Relevant bibliographies by topics / Malicious insider

Contents

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

Academic literature on the topic 'Malicious insider'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Malicious insider"

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Nguyen, Minh-Duong, Ngoc-Tu Chau, Seungwook Jung, and Souhwan Jung. "A Demonstration of Malicious Insider Attacks inside Cloud IaaS Vendor." International Journal of Information and Education Technology 4, no. 6 (2014): 483–86. http://dx.doi.org/10.7763/ijiet.2014.v4.455.

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Jones, Andy. "Catching the malicious insider." Information Security Technical Report 13, no. 4 (2008): 220–24. http://dx.doi.org/10.1016/j.istr.2008.10.008.

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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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Glancy, Fletcher, David P. Biros, Nan Liang, and Andy Luse. "Classification of malicious insiders and the association of the forms of attacks." Journal of Criminal Psychology 10, no. 3 (2020): 233–47. http://dx.doi.org/10.1108/jcp-03-2020-0012.

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Purpose The authors argue that the current studies about malicious insiders confuse the fact that malicious attacks belong to two different categories, namely, those that launch instrumental attacks and expressive attacks. The authors collect malicious insider data from publicly available sources and use text-mining techniques to analyze the association between malicious insiders’ characteristics and the different types of attack. Design/methodology/approach The authors investigated the relationship between personality characteristics and different types of malicious attacks. For the personality characteristics, the authors use the same method as Liang et al. (2016), which extracted these characteristics based on a keyword-characteristic dictionary. For different types of malicious attacks, two raters rated each case based on criteria modified from criminology research to determine the degree of expressiveness and instrumentality. Findings The results show that malicious insiders who are manipulative or seeking personal gain tend to carry out instrumental attacks. Malicious insiders who are arrogant tend to conduct expressive attacks. Research limitations/implications This study uses third party articles to identify the personality characteristics of known malicious insiders. As such, not all personality characteristics may have been reported. Data availability was an issue. Practical implications Understanding if different personality characteristics lead different types of attacks can help managers identify employees who exhibit them and mitigate an attack before it occurs. Social implications Malicious insider attacks can have devastating results on businesses and employees. Help to identify potential malicious insiders before they act, may prevent undue harm. Originality/value This study used 132 cases of none malicious insiders to examine their attack objectives. No other study that the authors know of used that many cases.
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Clarke, Karla, Yair Levy, Laurie Dringus, and Shonda Brown. "How workplace satisfaction affects insider threat detection as a vital variable for the mitigation of malicious cyber insiders." Online Journal of Applied Knowledge Management 7, no. 1 (2019): 40–52. http://dx.doi.org/10.36965/ojakm.2019.7(1)40-52.

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Insider threat mitigation is a growing challenge within organizations. The development of a novel alert visualization dashboard for the identification of potentially malicious cyber insider threats was identified as necessary to alleviate this challenge. This research developed a cyber insider threat dashboard visualization prototype for detecting potentially malicious cyber insider activities QUICK.v™. This study utilized Subject Matter Experts (SMEs) by applying the Delphi Method to identify the most critical cyber visualization variables and ranking. This paper contains the detailed results of a survey based experimental research study that identified the critical cybersecurity variables also referred to as cybersecurity vital signs. The identified vital signs will aid cybersecurity analysts with triage for potentially malicious insider threats. From a total of 45 analytic variables assessed by 42 cybersecurity SMEs, the top six variables were identified using a comprehensive data collection process. The results indicated that workplace satisfaction is one of the top critical cyber visualization variables that should be measured and visualized to aid cybersecurity analysts in the detection of potentially malicious cyber insider threat activities. The process of the data collection to identify and rank critical cyber visualization variables are described.
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Kim, Jung Hwan, Chul Min Kim, and Man-Sung Yim. "An Investigation of Insider Threat Mitigation Based on EEG Signal Classification." Sensors 20, no. 21 (2020): 6365. http://dx.doi.org/10.3390/s20216365.

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This study proposes a scheme to identify insider threats in nuclear facilities through the detection of malicious intentions of potential insiders using subject-wise classification. Based on electroencephalography (EEG) signals, a classification model was developed to identify whether a subject has a malicious intention under scenarios of being forced to become an insider threat. The model also distinguishes insider threat scenarios from everyday conflict scenarios. To support model development, 21-channel EEG signals were measured on 25 healthy subjects, and sets of features were extracted from the time, time–frequency, frequency and nonlinear domains. To select the best use of the available features, automatic selection was performed by random-forest-based algorithms. The k-nearest neighbor, support vector machine with radial kernel, naïve Bayes, and multilayer perceptron algorithms were applied for the classification. By using EEG signals obtained while contemplating becoming an insider threat, the subject-wise model identified malicious intentions with 78.57% accuracy. The model also distinguished insider threat scenarios from everyday conflict scenarios with 93.47% accuracy. These findings could be utilized to support the development of insider threat mitigation systems along with existing trustworthiness assessments in the nuclear industry.
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Adikari, Swini. "Countering the Threat of Nuclear Terrorism Arising from Malicious Insiders." Global Affairs Review 1, no. 2 (2021): 1–18. http://dx.doi.org/10.51330/gar.0020214.

