7,740 research outputs found

    Predictive Analytics In Higher Education: Five Guiding Practices for Ethical Use

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    Without ethical practices, student data could be used to curtail academic success rather than help ensure it. For example, without a clear plan in place, an institution could use predictive analytics to justify using fewer resources to recruit low-income students because their chances of enrolling are less sure than for more affluent prospective students. In this report, New America lays out important questions to consider as administrators formulate how to use predictive analytics ethically

    Assessing and augmenting SCADA cyber security: a survey of techniques

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    SCADA systems monitor and control critical infrastructures of national importance such as power generation and distribution, water supply, transportation networks, and manufacturing facilities. The pervasiveness, miniaturisations and declining costs of internet connectivity have transformed these systems from strictly isolated to highly interconnected networks. The connectivity provides immense benefits such as reliability, scalability and remote connectivity, but at the same time exposes an otherwise isolated and secure system, to global cyber security threats. This inevitable transformation to highly connected systems thus necessitates effective security safeguards to be in place as any compromise or downtime of SCADA systems can have severe economic, safety and security ramifications. One way to ensure vital asset protection is to adopt a viewpoint similar to an attacker to determine weaknesses and loopholes in defences. Such mind sets help to identify and fix potential breaches before their exploitation. This paper surveys tools and techniques to uncover SCADA system vulnerabilities. A comprehensive review of the selected approaches is provided along with their applicability

    SCADA System Testbed for Cybersecurity Research Using Machine Learning Approach

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    This paper presents the development of a Supervisory Control and Data Acquisition (SCADA) system testbed used for cybersecurity research. The testbed consists of a water storage tank's control system, which is a stage in the process of water treatment and distribution. Sophisticated cyber-attacks were conducted against the testbed. During the attacks, the network traffic was captured, and features were extracted from the traffic to build a dataset for training and testing different machine learning algorithms. Five traditional machine learning algorithms were trained to detect the attacks: Random Forest, Decision Tree, Logistic Regression, Naive Bayes and KNN. Then, the trained machine learning models were built and deployed in the network, where new tests were made using online network traffic. The performance obtained during the training and testing of the machine learning models was compared to the performance obtained during the online deployment of these models in the network. The results show the efficiency of the machine learning models in detecting the attacks in real time. The testbed provides a good understanding of the effects and consequences of attacks on real SCADA environmentsComment: E-Preprin

    After the Gold Rush: The Boom of the Internet of Things, and the Busts of Data-Security and Privacy

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    This Article addresses the impact that the lack of oversight of the Internet of Things has on digital privacy. While the Internet of Things is but one vehicle for technological innovation, it has created a broad glimpse into domestic life, thus triggering several privacy issues that the law is attempting to keep pace with. What the Internet of Things can reveal is beyond the control of the individual, as it collects information about every practical aspect of an individual’s life, and provides essentially unfettered access into the mind of its users. This Article proposes that the federal government and the state governments bend toward consumer protection while creating a cogent and predictable body of law surrounding the Internet of Things. Through privacy-by-design or self-help, it is imperative that the Internet of Things—and any of its unforeseen progeny—develop with an eye toward safeguarding individual privacy while allowing technological development

    An Empirical Assessment of Senior Citizens’ Cybersecurity Awareness, Computer Self-Efficacy, Perceived Risk of Identity Theft, Attitude, and Motivation to Acquire Cybersecurity Skills

