838 research outputs found

    Impact and key challenges of insider threats on organizations and critical businesses

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    The insider threat has consistently been identified as a key threat to organizations and governments. Understanding the nature of insider threats and the related threat landscape can help in forming mitigation strategies, including non-technical means. In this paper, we survey and highlight challenges associated with the identification and detection of insider threats in both public and private sector organizations, especially those part of a nation’s critical infrastructure. We explore the utility of the cyber kill chain to understand insider threats, as well as understanding the underpinning human behavior and psychological factors. The existing defense techniques are discussed and critically analyzed, and improvements are suggested, in line with the current state-of-the-art cyber security requirements. Finally, open problems related to the insider threat are identified and future research directions are discussed

    Data-Driven and Artificial Intelligence (AI) Approach for Modelling and Analyzing Healthcare Security Practice: A Systematic Review

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    Data breaches in healthcare continue to grow exponentially, calling for a rethinking into better approaches of security measures towards mitigating the menace. Traditional approaches including technological measures, have significantly contributed to mitigating data breaches but what is still lacking is the development of the “human firewall,” which is the conscious care security practices of the insiders. As a result, the healthcare security practice analysis, modeling and incentivization project (HSPAMI) is geared towards analyzing healthcare staffs’ security practices in various scenarios including big data. The intention is to determine the gap between staffs’ security practices and required security practices for incentivization measures. To address the state-of-the art, a systematic review was conducted to pinpoint appropriate AI methods and data sources that can be used for effective studies. Out of about 130 articles, which were initially identified in the context of human-generated healthcare data for security measures in healthcare, 15 articles were found to meet the inclusion and exclusion criteria. A thorough assessment and analysis of the included article reveals that, KNN, Bayesian Network and Decision Trees (C4.5) algorithms were mostly applied on Electronic Health Records (EHR) Logs and Network logs with varying input features of healthcare staffs’ security practices. What was found challenging is the performance scores of these algorithms which were not sufficiently outlined in the existing studies

    Dealing with the Malicious Insider

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    This paper looks at a number of issues relating to the malicious insider and the nature of motivation, loyalty and the type of attacks that occur. The paper also examines the changing environmental, social, cultural and business issues that have resulted in an increased exposure to the insider threat. The paper then discusses a range of measures that can be taken to reduce both the likelihood of an attack and the impact that such an attack may have. These measures should be driven by focused and effective risk management processes

    Development and Validation of a Proof-of-Concept Prototype for Analytics-based Malicious Cybersecurity Insider Threat in a Real-Time Identification System

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    Insider threat has continued to be one of the most difficult cybersecurity threat vectors detectable by contemporary technologies. Most organizations apply standard technology-based practices to detect unusual network activity. While there have been significant advances in intrusion detection systems (IDS) as well as security incident and event management solutions (SIEM), these technologies fail to take into consideration the human aspects of personality and emotion in computer use and network activity, since insider threats are human-initiated. External influencers impact how an end-user interacts with both colleagues and organizational resources. Taking into consideration external influencers, such as personality, changes in organizational polices and structure, along with unusual technical activity analysis, would be an improvement over contemporary detection tools used for identifying at-risk employees. This would allow upper management or other organizational units to intervene before a malicious cybersecurity insider threat event occurs, or mitigate it quickly, once initiated. The main goal of this research study was to design, develop, and validate a proof-of-concept prototype for a malicious cybersecurity insider threat alerting system that will assist in the rapid detection and prediction of human-centric precursors to malicious cybersecurity insider threat activity. Disgruntled employees or end-users wishing to cause harm to the organization may do so by abusing the trust given to them in their access to available network and organizational resources. Reports on malicious insider threat actions indicated that insider threat attacks make up roughly 23% of all cybercrime incidents, resulting in $2.9 trillion in employee fraud losses globally. The damage and negative impact that insider threats cause was reported to be higher than that of outsider or other types of cybercrime incidents. Consequently, this study utilized weighted indicators to measure and correlate simulated user activity to possible precursors to malicious cybersecurity insider threat attacks. This study consisted of a mixed method approach utilizing an expert panel, developmental research, and quantitative data analysis using the developed tool on simulated data set. To assure validity and reliability of the indicators, a panel of subject matter experts (SMEs) reviewed the indicators and indicator categorizations that were collected from prior literature following the Delphi technique. The SMEs’ responses were incorporated into the development of a proof-of-concept prototype. Once the proof-of-concept prototype was completed and fully tested, an empirical simulation research study was conducted utilizing simulated user activity within a 16-month time frame. The results of the empirical simulation study were analyzed and presented. Recommendations resulting from the study also be provided