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Nuclear theft from malicious insiders is a significant threat to Pakistan’s nuclear weapons arsenal. Pakistan is a member of the Convention of the Physical Protection of Nuclear Material (CPPNM), which is an international agreement that adheres to the protection of nuclear materials and the recovery of stolen nuclear materials. However, this agreement does not specifically take into account the risk of security breaches arising from malicious insiders due to Pakistan’s rapidly growing nuclear arsenal. The purpose of this paper is to examine the heightened risk of insider threats in conjunction with Pakistan’s increasing nuclear force structure. The first section of the paper examines the history of the development of Pakistan’s nuclear weapons programme and discusses Pakistan’s current nuclear force structure. The second section examines the international and domestic policies that Pakistan follows to address the issue of insider threats to Pakistan’s nuclear facilities. The final section proposes two policy alternatives to address Pakistan’s growing insider threat risks and outlines how the Design Basis Threat assessment is the most effective solution for Pakistan’s growing insider threat.
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Park, Won, Youngin You, and Kyungho Lee. "Detecting Potential Insider Threat: Analyzing Insiders’ Sentiment Exposed in Social Media." Security and Communication Networks 2018 (July 18, 2018): 1–8. http://dx.doi.org/10.1155/2018/7243296.

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In the era of Internet of Things (IoT), impact of social media is increasing gradually. With the huge progress in the IoT device, insider threat is becoming much more dangerous. Trying to find what kind of people are in high risk for the organization, about one million of tweets were analyzed by sentiment analysis methodology. Dataset made by the web service “Sentiment140” was used to find possible malicious insider. Based on the analysis of the sentiment level, users with negative sentiments were classified by the criteria and then selected as possible malicious insiders according to the threat level. Machine learning algorithms in the open-sourced machine learning software “Weka (Waikato Environment for Knowledge Analysis)” were used to find the possible malicious insider. Decision Tree had the highest accuracy among supervised learning algorithms and K-Means had the highest accuracy among unsupervised learning. In addition, we extract the frequently used words from the topic modeling technique and then verified the analysis results by matching them to the information security compliance elements. These findings can contribute to achieve higher detection accuracy by combining individual’s characteristics to the previous studies such as analyzing system behavior.
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Polyanichko, M. "Methodology for Detecting Anomalous Interaction of Users with Information Assets to Identify Insider Activity." Proceedings of Telecommunication Universities 6, no. 1 (2020): 94–98. http://dx.doi.org/10.31854/1813-324x-2020-6-1-94-98.

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The article describe us that the identification of insiders and insider activities in the organization is an actual direction of ensuring information security, since the high level of software development and hardware information protection brings the malicious actions of legitimate users to the fore. This article discusses the methodology which allows to identify anomalies in the organization’s employees interaction with information assets and its applicability is assessed in the context of work to detect malicious activities of insiders.
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Saranjame, Rahul, and Manik Lal Das. "Securing Digital Image from Malicious Insider Attacks." International Journal of Computer Vision and Image Processing 8, no. 2 (2018): 49–58. http://dx.doi.org/10.4018/ijcvip.2018040103.

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Protection of digital images from malicious (and dishonest) insider entities is an important concern in modern digital space. A malicious entity can alter some important features of an image to mislead the target recipient of the image, which can cause harm in applications such as healthcare, insurance, product description and so on. In order to protect digital images, cryptographic primitives such as pseudo-random function and digital signature have been used in practice for image protection. In this article, the authors present a method of image protection from malicious image manipulation. The authors use the concept of secret sharing and public key primitives in the proposed method. This article discusses on attacks involving generation of fake shares to cheat honest user(s) and a demonstration of the proposed system employing a centralized server to generate shares and authenticate them on the basis of requests is made as a counter to the described attack.
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Dissertations / Theses on the topic "Malicious insider"

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Schluderberg, Larry E. "Addressing the cybersecurity Malicious Insider threat." Thesis, Utica College, 2015. http://pqdtopen.proquest.com/#viewpdf?dispub=1571095.

