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With hackers relentlessly disrupting cyberspace and the day-to-day operations of organizations worldwide, there are also concerns related to Personally Identifiable Information (PII). Due to the data breaches and the data getting dumped on the clear web or the dark web, there are serious concerns about how the different threat actors worldwide can misuse the data. Also, it raises the question of how hackers can create a profile of an individual starting from one data leak and getting more details on individuals with the help of Open Source Intelligence (OSINT). Furthermore, there is a dilemma in utilizing data breach datasets dumped on the clear web or the dark web because of the sensitive nature of the information. There can be issues related to ethics, law enforcement, and legal use of data. Thus, to tackle this, we will construct synthetic datasets that will allow researchers and professionals to understand how data leaks can be dangerous and how hackers can connect the dots further by creating complete profiles of individuals. We have programmatically generated a synthetic master record of 4 million unique individuals with complete profiles of their PIIs, and then using the master record, we have further generated 16 scenario-based datasets by creating a fictitious narrative of data breaches covering different industry types. These datasets will facilitate researchers and industry professionals in understanding the distribution of PIIs across data breaches. The data classes represent the nature of PIIs sourced from ‘Have I Been Pwned?’ to create synthetic records. The synthetically generated records are shared with the code in this paper to facilitate future researchers and practitioners to generate customized synthetic records according to their requirements, enabling transparency in terms of reusability, reproducibility, and replicability.

Abstract The processing of personal data gives a rise to many privacy concerns, and one of them is to ensure the transparency of data processing to end users. Usually this information is communicated to them using privacy policies. In this paper, the problem of user notification in case of data breaches and policy changes is addressed, besides an ontology-based approach to model them is proposed. To specify the ontology concepts and properties, the requirements and recommendations for the legislative regulations as well as existing privacy policies are evaluated. A set of SPARQL queries to validate the correctness and completeness of the proposed ontology are developed. The proposed approach is applied to evaluate the privacy policies designed by cloud computing providers and IoT device manufacturers. The results of the analysis show that the transparency of user notification scenarios presented in the privacy policies is still very low, and the companies should reconsider the notification mechanisms and provide more detailed information in privacy policies.

Data breach incidents are now a regular occurrence, with millions of people affected worldwide. Few studies have examined the psychological aspects of data breach experiences, however, or the individual differences that influence how people react to these events. In this study, we examined the psychological stress associated with a personal experience with a data breach and several individual differences hypothesized to modulate such stress (age, gender, digital security awareness and expertise, trait anxiety, negative emotionality, and propensity to worry). A student sample (N = 166) and a community sample (N = 359) completed an online survey that asked participants to describe their most serious data breach and then complete the Impact of Events Scale—Revised (IES-R) to answer specific questions about the nature of the stress they experienced after the breach. Standard measures of trait anxiety, negative emotionality, and propensity to worry were also completed. A Data Breach Severity Index (DBSI) was created to quantify the invasiveness and consequences of each participant’s data breach. Hierarchical multiple regression analyses were used to identify demographic variables and psychological characteristics predictive of IES-R scores while controlling for DBSI scores. As expected, more invasive and consequential data breaches were associated with higher IES-R scores (greater data-breach-induced stress). Women had higher IES-R scores than men, and this difference persisted after controlling for gender differences in anxiety, negative emotionality, and propensity to worry. Greater daily social media use was associated with higher IES-R scores, whereas higher digital security expertise was associated with lower IES-R scores. The results illuminate several relationships between demographic and psychological characteristics and data-breach-induced stress that should be investigated further.

Research into data security often emphasizes the need to understand the factors linked to security breaches, aiming to prevent future information security incidents. The advancement of digital technology has made safeguarding an organization’s sensitive data more complex. Despite the growth of research in data security, there’s currently a shortage of studies that specifically investigate the factors contributing to information security breaches in organizations. Previous studies have primarily examined the security posture of companies and organizations, focusing on the breach type and location. However, few studies have explored external factors that may contribute to organizations’ vulnerability to information security breaches. The current study addresses this gap in the literature by integrating modern crime theory (MCT) to investigate the exogenous factors influencing the victimization of public and private organizations to data breach incidents. We use insights from crime theories and information about organizations’ technical, organizational, and financial aspects to investigate how attractiveness, visibility, and guardianship affect the likelihood of data breaches. We build a theoretical model to explore the relationship between these factors as independent predictors of data breaches. A covariance-based structural equation modeling (CB-SEM) based framework is developed to conduct a comprehensive examination of the dynamics within the context of cybercrime. Through the examination of collected data from 4,868 organizations, this study demonstrates a good fit of the hypothesized model to the data, supporting the validity of the proposed constructs. The results of this study validate the use of MCT in the study of information security breach, and enable the identification of the major exogenous factors influencing data breaches, such as the attractiveness of valuable data and effectiveness of guardianship measures.

The Internet of Things, Smart Devices, Information Systems, and Cloud Services have led to a digital transformation of companies. Such revolution has been accompanied by a huge amount of data available for companies, posing the growing challenge of data breaches. However, data breaches are not just a concern and complication for security experts; they also affect clients, stakeholders, organizations, and businesses, as stated by the Privacy Rights Clearinghouse. Thus, this study provides insights into data breaches faced by companies listed on the New York Stock Exchange and NASDAQ. The study found that hacking/IT incidents are the forms of attack with greater impact in data breaches, followed by unauthorized internal disclosures. The frequency of data breaches, the magnitude of exposed records, and financial losses due to breached records are increasing rapidly. Data from the companies listed on the stock exchange is regarded as being highly valuable. This has become a significant lure for the misappropriation and pilferage of data. Addressing this anomaly, the paper employs statistical visualizations of the data to shed light on these incidents and assess their consequences on the affected companies and individuals whose data was compromised. This work aims to contribute to a comprehensive understanding of data breaches and empower organizations to safeguard against them proactively by conducting this multifaceted analysis, and also provides a brief qualitative risk assessment regarding the attack vectors.

In Indonesia, the eHealth application has been widely used. It has also been recognized by World Health Organization (WHO) that Information and Communication Technology (ICT) provides a cost-effective and secure value to support various health sectors. The research method uses normative research which more emphasizes the use of positive law and comparisons of law with other countries. Meanwhile, the approach used in this study is a “qualitative empirical”. A primary legal material implementing statutory regulation in the field of Cyber law, and practically discusses how it is implemented in eHealth. This research examines two things in depth. Firstly; Is a “Data breach” committed by the electronic service providers? Secondly; Is a “Data theft” modus operandi achieved by the perpetrator? This study concludes that a “data breach” can occur due to “carelessness” or “bad faith” on the part of the service provider. Thus, bad faith behavior may intentionally process the data for illegal commercial purposes, either by processing it alone or by cooperating with other parties who use the data. Meanwhile, “Data theft” caused by “illegal access” activities there are carried out by the perpetrator, causing data can be changed, damaged, and deleted. Data related to eHealth is included in the category of special data that is protected by the laws and regulations in Indonesia. Thus, service providers should participate in providing data protection efforts by making “self-regulation” and providing training to service users, in an effort to avoid crime under Law Number. 27 of 2022 on Personal Data Protection.

This research studies the occurrence of data breaches in healthcare provider settings regarding patient data. Using visual analytics and data visualization tools, we study the distribution of healthcare breaches by state. We review the main causes and types of breaches, as well as their impact on both providers and patients. The research shows a range of data breach victims. Network servers are the most popular location for common breaches, such as hacking and information technology (IT) incidents, unauthorized access, theft, loss, and improper disposal. We offer proactive recommendations to prepare for a breach. These include, but are not limited to, regulatory compliance, implementing policies and procedures, and monitoring network servers. Unfortunately, the results indicate that the probability of data breaches will continue to rise.

Data breaches are becoming an increasingly prevalent and global concern due to their massive impact. One of the primary challenges in investigating data breach incidents is the unavailability of a specific framework that acknowledges the characteristics of a data breach incident and provides clear steps on how the investigative framework can comprehensively answer what, who, when, where, why, and how (5WH) questions. This paper aims to develop a novel digital forensic investigation framework that can overcome these data breach investigation challenges. The proposed framework utilizes the data breach breakdown phases to analyze data breach incidents according to their characteristics. The main contribution of our work is a novel digital forensic framework for data breach investigation that enhances the 5WH analysis depth by utilizing evidence classification and artifact visualization based on data breach breakdown phases. Furthermore, we design the framework components to provide comprehensive analysis results that make it easier for investigators to summarize the answers to the 5WH questions. To validate the framework, we apply it to a case study of enterprise-level data breach incidents. Based on the case study analysis, the proposed investigation framework successfully provides all the answers to the 5WH questions. This comprehensive answering ability is the study’s fundamental strength compared to other digital forensic investigation frameworks.

A data breach is the unauthorized disclosure of sensitive personal data, and it impacts millions of individuals annually in the United States, as reported by Privacy Rights Clearinghouse. These breaches jeopardize the physical safety of the individuals whose data are exposed and result in substantial economic losses for the affected companies. To diminish the frequency and severity of data breaches in the future, it is imperative to research their causes and explore preventive measures. In pursuit of this goal, this study considers a dataset of data breach incidents affecting companies listed on the New York Stock Exchange and NASDAQ. This dataset has been augmented with additional information regarding the targeted company. This paper employs statistical visualizations of the data to clarify these incidents and assess their consequences on the affected companies and individuals whose data were compromised. We then propose mitigation controls based on established frameworks such as the NIST Cybersecurity Framework. Additionally, this paper reviews the compliance scenario by examining the relevant laws and regulations applicable to each case, including SOX, HIPAA, GLBA, and PCI-DSS, and evaluates the impacts of data breaches on stock market prices. We also review guidelines for appropriately responding to data leaks in the U.S., for compliance achievement and cost reduction. By conducting this analysis, this work aims to contribute to a comprehensive understanding of data breaches and empower organizations to safeguard against them proactively, improving the technical quality of their basic services. To our knowledge, this is the first paper to address compliance with data protection regulations, security controls as countermeasures, financial impacts on stock prices, and incident response strategies. Although the discussion is focused on publicly traded companies in the United States, it may also apply to public and private companies worldwide.

