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2020-01-21
Zhang, Chiyu, Hwang, Inseok.  2019.  Decentralized Multi-Sensor Scheduling for Multi-Target Tracking and Identity Management. 2019 18th European Control Conference (ECC). :1804–1809.
This paper proposes a multi-target tracking and identity management method with multiple sensors: a primary sensor with a large detection range to provide the targets' state estimates, and multiple secondary sensors capable of recognizing the targets' identities. Each of the secondary sensors is assigned to a sector of the operation area; a secondary sensor decides which target in its assigned sector to be identified and controls itself to identify the target. We formulate the decision-making process as an optimization problem to minimize the uncertainty of the targets' identities subject to the sensor dynamic constraints. The proposed algorithm is decentralized since the secondary sensors only communicate with the primary sensor for the target information, and need not to synchronize with each other. By integrating the proposed algorithm with the existing multi-target tracking algorithms, we develop a closed-loop multi-target tracking and identity management algorithm. The effectiveness of the proposed algorithm is demonstrated with illustrative numerical examples.
Vo, Tri Hoang, Fuhrmann, Woldemar, Fischer-Hellmann, Klaus-Peter, Furnell, Steven.  2019.  Efficient Privacy-Preserving User Identity with Purpose-Based Encryption. 2019 International Symposium on Networks, Computers and Communications (ISNCC). :1–8.
In recent years, users may store their Personal Identifiable Information (PII) in the Cloud environment so that Cloud services may access and use it on demand. When users do not store personal data in their local machines, but in the Cloud, they may be interested in questions such as where their data are, who access it except themselves. Even if Cloud services specify privacy policies, we cannot guarantee that they will follow their policies and will not transfer user data to another party. In the past 10 years, many efforts have been taken in protecting PII. They target certain issues but still have limitations. For instance, users require interacting with the services over the frontend, they do not protect identity propagation between intermediaries and against an untrusted host, or they require Cloud services to accept a new protocol. In this paper, we propose a broader approach that covers all the above issues. We prove that our solution is efficient: the implementation can be easily adapted to existing Identity Management systems and the performance is fast. Most importantly, our approach is compliant with the General Data Protection Regulation from the European Union.
Soltani, Reza, Nguyen, Uyen Trang, An, Aijun.  2019.  Practical Key Recovery Model for Self-Sovereign Identity Based Digital Wallets. 2019 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech). :320–325.
Recent years have seen an increased interest in digital wallets for a multitude of use cases including online banking, cryptocurrency, and digital identity management. