Relevant bibliographies by topics / Insider threats

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Insider threats'

Author: Grafiati
Published: 4 June 2021
Last updated: 18 June 2025

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Journal articles on the topic "Insider threats"

1

Mohammad, Nur Ameera Natasha, Warusia Mohamed Yassin, Rabiah Ahmad, Aslinda Hassan, and Mohammed Nasser Ahmed Al Mhiqani. "An Insider Threat Categorization Framework for Automated Manufacturing Execution System." International Journal of Innovation in Enterprise System 3, no. 02 (2019): 31–41. http://dx.doi.org/10.25124/ijies.v3i02.38.

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Insider threats become one of the most dangerous threats in the cyber world as compared to outsider as the insiders have knowledge of assets. In addition, the threats itself considered in-visible and no one can predict what, when and how exactly the threat launched. Based on conducting literature, threat in Automated Manufacturing Execution Systems (AMESs) can be divided into three principle factors. Moreover, there is no standard framework to be referring which exist nowadays to categorize such factors in order to identify insider threats possible features. Therefore, from the conducted literature a standard theoretical categorization of insider threats framework for AMESs has been proposed. Hence, three principle factors, i.e. Human, Systems and Machine have considered as major categorization of insider threats. Consequently, the possible features for each factor identified based on previous researcher recommendations. Therefore, via identifying possible features and categorize it into principle factors or groups, a standard framework could be derived. These frameworks will contribute more benefit specifically in the manufacturing field as a reference to mitigate an insider threat. 
 Keywords—automated manufacturing execution systems insider threats, factors and features, insider threat categorization framework.
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Hu, Teng, Bangzhou Xin, Xiaolei Liu, Ting Chen, Kangyi Ding, and Xiaosong Zhang. "Tracking the Insider Attacker: A Blockchain Traceability System for Insider Threats." Sensors 20, no. 18 (2020): 5297. http://dx.doi.org/10.3390/s20185297.

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The insider threats have always been one of the most severe challenges to cybersecurity. It can lead to the destruction of the organisation’s internal network system and information leakage, which seriously threaten the confidentiality, integrity and availability of data. To make matters worse, since the attacker has authorized access to the internal network, they can launch the attack from the inside and erase their attack trace, which makes it challenging to track and forensics. A blockchain traceability system for insider threats is proposed in this paper to mitigate the issue. First, this paper constructs an insider threat model of the internal network from a different perspective: insider attack forensics and prevent insider attacker from escaping. Then, we analyze why it is difficult to track attackers and obtain evidence when an insider threat has occurred. After that, the blockchain traceability system is designed in terms of data structure, transaction structure, block structure, consensus algorithm, data storage algorithm, and query algorithm, while using differential privacy to protect user privacy. We deployed this blockchain traceability system and conducted experiments, and the results show that it can achieve the goal of mitigating insider threats.
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Al-Mhiqani, Mohammed Nasser, Rabiah Ahmad, Z. Zainal Abidin, et al. "A Review of Insider Threat Detection: Classification, Machine Learning Techniques, Datasets, Open Challenges, and Recommendations." Applied Sciences 10, no. 15 (2020): 5208. http://dx.doi.org/10.3390/app10155208.

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Insider threat has become a widely accepted issue and one of the major challenges in cybersecurity. This phenomenon indicates that threats require special detection systems, methods, and tools, which entail the ability to facilitate accurate and fast detection of a malicious insider. Several studies on insider threat detection and related areas in dealing with this issue have been proposed. Various studies aimed to deepen the conceptual understanding of insider threats. However, there are many limitations, such as a lack of real cases, biases in making conclusions, which are a major concern and remain unclear, and the lack of a study that surveys insider threats from many different perspectives and focuses on the theoretical, technical, and statistical aspects of insider threats. The survey aims to present a taxonomy of contemporary insider types, access, level, motivation, insider profiling, effect security property, and methods used by attackers to conduct attacks and a review of notable recent works on insider threat detection, which covers the analyzed behaviors, machine-learning techniques, dataset, detection methodology, and evaluation metrics. Several real cases of insider threats have been analyzed to provide statistical information about insiders. In addition, this survey highlights the challenges faced by other researchers and provides recommendations to minimize obstacles.
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Palaparthy, Keerthana, Y. Manohar Reddy, Jatoth Victor Paul, and S. Raju. "Enhancing Insider Threat Detection through Integrated Behavioral, Signature and Anomaly based Detection Methods." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 12 (2024): 1–6. https://doi.org/10.55041/ijsrem39835.

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Insider threats present substantial risks to organizational security, as malicious actors exploit their authorized access to systems, networks, or data to perpetrate harmful activities. These threats encompass various forms, including data theft, sabotage, fraud, or espionage, leading to significant financial losses, reputational damage, or regulatory penalties. Traditional approaches to insider threat detection, such as anomaly-based, signature-based, and behavioral analysis methods, have inherent limitations, including high false positives, reliance on known patterns, and lack of contextual understanding. These approaches often fail to classify insider threats accurately, potentially leading to innocent insiders being mislabeled as malicious. In this project, a unified insider threat detection system is proposed, integrating anomaly-based, signature- based, and behavioral analysis methods using Support Vector Machines (SVMs). By combining these methods and leveraging the strengths of SVMs, the aim is to address the limitations of individual approaches and enhance detection accuracy. Weighted voting is employed to fuse the output of each detection method, providing a comprehensive likelihood estimate of insider threats. This integrated approach enables organizations to better identify and mitigate insider threats, safeguarding sensitive assets and maintaining a robust security posture. Keywords— Insider threat, Insider threat detection, Signature- based detection, Anomaly-based detection, Behavior analysis, False positives, Detection accuracy, Weighted Voting Mechanism.
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Kim, Park, Kim, Cho, and Kang. "Insider Threat Detection Based on User Behavior Modeling and Anomaly Detection Algorithms." Applied Sciences 9, no. 19 (2019): 4018. http://dx.doi.org/10.3390/app9194018.

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Insider threats are malicious activities by authorized users, such as theft of intellectual property or security information, fraud, and sabotage. Although the number of insider threats is much lower than external network attacks, insider threats can cause extensive damage. As insiders are very familiar with an organization’s system, it is very difficult to detect their malicious behavior. Traditional insider-threat detection methods focus on rule-based approaches built by domain experts, but they are neither flexible nor robust. In this paper, we propose insider-threat detection methods based on user behavior modeling and anomaly detection algorithms. Based on user log data, we constructed three types of datasets: user’s daily activity summary, e-mail contents topic distribution, and user’s weekly e-mail communication history. Then, we applied four anomaly detection algorithms and their combinations to detect malicious activities. Experimental results indicate that the proposed framework can work well for imbalanced datasets in which there are only a few insider threats and where no domain experts’ knowledge is provided.
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Soleh, Musdi Muhammad. "A Study Case in NTMC POLRI: Reducing Data Breach Risk from Insider Threats by Using Risk IT Framework." ACMIT Proceedings 3, no. 1 (2019): 171–79. http://dx.doi.org/10.33555/acmit.v3i1.41.

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Risks is not only merely comes from external threats, it is also comes from inside - internal actor. Vormetric Insider Threat mentioned that in 800 surveyed enterprise companies, 89% vulnerable to insider attacks [1]. It mentioned that Data Breach issue the highest risk happened to the company caused by insider threats. This paper will analyse the insider attacks, Risk IT framework will be used toreduce to reduce and prevent these vulnerabilities in valuable assets.
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Alsowail, Rakan A., and Taher Al-Shehari. "A Multi-Tiered Framework for Insider Threat Prevention." Electronics 10, no. 9 (2021): 1005. http://dx.doi.org/10.3390/electronics10091005.

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As technologies are rapidly evolving and becoming a crucial part of our lives, security and privacy issues have been increasing significantly. Public and private organizations have highly confidential data, such as bank accounts, military and business secrets, etc. Currently, the competition between organizations is significantly higher than before, which triggers sensitive organizations to spend an excessive volume of their budget to keep their assets secured from potential threats. Insider threats are more dangerous than external ones, as insiders have a legitimate access to their organization’s assets. Thus, previous approaches focused on some individual factors to address insider threat problems (e.g., technical profiling), but a broader integrative perspective is needed. In this paper, we propose a unified framework that incorporates various factors of the insider threat context (technical, psychological, behavioral and cognitive). The framework is based on a multi-tiered approach that encompasses pre, in and post-countermeasures to address insider threats in an all-encompassing perspective. It considers multiple factors that surround the lifespan of insiders’ employment, from the pre-joining of insiders to an organization until after they leave. The framework is utilized on real-world insider threat cases. It is also compared with previous work to highlight how our framework extends and complements the existing frameworks. The real value of our framework is that it brings together the various aspects of insider threat problems based on real-world cases and relevant literature. This can therefore act as a platform for general understanding of insider threat problems, and pave the way to model a holistic insider threat prevention system.
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Hobbs, Christopher. "Insider threats." International Affairs 95, no. 3 (2019): 725–26. http://dx.doi.org/10.1093/ia/iiz084.

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Niblett, Gareth. "Insider Threats." ITNOW 58, no. 2 (2016): 23. http://dx.doi.org/10.1093/itnow/bww039.

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Luqman Hakim. "Insider Threats: The Cybersecurity Analysis using OCTAVE Allegro which are combined with HAIS-Q." Uranus : Jurnal Ilmiah Teknik Elektro, Sains dan Informatika 3, no. 1 (2025): 36–47. https://doi.org/10.61132/uranus.v3i1.649.

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There are various types of cybersecurity threat in the globe, one of which is an insider threat. Because the current vulnerability generates an insider threat, SMEs suffer. In this situation, the company suffers a loss of profit and trust. Because of the speed and intensity of cybersecurity, particularly internal threats, SMEs must conduct regular vulnerability assessments. Insider threats to cyber security are a major issue in today's environment. Insider threats come in a variety of flavours, one of which is the unintended insider threat, or UIsT. This type of threat is a real one, and it is important to understand who and how they can become an insider threat.
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Dissertations / Theses on the topic "Insider threats"

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Hartline, Cecil L. Jr. "Examination of Insider Threats| A Growing Concern." Thesis, Utica College, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10687276.

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<p> The National Infrastructure Advisory Council (NAIC) reports that "...preventing all insider threats is neither possible nor economically feasible..." because the threat is already behind perimeter defenses and often know exactly where vulnerabilities exist within organizations (Cline, 2016). The purpose of this research was to determine the prevalence of malicious and unintentional insider threats. Statistically, the numbers support the idea that insider threats are increasing and occurring more frequently. The true numbers, which only account for the incidents that were reported, may be higher than originally expected. The statistical numbers are likely to much higher because organizations fear reputational damage and client loss. Organizations give reasons such as not enough evidence for conviction or too hard to prove guilt. The result of the paper indicates that companies focus most of their resources on external threats and not the insider threat that is costlier to remediate and considered the most damaging of all threats. The research focuses on malicious and unintentional insider threats and how they are different. A 2018 Crowd Research Partners report found 90% of organizations believe they are vulnerable to insider attacks, while 53% of businesses confirmed they had experienced an insider threat in the past 12 months (Crowd Research Partners, 2017a). The insider threat is hard to manage because an organization not only need worry about their own employees they also must monitor and manage third-party vendors, partners, and contractors. However, with a combination of technical and nontechnical solutions, including an insider threat program, companies can detect, deter, prevent or at least reduce the impacts of insider threats. Abstract The National Infrastructure Advisory Council (NAIC) reports that "...preventing all insider threats is neither possible nor economically feasible..." because the threat is already behind perimeter defenses and often know exactly where vulnerabilities exist within organizations (Cline, 2016). The purpose of this research was to determine the prevalence of malicious and unintentional insider threats. Statistically, the numbers support the idea that insider threats are increasing and occurring more frequently. The true numbers, which only account for the incidents that were reported, may be higher than originally expected. The statistical numbers are likely to much higher because organizations fear reputational damage and client loss. Organizations give reasons such as not enough evidence for conviction or too hard to prove guilt. The result of the paper indicates that companies focus most of their resources on external threats and not the insider threat that is costlier to remediate and considered the most damaging of all threats. The research focuses on malicious and unintentional insider threats and how they are different. A 2018 Crowd Research Partners report found 90% of organizations believe they are vulnerable to insider attacks, while 53% of businesses confirmed they had experienced an insider threat in the past 12 months (Crowd Research Partners, 2017a). The insider threat is hard to manage because an organization not only need worry about their own employees they also must monitor and manage third-party vendors, partners, and contractors. However, with a combination of technical and nontechnical solutions, including an insider threat program, companies can detect, deter, prevent or at least reduce the impacts of insider threats.</p><p>
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Jenkins, Jeffrey Lyne. "Alleviating Insider Threats: Mitigation Strategies and Detection Techniques." Diss., The University of Arizona, 2013. http://hdl.handle.net/10150/297023.

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Insider threats--trusted members of an organization who compromise security--are considered the greatest security threat to organizations. Because of ignorance, negligence, or malicious intent, insider threats may cause security breaches resulting in substantial damages to organizations and even society. This research helps alleviate the insider threat through developing mitigation strategies and detection techniques in three studies. Study 1 examines how security controls--specifically depth-of-authentication and training recency--alleviate non-malicious insider threats through encouraging secure behavior (i.e., compliance with an organization's security policy). I found that `simpler is better' when implementing security controls, the effects of training diminish rapidly, and intentions are poor predictors of actual secure behavior. Extending Study 1's finding on training recency, Study 2 explains how different types of training alleviate non-malicious insider threat activities. I found that just-in-time reminders are more effective than traditional training programs in improving secure behavior, and again that intentions are not an adequate predictor of actual secure behavior. Both Study 1 and Study 2 introduce effective mitigation strategies for alleviating the non-malicious insider threat; however, they have limited utility when an insider threat has malicious intention, or deliberate intentions to damage the organization. To address this limitation, Study 3 conducts research to develop a tool for detecting malicious insider threats. The tool monitors mouse movements during an insider threat screening survey to detect when respondents are being deceptive. I found that mouse movements are diagnostic of deception. Future research directions are discussed to integrate and extend the findings presented in this dissertation to develop a behavioral information security framework for alleviating both the non-malicious and malicious insider threats in organizations.
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Alawneh, Muntaha. "Mitigating the risk of insider threats when sharing credentials." Thesis, Royal Holloway, University of London, 2012. http://repository.royalholloway.ac.uk/items/aa8e8463-ae05-06f2-ddd9-cc4756a61c86/10/.