Background: Cloud computing (CC) is a disruptive computing paradigm that uses networked systems, notably the Internet, to provide shared resources and services. Its use has been widespread, owing partly to its promise to reduce computation costs. Objective: This study aims to get into the critical security concerns that cloud computing poses, and to provide unique solutions to these difficulties. Methods: By examining the operational procedures and infrastructure of data centers - the key suppliers of cloud services - this article elaborates on the particular risks that cloud-based operations bring. The study underlines the need of increased security, particularly considering the interconnection and apparent control customers have over ostensibly devoted resources. Results: Cloud computing offers a variety of advantages, including on-demand service delivery, geographical independence, and pay-as-you-go pricing. However, its intrinsic structure creates threats to data integrity, availability, and privacy. In response, this article presents a Dynamic Secure Interconnection (DSI) architecture that divides the cloud into dynamic virtual trust zones, each with its own set of security protocols. Conclusion: As cloud computing continues to transform IT and business environments, implementing effective security measures becomes more important. The suggested DSI mechanism is a viable way to bolstering security inside cloud systems, aiming for a safer, more regulated data management environment.

The purpose of this research study was to explore what can be learned by prioritizing for ransomware and data loss protection during organizational strategic planning to mitigate the negative effects of these events while identifying specific actions and recommendations organizations can take to mitigate the effects of ransomware and associated data loss. The problem addressed was that many organizations have become or will become victims of massive data losses caused by ransomware attacks because ransomware security controls and data loss prevention are not prioritized during strategic planning (Breckenridge, 2020). The methodology used was a qualitative metasynthesis which examined six case studies that were chosen as a representative set of organizations that have experienced common effects that are often felt in the aftermath of either a ransomware attack, poor strategic planning for cybersecurity controls, or data loss. The findings show the emergence of several themes including a common lack of strategic planning, the inability to recognize network anomalies leading to malware installations that resulted in data breaches, the lack of or misuse of security controls, and the heavy consequences suffered as a result of not putting effort into preventing the data breaches. Additional examination focused on the need for a proactive approach to data loss prevention which demands the attention of organizational leadership at the highest levels.

Data breaches result in data loss, including personal, health, and financial information that are crucial, sensitive, and private. The breach is a security incident in which personal and sensitive data are exposed to unauthorized individuals, with the potential to incur several privacy concerns. As an example, the French newspaper Le Figaro breached approximately 7.4 billion records that included full names, passwords, and e-mail and physical addresses. To reduce the likelihood and impact of such breaches, it is fundamental to strengthen the security efforts against this type of incident and, for that, it is first necessary to identify patterns of its occurrence, primarily related to the number of data records leaked, the affected geographical region, and its regulatory aspects. To advance the discussion in this regard, we study a dataset comprising 428 worldwide data breaches between 2018 and 2019, providing a visualization of the related statistics, such as the most affected countries, the predominant economic sector targeted in different countries, and the median number of records leaked per incident in different countries, regions, and sectors. We then discuss the data protection regulation in effect in each country comprised in the dataset, correlating key elements of the legislation with the statistical findings. As a result, we have identified an extensive disclosure of medical records in India and government data in Brazil in the time range. Based on the analysis and visualization, we find some interesting insights that researchers seldom focus on before, and it is apparent that the real dangers of data leaks are beyond the ordinary imagination. Finally, this paper contributes to the discussion regarding data protection laws and compliance regarding data breaches, supporting, for example, the decision process of data storage location in the cloud.

With the development of modern data processing, mining and collection technologies, various companies and institutions will have more opportunities to make these data operations faster and more efficiently. From the economic perspective, processing personal data is evidently lucrative and companies would therefore like to obtain as much data as possible. This paper analyses and summarizes existing and emerging social and economic trends, implications and issues caused by clashes between European legislation on personal data protection (the GDPR) and current data processing practices. Utilizing both quantitative and qualitative data, the article attempts to scrutinize the implications of the conflict between the rising demand for privacy and personal data protection on the one hand and the ever-growing need to process and store personal data, especially by commercial organizations, on the other. Analysing databases, legislation, reports, statistical data and surveys, the paper attempts to provide an estimate of the value of personal data and the consequences of poor handling of personal data.

The exponential growth in the interconnectedness of people and devices, as well as the upward trend in cyberspace usage will continue to lead to a greater reliance on the internet. Most people’s daily activities are dependent on their ability to navigate the internet to access and manage information. There are usually real risks associated with managing or accessing information, and these risks when exploited by threat actors, often lead to cybersecurity incidents. It is a common knowledge that a major cybersecurity incident is likely to result in significant financial losses, legal liability, privacy violations, reputational damage, sensitive data compromises, as well as national security implications. Threat actors usually employ various attack techniques to cause these incidents. After we identified the major cybersecurity incident report that is consolidated by the Center for Strategic & International Studies (CSIS) from which we derived the data of about the 803 major incidents that we analyzed, we then verified its (CSIS) credibility, non-partisan, global outreach and cybersecurity attack coverage by cross-referencing it with Data Breach Investigation Report (DBIR). We also through the lens of the Global Cybersecurity Index (GCI) ensured that this study is conducted within the context of cybersecurity principles. In reference to these attack techniques employed by threat actors, we conducted an exploratory investigation of 803 major cybersecurity incidents that were reported over the last decade. From a group of 244 of these major security incidents that happened and were reported between 2005 and 2021, this study reports that malware attack techniques were employed by threat actors to cause 48 percent of them and phishing attack techniques account for 19.7 percent of them. As many sources have confirmed the fact that major incidents will always happen, we echo the importance of readiness of organizations to conduct cybersecurity incident triage and or thorough investigation as necessary. Given the relevance of the guidelines outlined in the National Institute of Standards and Technology (NIST) incident response framework, we also recommend that organizations should adopt it or at least embrace similar guidelines as best as possible.

While data breaches are a frequent and universal phenomenon, the characteristics and dimensions of data breaches are unexplored. In this novel exploratory research, we apply machine learning (ML) and text analytics to a comprehensive collection of data breach litigation cases to extract insights from the narratives contained within these cases. Our analysis shows stakeholders (e.g., litigants) are concerned about major topics related to identity theft, hacker, negligence, FCRA (Fair Credit Reporting Act), cybersecurity, insurance, phone device, TCPA (Telephone Consumer Protection Act), credit card, merchant, privacy, and others. The topics fall into four major clusters: “phone scams”, “cybersecurity”, “identity theft”, and “business data breach”. By utilizing ML, text analytics, and descriptive data visualizations, our study serves as a foundational piece for comprehensively analyzing large textual datasets. The findings hold significant implications for both researchers and practitioners in cybersecurity, especially those grappling with the challenges of data breaches.

The problem of data breach incidents is prevalent in the media and has attracted the attention of researchers and practitioners working diligently on solutions. Commercial entities, non-profit organizations, and government agencies that obtain, process, and store personal or business-related information face the risks of the breach of client personal information and organizational intellectual property, which can result in legal, reputational, and financial damages. This study aims to estimate the probability of the occurrence of a breach and its size using a predictive model with historical data as input. We used a dataset of all reported data breaches in the U.S. collected by Privacy Rights Clearinghouse (PRC). The results show that the trend of data breaches has not been increasing despite all the attention and warnings. Our Poisson and Negative binomial models proved promising and can predict data breach incidents with low deviance from actual numbers.

This study tries to evaluate the experimental behavior of graduate students of Ilam University when using mobile electronic devices (mobile phones, tablets and laptops) based on the protection motivation theory of data breach. This research is of applied-survey type. The statistical population of research includes graduate students of Ilam University. Data collection tool was based on the questionnaires introduced by Boss et al., Woon et al., Claar and Johnson, Johnson and Warkentin, and Posey et al. For data analysis, structural equation modeling was used to fit the model and test the hypotheses of research in AMOS software using partial least squares method. Results indicated that there is a positive relationship between the perceived threat sensitivity, response effectiveness, self-efficacy and the possibility of using the security of mobile electronic devices with the protection motivation. In addition, the findings showed that there is not a meaningful relationship between the perceived threat intensity and the motivation of protecting the mobile electronic devices. There is a negative (indirect) relationship between the perceived response cost and the protection motivation. Generally, this study emphasized that the confrontational assessment process is a more important factor than the threat assessment process in increasing users’ protection motivation.