    Mitigating Insider Sabotage and Espionage: A Review of the United States Air Force\u27s Current Posture

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    The security threat from malicious insiders affects all organizations. Mitigating this problem is quite difficult due to the fact that (1) there is no definitive profile for malicious insiders, (2) organizations have placed trust in these individuals, and (3) insiders have a vast knowledge of their organization’s personnel, security policies, and information systems. The purpose of this research is to analyze to what extent the United States Air Force (USAF) security policies address the insider threat problem. The policies are reviewed in terms of how well they align with best practices published by the Carnegie Mellon University Computer Emergency Readiness Team and additional factors this research deems important, including motivations, organizational priorities, and social networks. Based on the findings of the policy review, this research offers actionable recommendations that the USAF could implement in order to better prevent, detect, and respond to malicious insider attacks. The most important course of action is to better utilize its workforce. All personnel should be trained on observable behaviors that can be precursors to malicious activity. Additionally, supervisors need to be empowered as the first line of defense, monitoring for stress, unmet expectations, and disgruntlement. In addition, this research proposes three new best practices regarding (1) screening for prior concerning behaviors, predispositions, and technical incidents, (2) issuing sanctions for inappropriate technical acts, and (3) requiring supervisors to take a proactive role

    Novel Alert Visualization: The Development of a Visual Analytics Prototype for Mitigation of Malicious Insider Cyber Threats

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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

    Development of a Methodology for Customizing Insider Threat Auditing on a Linux Operating System

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    Insider threats can pose a great risk to organizations and by their very nature are difficult to protect against. Auditing and system logging are capabilities present in most operating systems and can be used for detecting insider activity. However, current auditing methods are typically applied in a haphazard way, if at all, and are not conducive to contributing to an effective insider threat security policy. This research develops a methodology for designing a customized auditing and logging template for a Linux operating system. An intent-based insider threat risk assessment methodology is presented to create use case scenarios tailored to address an organization’s specific security needs and priorities. These organization specific use cases are verified to be detectable via the Linux auditing and logging subsystems and the results are analyzed to create an effective auditing rule set and logging configuration for the detectable use cases. Results indicate that creating a customized auditing rule set and system logging configuration to detect insider threat activity is possible

    Cloud Forensic: Issues, Challenges and Solution Models

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    Cloud computing is a web-based utility model that is becoming popular every day with the emergence of 4th Industrial Revolution, therefore, cybercrimes that affect web-based systems are also relevant to cloud computing. In order to conduct a forensic investigation into a cyber-attack, it is necessary to identify and locate the source of the attack as soon as possible. Although significant study has been done in this domain on obstacles and its solutions, research on approaches and strategies is still in its development stage. There are barriers at every stage of cloud forensics, therefore, before we can come up with a comprehensive way to deal with these problems, we must first comprehend the cloud technology and its forensics environment. Although there are articles that are linked to cloud forensics, there is not yet a paper that accumulated the contemporary concerns and solutions related to cloud forensic. Throughout this chapter, we have looked at the cloud environment, as well as the threats and attacks that it may be subjected to. We have also looked at the approaches that cloud forensics may take, as well as the various frameworks and the practical challenges and limitations they may face when dealing with cloud forensic investigations.Comment: 23 pages; 6 figures; 4 tables. Book chapter of the book titled "A Practical Guide on Security and Privacy in Cyber Physical Systems Foundations, Applications and Limitations", World Scientific Series in Digital Forensics and Cybersecurit
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