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This thesis extends DRM schemes which address the problem of unauthorized proprietary content sharing in home networks to address the problem of unauthorized confidential content sharing in organizations. In particular it focuses on how to achieve secure content sharing between employees in a group while limiting content leakage to unauthorized individuals outside the group. The thesis discusses the main organization types, process work ow and requirements. Our main interest is in organizations which consider content sharing between groups of employees as a fundamental requirement. Achieving secure content sharing requires a deep analysis and understanding of security threats affecting such a fundamental requirement. We study and analyze one of the major threats which affect secure content sharing, which is the threat of content leakage. In this thesis we focus on content leakage which happens when authorized employees share their credentials with others not authorized to access content, thus enabling unauthorized users to access confidential content. Leaking content in this way is what we refer to as content leakage throughout this thesis. We found that to limit the content leakage threat effectively we have to split it into two main categories: internal leakage and external leakage. In the thesis we define each category, discuss the intersection between the categories, and consider how they can be realized. Next, we analyze and assess existing content protection schemes, which focus on content sharing and protection from authorized employees misusing their privileges. These mainly include Enterprise Rights Management (ERM) and Digital Rights Management (DRM) schemes. Based on the analysis we identify the weaknesses found in these schemes for mitigating the content leakage threat. Following that we develop a framework, which we use to mitigate the content leakage threat. This framework is based on the authorized domain concept which was first proposed to address DRM threats. We extend the authorized domain concept so that it consists of a group of devices owned by an organization, whose employees need to share a pool of content amongst each other, e.g. a group of individuals working on a project. In other words, we group devices and content together in a controlled and secure environment. In this thesis, we propose two types of domains: the global domain and the dynamic domain that we use to address the identified content leakage threats. The proposed schemes allow secure content sharing between devices in a dynamic and global domain, and limit the leakage of content to devices outside the domain. Next, we extend our study to cover secure information sharing not only within a single organization but also to cover this important requirement within collaborating organizations. We then describe and analyze how the content leakage threat can be realized between collaborating organizations. We propose a scheme to control content sharing and, simultaneously, to limit the effect of content leakage when an organization needs to collaborate with other organizations.
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Denison, Stephen. "The accessibility of insider threats on a corporate network." Thesis, Utica College, 2015. http://pqdtopen.proquest.com/#viewpdf?dispub=1604807.

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<p> Corporations try to defend themselves against outsider threats, but insider threats can be just as devastating. Insiders have an understanding of their organization&rsquo;s critical assets, physical access to computers, and more privileges than their outside counterparts. This paper will outline three different areas of accessibility issues that insiders can take advantage of in order to leak sensitive information; exfiltration methods, encryption, and corporate considerations of best practices. Data exfiltration focuses on the different techniques that insiders can use to transfer sensitive information. The research outlines how exfiltration has evolved into more sophisticated techniques, but concludes that rudimentary methods associated with external storage devices are still prominently used. Data encryption, if applied properly, can protect sensitive information from unauthorized access, but also creates problems that corporations will have to address. Work productivity can be halted by encryption techniques, causing employees to bypass these systems. Historical cyber attacks show that managing encryption keys are equally important as managing encrypted data, but encryption can still be dismantled through brute force attacks. Corporations will have to make decisions on which best practice methods to choose from in order to defend themselves against insider attacks. Some of these considerations include: risk assessments, employee training, monitoring, password management, data management, and BYOD considerations. Improper utilization of these practices can allow information to be stolen by insiders, but if applied properly, can mitigate the accessibility of insiders. Keywords: insider threats; data exfiltration; Cybersecurity; Professor Christopher Riddell; encryption.</p>
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Elmrabit, Nebrase. "A multiple-perspective approach for insider-threat risk prediction in cyber-security." Thesis, Loughborough University, 2018. https://dspace.lboro.ac.uk/2134/36243.