BackgroundHealthcare is facing a growing threat of cyberattacks. Myriad data sources illustrate the same trends that healthcare is one of the industries with the highest risk of cyber infiltration and is seeing a surge in security incidents within just a few years. The circumstances thus begged the question: are US hospitals prepared for the risks that accompany clinical medicine in cyberspace?ObjectiveThe study aimed to identify the major topics and concerns present in today's hospital cybersecurity field, intended for non-cyber professionals working in hospital settings.MethodsVia structured literature searches of the National Institutes of Health's PubMed and Tel Aviv University's DaTa databases, 35 journal articles were identified to form the core of the study. Databases were chosen for accessibility and academic rigor. Eighty-seven additional sources were examined to supplement the findings.ResultsThe review revealed a basic landscape of hospital cybersecurity, including primary reasons hospitals are frequent targets, top attack methods, and consequences hospitals face following attacks. Cyber technologies common in healthcare and their risks were examined, including medical devices, telemedicine software, and electronic data. By infiltrating any of these components of clinical care, attackers can access mounds of information and manipulate, steal, ransom, or otherwise compromise the records, or can use the access to catapult themselves to deeper parts of a hospital's network. Issues that can increase healthcare cyber risks, like interoperability and constant accessibility, were also identified. Finally, strategies that hospitals tend to employ to combat these risks, including technical, financial, and regulatory, were explored and found to be weak. There exist serious vulnerabilities within hospitals' technologies that many hospitals presently fail to address. The COVID-19 pandemic was used to further illustrate this issue.ConclusionsComparison of the risks, strategies, and gaps revealed that many US hospitals are unprepared for cyberattacks. Efforts are largely misdirected, with external—often governmental—efforts negligible. Policy changes, e.g., training employees in cyber protocols, adding advanced technical protections, and collaborating with several experts, are necessary. Overall, hospitals must recognize that, in cyber incidents, the real victims are the patients. They are at risk physically and digitally when medical devices or treatments are compromised.

Dark Web forums are significantly exploited to trade confidential information and illicit products by criminals. This paper addresses the problem of how to identify the cluster of discussion forums and their characteristics on the Dark Web. Exiting methods are mostly dependent on the continuous labeled contents, which are expensive and not feasible due to the nature of Dark Web data. Therefore, an approach that does not need a continuous availability of labeled forum and related knowledge is required. To this end, we propose an unsupervised model to identify and characterize Dark Web forums by combining clustering algorithm and decision tree algorithm. The proposed method presents the characteristics in an explainable form that can be used by the cyber threat intelligence system and law enforcement as scientific evidence to analyze any data breach or illicit activities in the Dark Web forums. To evaluate the performance of our model comprehensive experiments were conducted using real Dark Web forum data. The proposed approach achieves 98% accuracy and F1 score of 98% validating the efficacy of our proposed model to successfully characterize Dark Web forums. The experimental results suggest that the proposed model could be useful to the cyber threat intelligence and law enforcement community for building an intelligent source of knowledge that can be used for detecting data breach and illicit activities happening in the Dark Web forums.