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<p> Malicious Insider threats consist of employees, contractors, or business partners who either have current authorized access, or have had authorized access to an organization's critical information and have intentionally misused that access in a manner that compromised the organization. Although incidents initiated by malicious insiders are fewer in number than those initiated by external threats, insider incidents are more costly on average because the threat is already trusted by the organization and often has privileged access to the organization's most sensitive information. In spite of the damage they cause there are indications that the seriousness of insider incidents are underappreciated as threats by management. The purpose of this research was to investigate who constitutes MI threats, why and how they initiate attacks, the extent to which MI activity can be modeled or predicted, and to suggest some risk mitigation strategies. The results reveal that addressing the Malicious Insider threat is much more than just a technical issue. Dealing effectively with the threat involves managing the dynamic interaction between employees, their work environment and work associates, the systems with which they interact, and organizational policies and procedures. Techniques for detecting and mitigating the threat are available and can be effectively applied. Some of the procedural and technical methods include definition of, follow through, and consistent application of corporate, and dealing with adverse events indigenous to the business environment. Other methods include conduct of a comprehensive Malicious Insider risk assessment, selective monitoring of employees in response to behavioral precursors, minimizing unknown access paths, control of the organization's production software baseline, and effective use of peer reporting.</p><p> Keywords: Cybersecurity, Professor Paul Pantani, CERT, insider, threat, IDS, SIEMS. FIM, RBAC, ABAC, behavioral, peer, precursors, access, authentication, predictive, analytics, system, dynamics, demographics.</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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Ofori-Duodu, Michael Samuel. "Exploring Data Security Management Strategies for Preventing Data Breaches." ScholarWorks, 2019. https://scholarworks.waldenu.edu/dissertations/7947.

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Insider threat continues to pose a risk to organizations, and in some cases, the country at large. Data breach events continue to show the insider threat risk has not subsided. This qualitative case study sought to explore the data security management strategies used by database and system administrators to prevent data breaches by malicious insiders. The study population consisted of database administrators and system administrators from a government contracting agency in the northeastern region of the United States. The general systems theory, developed by Von Bertalanffy, was used as the conceptual framework for the research study. The data collection process involved interviewing database and system administrators (n = 8), organizational documents and processes (n = 6), and direct observation of a training meeting (n = 3). By using methodological triangulation and by member checking with interviews and direct observation, efforts were taken to enhance the validity of the findings of this study. Through thematic analysis, 4 major themes emerged from the study: enforcement of organizational security policy through training, use of multifaceted identity and access management techniques, use of security frameworks, and use of strong technical control operations mechanisms. The findings of this study may benefit database and system administrators by enhancing their data security management strategies to prevent data breaches by malicious insiders. Enhanced data security management strategies may contribute to social change by protecting organizational and customer data from malicious insiders that could potentially lead to espionage, identity theft, trade secrets exposure, and cyber extortion.
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Landress, Angela D. "The Impact of Mindfulness on Non-malicious Spillage within Images on Social Networking Sites." Thesis, Nova Southeastern University, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10842441.

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<p> Insider threat by employees in organizations is a problematic issue in today&rsquo;s fast-paced, internet-driven society. Gone are the days when securing the perimeter of one&rsquo;s network protected their business. Security threats are now mobile, and employees have the ability to share sensitive business data with hundreds of people instantaneously from mobile devices. While prior research has addressed social networking topics such as trust in relation to information systems, the use of social networking sites, social networking security, and social networking sharing, there is a lack of research in the mindfulness of users who spill sensitive data contained within images posted on social networking sites (SNS). The author seeks to provide an understanding of how non-malicious spillage through images relates to the mindfulness of employees, who are also deemed insiders. Specifically, it explores the relationships between the following variables: mindfulness, proprietary information spillage, and spillage of personally identifiable information (PII). A quasi-experimental study was designed, which was correlational in nature. Individuals were the unit of analysis. A sample population of business managers with SNS accounts were studied. A series of video vignettes were used to measure mindfulness. Surveys were used as a tool to collect and analyze data. There was a positive correlation between non-malicious spillage of sensitive business, both personally identifiable information and proprietary data, and a lack of mindfulness. </p><p>
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Hueca, Angel L. "Development and Validation of a Proof-of-Concept Prototype for Analytics-based Malicious Cybersecurity Insider Threat in a Real-Time Identification System." Diss., NSUWorks, 2018. https://nsuworks.nova.edu/gscis_etd/1063.

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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.
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Kambhampaty, Krishna Kanth. "Detecting Insider and Masquerade Attacks by Identifying Malicious User Behavior and Evaluating Trust in Cloud Computing and IoT Devices." Diss., North Dakota State University, 2019. https://hdl.handle.net/10365/29914.