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Currently governments and research communities are concentrating on insider threat matters more than ever, the main reason for this is that the effect of a malicious insider threat is greater than before. Moreover, leaks and the selling of the mass data have become easier, with the use of the dark web. Malicious insiders can leak confidential data while remaining anonymous. Our approach describes the information gained by looking into insider security threats from the multiple perspective concepts that is based on an integrated three-dimensional approach. The three dimensions are human issue, technology factor, and organisation aspect that forms one risk prediction solution. In the first part of this thesis, we give an overview of the various basic characteristics of insider cyber-security threats. We also consider current approaches and controls of mitigating the level of such threats by broadly classifying them in two categories: a) technical mitigation approaches, and b) non-technical mitigation approaches. We review case studies of insider crimes to understand how authorised users could harm their organisations by dividing these cases into seven groups based on insider threat categories as follows: a) insider IT sabotage, b) insider IT fraud, c) insider theft of intellectual property, d) insider social engineering, e) unintentional insider threat incident, f) insider in cloud computing, and g) insider national security. In the second part of this thesis, we present a novel approach to predict malicious insider threats before the breach takes place. A prediction model was first developed based on the outcomes of the research literature which highlighted main prediction factors with the insider indicator variables. Then Bayesian network statistical methods were used to implement and test the proposed model by using dummy data. A survey was conducted to collect real data from a single organisation. Then a risk level and prediction for each authorised user within the organisation were analysed and measured. Dynamic Bayesian network model was also proposed in this thesis to predict insider threats for a period of time, based on data collected and analysed on different time scales by adding time series factors to the previous model. Results of the verification test comparing the output of 61 cases from the education sector prediction model show a good consistence. The correlation was generally around R-squared =0.87 which indicates an acceptable fit in this area of research. From the result we expected that the approach will be a useful tool for security experts. It provides organisations with an insider threat risk assessment to each authorised user and also organisations can discover their weakness area that needs attention in dealing with insider threat. Moreover, we expect the model to be useful to the researcher's community as the basis for understanding and future research.
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Catrantzos, Nicholas. "No dark corners defending against insider threats to critical infrastructure /." Thesis, Monterey, California : Naval Postgraduate School, 2009. http://edocs.nps.edu/npspubs/scholarly/theses/2009/Sep/09Sep%5FCatrantzos.pdf.

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Thesis (M.A. in Security Studies (Homeland Security and Defense))--Naval Postgraduate School, September 2009.<br>Thesis Advisor(s): Tucker, David. "September 2009." Description based on title screen as viewed on November 03, 2009. Author(s) subject terms: Critical infrastructure protection, insider threat, trust betrayers, infiltrators, disgruntled insiders, Defensible Space, Fixing Broken Windows, employee engagement, No Dark Corners. Includes bibliographical references (p. 85-88). Also available in print.
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Lombardo, Gary. "Predicting the Adoption of Big Data Security Analytics for Detecting Insider Threats." Thesis, Capella University, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10751570.

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<p> Increasingly, organizations are at risk of data breaches due to corporate insider threats. Insiders, in fact, are the biggest threat to corporate data assets and are evading traditional cybersecurity countermeasures. The volume of big data makes insider threat detection more difficult. Conversely big data security analytics (BDSA) enables the detection of anomalous behavior patterns within large datasets in real time, offering organizations potentially a more effective cybersecurity countermeasure for detecting insider threats. However, there was a gap in the literature about what was known about information technology (IT) professionals&rsquo; behavioral intentions (BIs) to adopt BDSA. The overarching management question of this study was whether IT professionals&rsquo; BIs to adopt BDSA were influenced by perceived usefulness (PU) and perceived ease of use (PEOU). This management question led to the investigation of three research questions: The first was if there was a statistically significant relationship between PU and an IT professional&rsquo;s BI to adopt BDSA. The second was if there was a statistically significant relationship between PEOU and an IT professional&rsquo;s BI to adopt BDSA. And, the third was does an IT professional&rsquo;s PEOU of BDSA influence the PU of BDSA. The study used a quantitative, nonexperimental, research design with the technology acceptance model (TAM) as the theoretical framework. Participants included 110 IT professionals with five or more years of experience in the IT field. A Fast Form Approach to Measuring Technology Acceptance and Other Constructs was used to collect data. The instrument had 12 items that used (a) semantic differential scales that ranged in value from -4 to +4 and (b) bipolar labels to measure the two independent variables, PU and PEOU. Multiple linear regression was used to measure the significance of the relationship between PU and BI, and PEOU and BI. Also measured was the moderating effect of the independent variable, PEOU, on the dependent variable, PU. Finally, multivariate adaptive regression splines (MARS) measured the predictive power of the TAM. The findings of this study indicate a statistically significant relationship between PU and an IT professional&rsquo;s BI to adopt BDSA and a statistically significant relationship between PEOU and PU. However, there was no statistically significant relationship between PEOU and an IT professional&rsquo;s BI to adopt BDSA. The MARS analysis indicated the TAM had strong predictive power. The practical implications of this study inform IT practitioners on the importance of technology usefulness. In the case of BDSA, the computational outcome must be reliable and provide value. Also, given the challenges of developing and effectively using BDSA, addressing the issue of ease of use may be important for IT practitioners to adopt and use BDSA. Moreover, as an IT practitioner gains experience with BDSA, the ability to extract value from big data influences PEOU and strengthens its relationship with PU.</p><p>
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Clarke, Karla A. "Novel Alert Visualization: The Development of a Visual Analytics Prototype for Mitigation of Malicious Insider Cyber Threats." Diss., NSUWorks, 2018. https://nsuworks.nova.edu/gscis_etd/1049.