Il saggio si propone di esaminare se le norme del Reg. UE 679/16 in materia di sicurezza del trattamento dei dati personali appaiono adeguate nel caso di data breach e se il bilanciamento degli interessi presi in considerazione dal Regolamento (tutela della libertà e dignità delle persone da un lato e sviluppo dell’economia digitale dall’altro) sia assicurato anche mediante i meccanismi di individuazione della responsabilità in caso di mancato trattamento sicuro dei dati e di individuazione dei criteri risarcitori. / 𝑇ℎ𝑒 𝑝𝑢𝑟𝑝𝑜𝑠𝑒 𝑜𝑓 𝑡ℎ𝑖𝑠 𝑒𝑠𝑠𝑎𝑦 𝑖𝑠 𝑡𝑜 𝑒𝑥𝑎𝑚𝑖𝑛𝑒 𝑤ℎ𝑒𝑡ℎ𝑒𝑟 𝑡ℎ𝑒 𝑟𝑢𝑙𝑒𝑠 𝑜𝑓 𝐸𝑈 𝑅𝑒𝑔. 679/16 𝑜𝑛 𝑡ℎ𝑒 𝑠𝑒𝑐𝑢𝑟𝑖𝑡𝑦 𝑜𝑓 𝑝𝑒𝑟𝑠𝑜𝑛𝑎𝑙 𝑑𝑎𝑡𝑎 𝑝𝑟𝑜𝑐𝑒𝑠𝑠𝑖𝑛𝑔 𝑎𝑝𝑝𝑒𝑎𝑟 𝑎𝑑𝑒𝑞𝑢𝑎𝑡𝑒 𝑖𝑛 𝑡ℎ𝑒 𝑒𝑣𝑒𝑛𝑡 𝑜𝑓 𝑎 𝑑𝑎𝑡𝑎 𝑏𝑟𝑒𝑎𝑐ℎ 𝑎𝑛𝑑 𝑤ℎ𝑒𝑡ℎ𝑒𝑟 𝑡ℎ𝑒 𝑏𝑎𝑙𝑎𝑛𝑐𝑒 𝑜𝑓 𝑖𝑛𝑡𝑒𝑟𝑒𝑠𝑡𝑠 𝑡𝑎𝑘𝑒𝑛 𝑖𝑛𝑡𝑜 𝑎𝑐𝑐𝑜𝑢𝑛𝑡 𝑏𝑦 𝑡ℎ𝑒 𝑅𝑒𝑔𝑢𝑙𝑎𝑡𝑖𝑜𝑛 (𝑝𝑟𝑜𝑡𝑒𝑐𝑡𝑖𝑜𝑛 𝑜𝑓 𝑡ℎ𝑒 𝑓𝑟𝑒𝑒𝑑𝑜𝑚 𝑎𝑛𝑑 𝑑𝑖𝑔𝑛𝑖𝑡𝑦 𝑜𝑓 𝑖𝑛𝑑𝑖𝑣𝑖𝑑𝑢𝑎𝑙𝑠 𝑜𝑛 𝑡ℎ𝑒 𝑜𝑛𝑒 ℎ𝑎𝑛𝑑 𝑎𝑛𝑑 𝑑𝑒𝑣𝑒𝑙𝑜𝑝𝑚𝑒𝑛𝑡 𝑜𝑓 𝑡ℎ𝑒 𝑑𝑖𝑔𝑖𝑡𝑎𝑙 𝑒𝑐𝑜𝑛𝑜𝑚𝑦 𝑜𝑛 𝑡ℎ𝑒 𝑜𝑡ℎ𝑒𝑟) 𝑖𝑠 𝑎𝑙𝑠𝑜 𝑒𝑛𝑠𝑢𝑟𝑒𝑑 𝑡ℎ𝑟𝑜𝑢𝑔ℎ 𝑡ℎ𝑒 𝑚𝑒𝑐ℎ𝑎𝑛𝑖𝑠𝑚𝑠 𝑓𝑜𝑟 𝑖𝑑𝑒𝑛𝑡𝑖𝑓𝑦𝑖𝑛𝑔 𝑙𝑖𝑎𝑏𝑖𝑙𝑖𝑡𝑦 𝑖𝑛 𝑡ℎ𝑒 𝑒𝑣𝑒𝑛𝑡 𝑜𝑓 𝑓𝑎𝑖𝑙𝑢𝑟𝑒 𝑡𝑜 𝑝𝑟𝑜𝑐𝑒𝑠𝑠 𝑑𝑎𝑡𝑎 𝑠𝑒𝑐𝑢𝑟𝑒𝑙𝑦 𝑎𝑛𝑑 𝑓𝑜𝑟 𝑖𝑑𝑒𝑛𝑡𝑖𝑓𝑦𝑖𝑛𝑔 𝑡ℎ𝑒 𝑐𝑟𝑖𝑡𝑒𝑟𝑖𝑎 𝑓𝑜𝑟 𝑐𝑜𝑚𝑝𝑒𝑛𝑠𝑎𝑡𝑖𝑜𝑛.

More and more data are being stored in various cloud storages and they make it impossible to personally take care of data security, since most of these service providers do not offer any options for users to set up trusted encryption. We offer two types of solution to protect data, a client-side encryption and a security middleware. OpenWebCrypt is a browser extension designed to secure private data so it does not leave the client browser. Our security middleware, CrypStore PI offers a flexible solution to encrypt all the data that leaves the trusted LAN. By doing so, both guarantee that neither an attacker on the untrusted channel, nor the third-party external service provider has access to those. Furthermore, by separating the keys and the encryption itself from the user machines to dedicated hardware, CrypStore PI also improves the level of protection. Our goal is to offer easy to use, configurable and affordable solutions for personal users or small enterprises who would like to take responsibility for the protection of their data stored in public clouds. Because of the limited resources, we analysed the performance of today's most used symmetric key encryption algorithms to be able to recommend the best choice.

The paper focuses primarily on the communication and notification of personal data breaches pursuant to the General Data Protection Regulation. The author discusses the issue in the context of the nemo tenetur principle and the related constitutional aspects.

To address rapidly growing data breach incidents effectively, healthcare providers need to identify various insider and outsider threats, analyze the vulnerabilities of their internal security systems, and develop more appropriate data security measures against the threats. While there have been studies on trends of data breach incidents, there is a lack of research on the analysis of descriptive contents posted on the data breach reporting website of the U.S. Department of Health and Human Services (HHS) Office for Civil Rights (OCR). Hence, this study develops a novel approach to the analysis of descriptive data breach information with the use of text mining and visualization. Insider threats, vulnerabilities, breach incidents, impacts, and responses to the breaches are analyzed for three data breach types.