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    Cyber-attacks on Internet users have caused billions of dollars in losses annually. Cybercriminals launch attacks via threat vectors such as unsecured wireless networks and phishing attacks on Internet users who are usually not aware of such attacks. Senior citizens are one of the most vulnerable groups who are prone to cyber-attacks, and this is largely due to their limited cybersecurity awareness and skills. Within the last decade, there has been a significant increase in Internet usage among senior citizens. It was documented that senior citizens had the greatest rate of increase in Internet usage over all the other age groups during the past decade. However, whenever senior citizens use the Internet, they are being targeted and exploited particularly for financial crimes, with estimation that one in five becoming a victim of financial fraud, costing more than $2.6 billion per year. Increasing the cybersecurity awareness and skills levels of Internet users have been recommended to mitigate the effects of cyber-attacks. However, it is unclear what motivates Internet users, particularly senior citizens, to acquire cybersecurity skills so that they can identify as well as mitigate the effects of the cyber-attacks. It is also not known how effective cybersecurity awareness training are on the cybersecurity skill level of senior citizens. Therefore, the main goal of this quantitative study was to empirically investigate the factors that contributed to senior citizens’ motivation to acquire cybersecurity skills so that they would be able to identify and mitigate cyber-attacks, as well as assess their actual cybersecurity skills level. This was done by assessing a model of contributing factors identified in prior literature (senior citizens’ cybersecurity awareness, computer self-efficacy, perceived risk of identity theft, & older adults’ computer technology attitude) on the motivation of senior citizens to acquire cybersecurity skills. This study utilized a Web-based survey to measure the contributing factors and a hands-on scenarios-based iPad app called MyCyberSkills™ that was developed and empirically validated in prior research to measure the cybersecurity skills level of the senior citizens. All study measures were done before and after cybersecurity awareness training (pre- & post-test) to uncover if there were any differences on the assessed models and scores due to such treatment. The study included a sample of 254 senior citizens with a mean age of about 70 years. Path analyses using Smart PLS 3.0 were done to assess the pre- and post-test models to determine the contributions of each contributing factor to senior citizens’ motivation to acquire cybersecurity skills. Additionally, analysis of variance (ANOVA) and analysis of covariance (ANCOVA) using SPSS were done to determine significant mean difference between the pre-and post-test levels of the senior citizens’ cybersecurity skill level. The path analysis results indicate that while all paths on both models were significant, many of the paths had very low path coefficients, which in turn, indicated weak relationships among the assessed paths. However, although the path coefficients were lower than expected, the findings suggest that both intrinsic and extrinsic motivation, along with antecedents such as senior citizens’ cybersecurity awareness, computer self-efficacy, perceived risk of identity theft, and older adults’ computer technology attitude significantly impact the cybersecurity skill levels of senior citizens. The analysis of variance results indicated that there was a significant increase in the mean cybersecurity skills scores from 59.67% to 64.51% (N=254) as a result of the cybersecurity awareness training. Hence, the cybersecurity awareness training was effective in increasing the cybersecurity skill level of the senior citizens, and empowered them with small but significant improvement in the requisite skills to take mitigating actions against cyberattacks. The analysis of covariance results indicated that, except for years using computers, all the other demographic indicators were not significant. Contributions from this study add to the body of knowledge by providing empirical results on the factors that motivate senior citizens to acquire cybersecurity skills, and thus, may help in reducing some of the billions of dollars in losses accrued to them because of cyber-attacks. Senior citizens will also benefit in that they will be better able to identify and mitigate the effects of cyber-attacks should they attend cybersecurity awareness trainings. Additionally, the recommendations from this study can be useful to law enforcement and other agencies that work with senior citizens in reducing the number of cases relating to cybersecurity issues amongst senior citizens, and thus, free up resources to fight other sources of cybercrime for law enforcement agencies

    The Data Breach Dilemma: Proactive Solutions for Protecting Consumers’ Personal Information

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    Data breaches are an increasingly common part of consumers’ lives. No institution is immune to the possibility of an attack. Each breach inevitably risks the release of consumers’ personally identifiable information and the strong possibility of identity theft. Unfortunately, current solutions for handling these incidents are woefully inadequate. Private litigation like consumer class actions and shareholder lawsuits each face substantive legal and procedural barriers. States have their own data security and breach notification laws, but there is currently no unifying piece of legislation or strong enforcement mechanism. This Note argues that proactive solutions are required. First, a national data security law—setting minimum data security standards, regulating the use and storage of personal information, and expanding the enforcement role of the Federal Trade Commission—is imperative to protect consumers’ data. Second, a proactive solution requires reconsidering how to minimize the problem by going to its source: the collection of personally identifiable information in the first place. This Note suggests regulating companies’ collection of Social Security numbers, and, eventually, using a system based on distributed ledger technology to replace the ubiquity of Social Security numbers
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