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Cyber insider threat is one of the most difficult risks to mitigate in organizations. However, innovative validated visualizations for cyber analysts to better decipher and react to detected anomalies has not been reported in literature or in industry. Attacks caused by malicious insiders can cause millions of dollars in losses to an organization. Though there have been advances in Intrusion Detection Systems (IDSs) over the last three decades, traditional IDSs do not specialize in anomaly identification caused by insiders. There is also a profuse amount of data being presented to cyber analysts when deciphering big data and reacting to data breach incidents using complex information systems. Information visualization is pertinent to the identification and mitigation of malicious cyber insider threats. The main goal of this study was to develop and validate, using Subject Matter Experts (SME), an executive insider threat dashboard visualization prototype. Using the developed prototype, an experimental study was conducted, which aimed to assess the perceived effectiveness in enhancing the analysts’ interface when complex data correlations are presented to mitigate malicious insiders cyber threats. Dashboard-based visualization techniques could be used to give full visibility of network progress and problems in real-time, especially within complex and stressful environments. For instance, in an Emergency Room (ER), there are four main vital signs used for urgent patient triage. Cybersecurity vital signs can give cyber analysts clear focal points during high severity issues. Pilots must expeditiously reference the Heads Up Display (HUD), which presents only key indicators to make critical decisions during unwarranted deviations or an immediate threat. Current dashboard-based visualization techniques have yet to be fully validated within the field of cybersecurity. This study developed a visualization prototype based on SME input utilizing the Delphi method. SMEs validated the perceived effectiveness of several different types of the developed visualization dashboard. Quantitative analysis of SME’s perceived effectiveness via self-reported value and satisfaction data as well as qualitative analysis of feedback provided during the experiments using the prototype developed were performed. This study identified critical cyber visualization variables and identified visualization techniques. The identifications were then used to develop QUICK.v™ a prototype to be used when mitigating potentially malicious cyber insider threats. The perceived effectiveness of QUICK.v™ was then validated. Insights from this study can aid organizations in enhancing cybersecurity dashboard visualizations by depicting only critical cybersecurity vital signs.
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Almajed, Yasser M. "A framework for an adaptive early warning and response system for insider privacy breaches." Thesis, De Montfort University, 2015. http://hdl.handle.net/2086/11129.

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Organisations such as governments and healthcare bodies are increasingly responsible for managing large amounts of personal information, and the increasing complexity of modern information systems is causing growing concerns about the protection of these assets from insider threats. Insider threats are very difficult to handle, because the insiders have direct access to information and are trusted by their organisations. The nature of insider privacy breaches varies with the organisation’s acceptable usage policy and the attributes of an insider. However, the level of risk that insiders pose depends on insider breach scenarios including their access patterns and contextual information, such as timing of access. Protection from insider threats is a newly emerging research area, and thus, only few approaches are available that systemise the continuous monitoring of dynamic insider usage characteristics and adaptation depending on the level of risk. The aim of this research is to develop a formal framework for an adaptive early warning and response system for insider privacy breaches within dynamic software systems. This framework will allow the specification of multiple policies at different risk levels, depending on event patterns, timing constraints, and the enforcement of adaptive response actions, to interrupt insider activity. Our framework is based on Usage Control (UCON), a comprehensive model that controls previous, ongoing, and subsequent resource usage. We extend UCON to include interrupt policy decisions, in which multiple policy decisions can be expressed at different risk levels. In particular, interrupt policy decisions can be dynamically adapted upon the occurrence of an event or over time. We propose a computational model that represents the concurrent behaviour of an adaptive early warning and response system in the form of statechart. In addition, we propose a Privacy Breach Specification Language (PBSL) based on this computational model, in which event patterns, timing constraints, and the triggered early warning level are expressed in the form of policy rules. The main features of PBSL are its expressiveness, simplicity, practicality, and formal semantics. The formal semantics of the PBSL, together with a model of the mechanisms enforcing the policies, is given in an operational style. Enforcement mechanisms, which are defined by the outcomes of the policy rules, influence the system state by mutually interacting between the policy rules and the system behaviour. We demonstrate the use of this PBSL with a case study from the e-government domain that includes some real-world insider breach scenarios. The formal framework utilises a tool that supports the animation of the enforcement and policy models. This tool also supports the model checking used to formally verify the safety and progress properties of the system over the policy and the enforcement specifications.
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Munshi, Asmaa Mahdi. "A study of insider threat behaviour: developing a holistic insider threat model." Thesis, Curtin University, 2013. http://hdl.handle.net/20.500.11937/1668.

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This study investigates the factors that influence the insider threat behaviour. The research aims to develop a holistic view of insider threat behaviour and ways to manage it. This research adopts an Explanatory Mixed Methods approach for the research process. Firstly, the researcher collects the quantitative data and then the qualitative data. In the first phase, the holistic insider threat model is developed; in the second phase, best practices are developed to manage the threat.
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Books on the topic "Insider threats"

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Arduin, Pierre-Emmanuel. Insider Threats. John Wiley & Sons, Inc., 2018. http://dx.doi.org/10.1002/9781119419785.

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Bertino, Elisa. Data Protection from Insider Threats. Springer International Publishing, 2012. http://dx.doi.org/10.1007/978-3-031-01890-9.