Internet of Things (IoT) presents opportunities for designing new technologies for organizations. Many organizations are beginning to accept these technologies for their daily work, where employees can be connected, both on the organization's premises and the “outside”, for business continuity. However, organizations continue to experience data breach incidents. Even though there is a plethora of researches in Information Security, there “seems” to be little or lack of interest from the research community, when it comes to human factors and its relationship to data breach incidents. The focus is usually on the technological component of Information Technology systems. Regardless of any technological solutions introduced, human factors continue to be an area that lacks the required attention. Making the assumption that people will follow expected secure behavioral patterns and therefore system security expectations will be satisfied, may not necessarily be true. Security is not something that can simply be purchased; human factors will always prove to be an important space to explore. Hence, human factors are without a doubt a critical point in Information Security. In this study, we propose an Organizational Information Security Framework For Human Factors applicable to the Internet of Things, which includes countermeasures that can help prevent or reduce data breach incidents as a result of human factors. Using linear regression on data breach incidents reported in the United States of America from 2009 to 2017, the study validates human factors as a weak-point in information security that can be extended to Internet of Things by predicting the relationship between human factors and data breach incidents, and the strength of these relationships. Our results show that five breach incidents out of the seven typified human factors to statistically and significantly predict data breach incidents. Furthermore, the results also show a positive correlation between human factors and these data breach incidents.

This research paper concerns the interactions between privacy and cybersecurity as business risks, exploring how the same challenges apply to both of them and how security is a global threat in a digitalized world. In their quest to gain competitive advantage, capitalizing on digital information and owning personal data, businesses of all types get challenged in managing risks, being exposed to data privacy and cybersecurity. As information and processes get digitized, more risks occur and an organization evolution is influenced by the way it manages risks of all kind: reputational, ethics, conformity, regulation, market, strategic, credit. The paper raises awareness and encourages dialogue on data governance and presents important direction lines over cyber security as a fundamental part of online privacy protection.

Recently, underground forums play a crucial role in trading and exchanging leaked personal information. Meanwhile, the forums have been gradually used as data breaches' information sources. Therefore, it shows an upward trend in announcing the results of data theft by posting in the forums. Identifying these threads can make the compromised third-party respond quickly to the data breach incident. For this purpose, we presented a system to identify the threads which are related to data breaches automatically. The system can monitor and discover data breaches in underground forums in real-time. In addition, the study further revealed the wording characteristics of the threads by applying the feature extraction method based on LDA topic model. In this paper, the data set was collected from the surface web and the dark web. Besides, to improve the performance of the system, we compared various supervised classification algorithms in this application scenario and selected the best method for the classifier. Through the system, we identified more than 92% of data breach threads on the experimental data set.

Healthcare sector is identified as particularly vulnerable to digital data breaches and damages caused by illegal use of personal and confidential information. Facing such dangerous threat medical entities need to estimate financial consequences of potential cyber attack leading to a breach of patients’ data. The paper’s aim is to provide an overview of the consequences of digital data breach in healthcare sector and their financial impact – comparing Polish and global perspective. The research method used was analysis and comparison of international literature, reports, case studies, statistics concerning data breaches in healthcare sector as well as new legal regulations applicable in European Union. The results of the research show that estimations of total digital data breach costs vary widely among various reports and analysis. The main reasons are application of different methods of estimation and lack of complete and reliable databases due to insufficient disclosure of cyber incidents. In addition, the most important conclusion of the paper is that there is an urgent need to conduct research concerning probable data breach costs in Polish healthcare sector, since studies pursued by renowned organisations have not covered Poland so far.

Insider attacks are becoming increasingly detrimental and frequent, affecting critical infrastructure at a massive scale. Recent attacks such as the U.K. National Health Service WannaCry ransomware attack which partly depends on internal users for initial infection highlight the increasing role of the malicious insiders in cyber-attack campaigns. The objective of this research is to ascertain the existing technological capability to mitigate insider threats within computer security systems by way of a mixed-method systematic review. Evidence was acquired from major sources of mainstream and grey literature by analyzing about 300 000 papers. Crude aggregated results were analyzed across the literature, and the results were TPR 0.75, FPR 0.32, σ 0.24 and 0.36, respectively, and σ2 0.06 and 0.13, respectively. In totality, the literature evidence suggests that there is high heterogeneity across crude data indicating that the effectiveness of security measures varies significantly. No solution is able to totally mitigate an insider threat. Themes when against that data suggest that most, if not all, security measures require breaches to occur before an analysis of malicious activity can prevent it in future through recall. Such a reactive approach is not effective protect our critical infrastructure including our healthcare systems. Consequently, there is a major theoretical shortfall in current cyber defence architecture.