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There are a variety of communication mediums or devices for interaction. Users hop from one medium to another frequently. Though the increase in the number of devices brings convenience, it also raises security concerns. Provision of platform to users is as much important as its security. In this dissertation we propose a security approach that captures user behavior for identifying malicious activities. System users exhibit certain behavioral patterns while utilizing the resources. User behaviors such as device location, accessing certain files in a server, using a designated or specific user account etc. If this behavior is captured and compared with normal users? behavior, anomalies can be detected. In our model, we have identified malicious users and have assigned trust value to each user accessing the system. When a user accesses new files on the servers that have not been previously accessed, accessing multiple accounts from the same device etc., these users are considered suspicious. If this behavior continues, they are categorized as ingenuine. A trust value is assigned to users. This value determines the trustworthiness of a user. Genuine users get higher trust value and ingenuine users get a lower trust value. The range of trust value varies from zero to one, with one being the highest trustworthiness and zero being the lowest. In our model, we have sixteen different features to track user behavior. These features evaluate users? activities. From the time users? log in to the system till they log out, users are monitored based on these sixteen features. These features determine whether the user is malicious. For instance, features such as accessing too many accounts, using proxy servers, too many incorrect logins attribute to suspicious activity. Higher the number of these features, more suspicious is the user. More such additional features contribute to lower trust value. Identifying malicious users could prevent and/or mitigate the attacks. This will enable in taking timely action against these users from performing any unauthorized or illegal actions. This could prevent insider and masquerade attacks. This application could be utilized in mobile, cloud and pervasive computing platforms.
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Cheng, Chien-Wen, and 鄭傑文. "Identifying potentially malicious behavior inside Android malware by static code analysis." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/44175699278460400644.

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Books on the topic "Malicious insider"

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Dunham, Ken. Malicious bots: An inside look into the cyber-criminal underground of the internet. Auerbach Publications, 2008.

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Malicious Bots: An Inside Look into the Cyber-Criminal Underground of the Internet. AUERBACH, 2008.

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Zhdanova, Mariia, and Dariya Orlova. Ukraine. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190931407.003.0003.

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This chapter examines the state of computational propaganda in Ukraine, focusing on two major dimensions: Ukraine’s response to the challenges of external information attacks, and the use of computational propaganda in internal political communication. Based on interviews with Ukrainian media experts, academics, industry insiders, and bot developers, the chapter explores the scale of the issue and identifies the most common tactics, instruments, and approaches for the deployment of political bots online. The cases described illustrate the misconceptions about fake accounts, paid online commentators, and automated scripts, as well as the threats of malicious online activities. First, we explain how bots operate in the internal political and media environment of the country and provide examples of typical campaigns. Second, we analyze the case of the MH17 tragedy as an illustrative example of Russia’s purposeful disinformation campaign against Ukraine, which has a distinctive social media component. Finally, responses to computational propaganda are scrutinized, including alleged governmental attacks on Ukrainian journalists, which reveal that civil society and grassroots movements have great potential to stand up to the perils of computational propaganda.
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Book chapters on the topic "Malicious insider"

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Li, Weihan, Brajendra Panda, and Qussai Yaseen. "Malicious Users’ Transactions: Tackling Insider Threat." In IFIP Advances in Information and Communication Technology. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-30436-1_18.

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Chen, Taolue, Florian Kammüller, Ibrahim Nemli, and Christian W. Probst. "A Probabilistic Analysis Framework for Malicious Insider Threats." In Lecture Notes in Computer Science. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-20376-8_16.

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Niihara, Koichi, and Hiroaki Kikuchi. "Primary Factors of Malicious Insider in E-learning Model." In HCI International 2016 – Posters' Extended Abstracts. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-40548-3_80.

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Ibrahim, Amjad, Simon Rehwald, Antoine Scemama, Florian Andres, and Alexander Pretschner. "Causal Model Extraction from Attack Trees to Attribute Malicious Insider Attacks." In Graphical Models for Security. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-62230-5_1.

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Fagade, Tesleem, Theo Spyridopoulos, Nabeel Albishry, and Theo Tryfonas. "System Dynamics Approach to Malicious Insider Cyber-Threat Modelling and Analysis." In Human Aspects of Information Security, Privacy and Trust. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-58460-7_21.

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Hugl, Ulrike. "Putting a Hat on a Hen? Learnings for Malicious Insider Threat Prevention from the Background of German White-Collar Crime Research." In Lecture Notes in Computer Science. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-20376-8_56.

