanjana and Elrod, Nathan J.
- Submitter:
- Jess Kropczynski
- Date Uploaded:
- 05/15/2020
- Date Modified:
- 05/15/2020
- Date Created:
- 2020-04-14
- License:
- All rights reserved
- Type:
- Article
- Description/Abstract:
- This study proposes enhanced oversight of smart homes by leveraging the social networks of homeowners to co-monitor for emergencies, while being mindful of privacy preserving features necessary for adoption. A pilot co-design workshop was conducted to determine features for co-monitoring. A group of four participants provided early findings and informed modifications to study design, and new insights for user behavior were emphasized. By refining the study design, we hope to better target users’ tacit knowledge in future workshops. Early findings include the users’ need for more than simply sharing access to a camera during an emergency in the home; users desired control over the microphone, the camera video stream, and the length of time. We believe this work will contribute to a broader understanding of features that better meet the needs and goals of smart device owners to enable co-monitoring.
- Creator/Author:
- Brandopadhayay, Rajdeep; Halse, Shane; Elrod, Nathan J.; Kropczynski, Jess, and Burden, Eric
- Submitter:
- Jess Kropczynski
- Date Uploaded:
- 05/15/2020
- Date Modified:
- 05/15/2020
- Date Created:
- 2020-04-14
- License:
- All rights reserved
- Type:
- Article
- Description/Abstract:
- This is an ongoing research project focused on creating a framework for capturing various artifacts concerning Internet of Things devices. Research has shown a severe lack of frameworks focusing on collecting data from and about IoT devices. Mozilla’s WebThings Gateway focuses on collecting this information from the devices. This project expects to find methods of IoT data collection through a proposed test-bed utilizing the WebThings Gateway.
- Creator/Author:
- Mahajan, Pranav
- Submitter:
- Jess Kropczynski
- Date Uploaded:
- 05/15/2020
- Date Modified:
- 05/15/2020
- Date Created:
- 2020-04-14
- License:
- All rights reserved
- Type:
- Article
- Description/Abstract:
- Open Government Data (OGD) promotes transparency, innovation, and value creation that makes information gathered by the government about the city and community open to all. The City of Cincinnati Open Government Data Portal allows citizens to access local data as part of a local OGD initiative. Although these datasets are available and are used by a broad audience, little is known about how users engage with this data and the general usability of the platforms. To learn more about this audience, this study is conducted in two steps 1)- a think-aloud activity and 2)- an online survey. Through these activities, we aim to gather information about how the users are interacting with the available data and for what purpose are they interacting with different sections of the portal. After gathering relevant data from the think-aloud activity, we aim to generate a questionnaire by analyzing all the information collected in the previous event at a larger scale. Using a web-based survey shared with individuals via Qualtrics, we will explore the use of the portal to gain more insight and knowledge on user requirements and their suggestions. The endpoint of this study is to develop insights that will help us understand user expectations and how changes could benefit the portal.
- Creator/Author:
- Murthy, Svati Sundara
- Submitter:
- Jess Kropczynski
- Date Uploaded:
- 05/15/2020
- Date Modified:
- 05/15/2020
- Date Created:
- 2020-04-14
- License:
- All rights reserved
- Type:
- Article
- Description/Abstract:
- Internet of Things (IoT) enabled smart homes to have made our daily lives easier, but these conveniences have also introduced security concerns. IoT devices hold security risks as well as smart home hubs and gateways. Gateways present a centralized point of communication among devices that can create a backdoor into network data for hackers but also present a detection opportunity. Intrusion detection is a common way to detect anomalies in network traffic. This paper introduces early work on an intrusion detection system (IDS) by detecting anomalies in the smart home network using Extreme Learning Machine and Artificial Immune System (AIS ELM). AIS uses the clonal Algorithm for the optimization of the input parameters, and ELM analyzes the input parameter for better convergence in detecting anomalous activity. The larger goal of this work is to apply this approach to a smart home network gateway and combined it with a push notification system that will allow the homeowner to identify any abnormalities in the smart home network and take appropriate action.
- Creator/Author:
- Alalade, Emmanuel Dare
- Submitter:
- Jess Kropczynski
- Date Uploaded:
- 05/15/2020
- Date Modified:
- 05/15/2020
- Date Created:
- 2020-04-14
- License:
- All rights reserved
- Type:
- Article
- Description/Abstract:
- Devices in the Internet of Things (IoT) have enhanced our ability to automate functions in smart homes and increased our ability to monitor day to day activities regardless of whether we are in our home. Despite these benefits of IoT devices, it is the case that notifications about threats to our home when we are away are typically only sent to one or two people within the home. We proposed enhanced monitoring of threats by allowing temporary access to IoT devices to extended networks of homeowners in situations where primary IoT device owners are not able to address a smartphone notification quickly.
- Creator/Author:
- Agrawal, Dev
- Submitter:
- Jess Kropczynski
- Date Uploaded:
- 05/15/2020
- Date Modified:
- 05/15/2020
- Date Created:
- 2019-04-11
- License:
- All rights reserved