Cybersecurity concerns are present in all nations, but the exact nature of the threats differs depending on the country and/or region. Therefore there is a need to assess the threats and impacts for specific countries. This article presents a high-level analysis of “newsworthy” cyber-incidents that affected South Africa. The 54 incidents that are considered are categorised according to impact type, perpetrator type, and victim type, and the trends are assessed. It was found that the most common impact type was data exposure, which was also one that had increased noticeably in recent years. The most prevalent perpetrator type was found to be hacktivists, which had also exhibited a recent increase in activity. A particularly concerning trend was the recent high number of incidents of data exposure caused by error, a trend running contrary to the drive to improve cybersecurity. It was also found that of the incidents considered, 54% targeted state-owned or political entities as victims. In general, the results appeared consistent with global reported trends

In today’s world, health data are being produced in ever\-increasing amounts due to extensive use of medical devices generating data in digital form. These data are stored in diverse formats at different health information systems. Medical practitioners and researchers can be benefited significantly if these massive heterogeneous data could be integrated and made accessible through a common platform. On the other hand, digital health data containing protected health information (PHI) are the main target of the cybercriminals. In this paper, we have provided a state of the art review of the security threats in the integrated healthcare information systems. According to our analysis, healthcare data servers are leading target of the hackers because of monetary value. At present, attacks on healthcare organizations' data are 1.25 times higher compared to five years ago. We have provided some important recommendations to minimize the risk of attacks and to reduce the chance of compromising patients' privacy after any successful attack.

With the emergence of global digital service providers, concerns about digital oligopolies have increased, with a wide range of potentially harmful effects being discussed. One of these relates to cyber security, where it has been argued that market concentration can increase cyber risk. Such a state of affairs could have dire consequences for insurers and reinsurers, who underwrite cyber risk and are already very concerned about accumulation risk. Against this background, the paper develops some theory about how convex cyber risk affects Cournot oligopoly markets of data storage. It is demonstrated that with constant or increasing marginal production cost, the addition of increasing marginal cyber risk cost decreases the differences between the optimal numbers of records stored by the oligopolists, in effect offsetting the advantage of lower marginal production cost. Furthermore, based on the empirical literature on data breach cost, two possibilities are found: (i) that such cyber risk exhibits decreasing marginal cost in the number of records stored and (ii) the opposite possibility that such cyber risk instead exhibits increasing marginal cost in the number of records stored. The article is concluded with a discussion of the findings and some directions for future research.

The prevalence of the internet as firm’s primary channel of operations and marketing in recent decades has made information security management a critical issue for firms. Yet, previous research on the information security issue have mostly focused on the impact of information security events on firms’ short-term value. Their impact on firms’ long-term value is rarely analyzed. Corporate managers have also largely dismissed the negative long-term impact of information security breaches by considering them as accidental and arguing that their frequency in recent years has instigated a sense of numbness in customers to their regards. Consequently, managers have paid little attention to information security investments. To assess the importance of information security investment, this study examines short-term and long-term stock market assessment of data breaches events at publicly traded companies. The findings of this study offer new insights for firms in assessing information security investment.

Wearable devices and smart clothes give rise to pivotal technological and legal issues in the fashion business. The cybersecurity attention in the digital society, and the advent of General Data Protection Regulation No. 2016/679 (GDPR) in the European, and global, legal framework, implied the need to evaluate which norms and aspects of the European Regulation could apply to wearable devices, which are becoming more and more invasive. Wearable devices are, first of all (and from a data protection point of view), intrusive tools that can put users’ personal (and intimate) data at risk. In particular, we will discuss the aspects of the spread of an accountability “culture” (also) in the fashion business, the need for correct management policy of data breaches, the rights of transparency for users/customers who are using wearable devices and smart clothes, and respect for the dignity and nondiscrimination of the individual during the data collection and processing. These are, all, fundamental points: the protection of the individual’s data in the digital landscape is, in fact, strictly connected to the protection of his/her fundamental rights in the modern digital society.

Healthcare sector is identified as particularly vulnerable to digital data breaches and damages caused by illegal use of personal and confidential information. Facing such dangerous threat medical entities need to estimate financial consequences of potential cyber attack leading to a breach of patients’ data. The paper’s aim is to provide an overview of the consequences of digital data breach in healthcare sector and their financial impact – comparing Polish and global perspective. The research method used was analysis and comparison of international literature, reports, case studies, statistics concerning data breaches in healthcare sector as well as new legal regulations applicable in European Union. The results of the research show that estimations of total digital data breach costs vary widely among various reports and analysis. The main reasons are application of different methods of estimation and lack of complete and reliable databases due to insufficient disclosure of cyber incidents. In addition, the most important conclusion of the paper is that there is an urgent need to conduct research concerning probable data breach costs in Polish healthcare sector, since studies pursued by renowned organisations have not covered Poland so far.

To fill a gap of research that explores cyber crisis management, this study analyzed news stories of the five largest data breaches experienced in 2014 by retailers (i.e. Target, Michaels, Neiman Marcus, Home Depot, and Staples). Corporate crisis communication and its news coverage (n = 64) were evaluated for crisis communication strategies and framed situational factors. Despite companies’ use of multiple strategies, newspapers reported their use of advocate strategies more often. Massmediated crisis response strategies were even different among the five companies. Newspapers also reframed crisis severity and crisis controllability. Finally, our findings addressed the key to dealing with the public relations nightmare that would result from a security breach.