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Ragavan, Harini, and Brajendra Panda. "Mitigation of Malicious Modifications by Insiders in Databases." In Information Systems Security. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-25560-1_23.

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Stavrou, Angelos, Michael E. Locasto, and Angelos D. Keromytis. "Pushback for Overlay Networks: Protecting Against Malicious Insiders." In Applied Cryptography and Network Security. Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-68914-0_3.

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Wang, Xiao, Jinqiao Shi, and Li Guo. "Towards Analyzing Traceability of Data Leakage by Malicious Insiders." In Trustworthy Computing and Services. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-35795-4_19.

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Ray, Indrajit, and Nayot Poolsapassit. "Using Attack Trees to Identify Malicious Attacks from Authorized Insiders." In Computer Security – ESORICS 2005. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11555827_14.

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Conference papers on the topic "Malicious insider"

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Berk, Vincent H., George Cybenko, Ian Gregorio-de Souza, and John P. Murphy. "Managing Malicious Insider Risk through BANDIT." In 2012 45th Hawaii International Conference on System Sciences (HICSS). IEEE, 2012. http://dx.doi.org/10.1109/hicss.2012.420.

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Patil, Dinesh, and Bandu Meshram. "Network Packet Analysis for Detecting Malicious Insider." In 2018 3rd International Conference for Convergence in Technology (I2CT). IEEE, 2018. http://dx.doi.org/10.1109/i2ct.2018.8529451.

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Gamachchi, Anagi, Li Sun, and Serdar Boztas. "Graph Based Framework for Malicious Insider Threat Detection." In Hawaii International Conference on System Sciences. Hawaii International Conference on System Sciences, 2017. http://dx.doi.org/10.24251/hicss.2017.319.

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Ragavan, Harini, and Brajendra Panda. "Mitigating Malicious Updates: Prevention of Insider Threat to Databases." In 2013 12th IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom). IEEE, 2013. http://dx.doi.org/10.1109/trustcom.2013.95.

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Nance, Kara, and Raffael Marty. "Identifying and Visualizing the Malicious Insider Threat Using Bipartite Graphs." In 2011 44th Hawaii International Conference on System Sciences (HICSS 2011). IEEE, 2011. http://dx.doi.org/10.1109/hicss.2011.231.

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Hashem, Yassir, Hassan Takabi, Ram Dantu, and Rodney Nielsen. "A Multi-Modal Neuro-Physiological Study of Malicious Insider Threats." In CCS '17: 2017 ACM SIGSAC Conference on Computer and Communications Security. ACM, 2017. http://dx.doi.org/10.1145/3139923.3139930.

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Chagarlamudi, Manideep, Brajendra Panda, and Yi Hu. "Insider Threat in Database Systems: Preventing Malicious Users' Activities in Databases." In 2009 Sixth International Conference on Information Technology: New Generations. IEEE, 2009. http://dx.doi.org/10.1109/itng.2009.67.

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Legg, Philip A. "Visualizing the insider threat: challenges and tools for identifying malicious user activity." In 2015 IEEE Symposium on Visualization for Cyber Security (VizSec). IEEE, 2015. http://dx.doi.org/10.1109/vizsec.2015.7312772.

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Nikolai, Jason, and Yong Wang. "A System for Detecting Malicious Insider Data Theft in IaaS Cloud Environments." In GLOBECOM 2016 - 2016 IEEE Global Communications Conference. IEEE, 2016. http://dx.doi.org/10.1109/glocom.2016.7841554.

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Nkosi, Lucky, Paul Tarwireyi, and Matthew O. Adigun. "Detecting a malicious insider in the cloud environment using sequential rule mining." In 2013 International Conference on Adaptive Science and Technology (ICAST). IEEE, 2013. http://dx.doi.org/10.1109/icastech.2013.6707505.

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Reports on the topic "Malicious insider"

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Silowash, George J., and Todd B. Lewellen. Insider Threat Control: Using Universal Serial Bus (USB) Device Auditing to Detect Possible Data Exfiltration by Malicious Insiders. Defense Technical Information Center, 2013. http://dx.doi.org/10.21236/ada610588.

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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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Noonan, Christine F. Spy the Lie: Detecting Malicious Insiders. Office of Scientific and Technical Information (OSTI), 2018. http://dx.doi.org/10.2172/1452870.

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Herzog, Jonathan, Gabriel Wachman, and Dan Liu. On the Robustness of Cognitive Networking Mechanisms to Malicious Insiders. Defense Technical Information Center, 2011. http://dx.doi.org/10.21236/ada573492.

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You might also be interested in the extended bibliographies on the topic 'Malicious insider' for particular source types:
Journal articles
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