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Probst, Christian W., Jeffrey Hunker, Dieter Gollmann, and Matt Bishop, eds. Insider Threats in Cyber Security. Springer US, 2010. http://dx.doi.org/10.1007/978-1-4419-7133-3.

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Contos, Brian T. Enemy at the Water Cooler: Real-Life Stories of Insider Threats and Enterprise Security Management Countermeasures. Elsevier, 2009.

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Andrew, Moore, and Trzeciak Randall, eds. The CERT guide to insider threats: How to prevent, detect, and respond to information technology crimes (theft, sabotage, fraud). Addison-Wesley, 2012.

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Elam, Jason. Inside threat: A Riley Covington thriller. Tyndale House Publishers, 2011.

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Godse, Vinayak. The threat within: A study on insider threat by DSCI in collaboration with PwC. Data Security Council of India, 2011.

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1954-, Hoffman Bruce, United States. Dept. of Energy., and Rand Corporation, eds. Insider crime: The threat to nuclear facilities and programs. Rand Corp., 1990.

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Arduin, Pierre-Emmanuel. Insider Threats. Wiley & Sons, Incorporated, John, 2018.

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Arduin, Pierre-Emmanuel. Insider Threats. Wiley & Sons, Incorporated, John, 2018.

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Book chapters on the topic "Insider threats"

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Haber, Morey J., and Brad Hibbert. "Insider Threats." In Privileged Attack Vectors. Apress, 2017. http://dx.doi.org/10.1007/978-1-4842-3048-0_6.

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Fennelly, Lawrence J., and Marianna A. Perry. "Insider Threats." In Security Officers and Supervisors. CRC Press, 2024. http://dx.doi.org/10.4324/9781003402718-124.

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Edwards, Dr Jason. "Insider Threats." In Mastering Cybersecurity. Apress, 2024. http://dx.doi.org/10.1007/979-8-8688-0297-3_14.

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Catrantzos, Nick. "Anomalous Insider Threats." In Managing the Insider Threat, 2nd ed. CRC Press, 2022. http://dx.doi.org/10.4324/9781003292678-12.

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Catrantzos, Nick. "Mortal Insider Threats." In Managing the Insider Threat, 2nd ed. CRC Press, 2022. http://dx.doi.org/10.4324/9781003292678-10.

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Neumann, Peter G. "Combatting Insider Threats." In Insider Threats in Cyber Security. Springer US, 2010. http://dx.doi.org/10.1007/978-1-4419-7133-3_2.

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Haber, Morey J. "Insider and External Threats." In Privileged Attack Vectors. Apress, 2020. http://dx.doi.org/10.1007/978-1-4842-5914-6_7.

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Claycomb, William R., and John McCloud. "Protection from Insider Threats." In Encyclopedia of Database Systems. Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4899-7993-3_80602-1.

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Probst, Christian W., Jeffrey Hunker, Dieter Gollmann, and Matt Bishop. "Aspects of Insider Threats." In Insider Threats in Cyber Security. Springer US, 2010. http://dx.doi.org/10.1007/978-1-4419-7133-3_1.

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Claycomb, William R., and John McCloud. "Protection from Insider Threats." In Encyclopedia of Database Systems. Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4614-8265-9_80602.

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Conference papers on the topic "Insider threats"

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S P, Manikandan, K. Ashok Kumar, T. Sai Harsha Vardhan, G. Thanigaivel, B. Venkataramanaiah, and Vijaya Vardan Reddy S P. "Detecting Insider Threats in Cybersecurity Using Machine Learning." In 2024 International Conference on IoT Based Control Networks and Intelligent Systems (ICICNIS). IEEE, 2024. https://doi.org/10.1109/icicnis64247.2024.10823353.

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Zewdie, Marshet, Anteneh Girma, and Tilahun Melak Sitote. "Deep Neural Networks for Detecting Insider Threats and Social Engineering Attacks." In 2024 International Conference on Electrical, Computer and Energy Technologies (ICECET). IEEE, 2024. http://dx.doi.org/10.1109/icecet61485.2024.10698519.

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Adeniyi, Abidemi Emmanuel, Mercy Oka Ebute, Halleluyah Oluwatobi Aworinde, Agbotiname Lucky Imoize, Joseph Bamidele Awotunde, and Oluwaferanmi Adedamola Adewusi. "Development of Cryptographic Algorithms for Protecting Cloud Data from Insider Threats." In 2024 IEEE 5th International Conference on Electro-Computing Technologies for Humanity (NIGERCON). IEEE, 2024. https://doi.org/10.1109/nigercon62786.2024.10927213.

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McGough, Andrew Stephen, David Wall, John Brennan, et al. "Insider Threats." In CCS'15: The 22nd ACM Conference on Computer and Communications Security. ACM, 2015. http://dx.doi.org/10.1145/2808783.2808785.

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Greitzer, Frank L. "Insider Threats." In NCS '19: Northwest Cybersecurity Symposium. ACM, 2019. http://dx.doi.org/10.1145/3332448.3332458.

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Claycomb, William R. "Detecting Insider Threats." In CCS'15: The 22nd ACM Conference on Computer and Communications Security. ACM, 2015. http://dx.doi.org/10.1145/2808783.2808794.

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Haim, Bar, Eitan Menahem, Yaron Wolfsthal, and Christopher Meenan. "Visualizing Insider Threats." In IUI'17: 22nd International Conference on Intelligent User Interfaces. ACM, 2017. http://dx.doi.org/10.1145/3030024.3038264.

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Claycomb, William R., Carly L. Huth, Brittany Phillips, Lori Flynn, and David McIntire. "Identifying indicators of insider threats: Insider IT sabotage." In 2013 International Carnahan Conference on Security Technology (ICCST). IEEE, 2013. http://dx.doi.org/10.1109/ccst.2013.6922038.

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Stamati-Koromina, Veroniki, Christos Ilioudis, Richard Overill, Christos K. Georgiadis, and Demosthenes Stamatis. "Insider threats in corporate environments." In the Fifth Balkan Conference in Informatics. ACM Press, 2012. http://dx.doi.org/10.1145/2371316.2371374.

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"Modelling of Enterprise Insider Threats." In 1st International Conference on Information Systems Security and Privacy. SCITEPRESS - Science and and Technology Publications, 2015. http://dx.doi.org/10.5220/0005327901320136.

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Reports on the topic "Insider threats"

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Hallahan, Jason. Countering Insider Threats - Handling Insider Threats Using Dynamic, Run-Time Forensics. Defense Technical Information Center, 2007. http://dx.doi.org/10.21236/ada473440.

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Reiher, Peter. File Profiling for Insider Threats. Defense Technical Information Center, 2002. http://dx.doi.org/10.21236/ada405498.

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Santos, Jr, and Eugene. On Insider Threats, Deception, and User Modeling. Defense Technical Information Center, 2011. http://dx.doi.org/10.21236/ada567009.

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Silowash, George, Dawn Cappelli, Andrew Moore, Randall Trzeciak, Timothy J. Shimeall, and Lori Flynn. Common Sense Guide to Mitigating Insider Threats 4th Edition. Defense Technical Information Center, 2012. http://dx.doi.org/10.21236/ada585500.

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Greitzer, Frank L., Lars J. Kangas, Christine F. Noonan, and Angela C. Dalton. Identifying at-risk employees: A behavioral model for predicting potential insider threats. Office of Scientific and Technical Information (OSTI), 2010. http://dx.doi.org/10.2172/1000159.

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Kelly, Luke. Threats to Civilian Aviation Since 1975. Institute of Development Studies (IDS), 2021. http://dx.doi.org/10.19088/k4d.2021.019.

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Abstract:
This literature review finds that the main malicious threats to civilian aviation since 1975 are attacks by terrorist groups, deliberate or accidental damage arising from conflicts, and incidents caused by people who work for airlines or airports. While the sector has responded to hijackings and bombings with increasing security since the 1970s, actors seeking to attack aircraft have modified their tactics, and new threats such as liquid explosives and cyber attacks have emerged. Civilian aviation has seen relatively fewer accidents and deaths over the years, but threats remain. The review focuses on malicious threats to civilian aviation. It, therefore, excludes weather events or accidents. The first section lists major malicious threats to civilian aviation since 1975. It includes both actual and planned events (e.g. hijackings that were prevented) that are recorded in open-source documents. Each threat is listed alongside information on its cause (e.g. terrorism, state actions, crime), the context in which it occurred (broader factors shaping the risk including geography, regime type, technology), and its impact (on passengers, policy, security, economic). The second section discusses some of the trends in threats to aviation. Motives for malicious threats include terrorism, crime, asylum-seeking, and insider attacks by aggrieved or mentally ill airline staff. Hijacking has been the most common form of threat, although bombing or suicide attacks have killed more people. Threats may also take the form of accidental attacks on civilian planes misidentified as threats in conflict zones. Experts suggest that growing threats are cyberattacks and the use of unmanned aerial vehicles, although neither has yet caused a major incident.
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CALIFORNIA UNIV LOS ANGELES. DoD Insider Threat Mitigation. Defense Technical Information Center, 1999. http://dx.doi.org/10.21236/ada385423.

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Montelibano, Joji, and Andrew Moore. Insider Threat Security Reference Architecture. Defense Technical Information Center, 2012. http://dx.doi.org/10.21236/ada609926.

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Wong, F. Insider Threat Symposium Curated Questions. Office of Scientific and Technical Information (OSTI), 2019. http://dx.doi.org/10.2172/1548366.

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Maxion, R. A., K. M. Tan, S. S. Killourhy, and T. N. Townsend. Profiler-2000: Attacking the Insider Threat. Defense Technical Information Center, 2005. http://dx.doi.org/10.21236/ada439600.

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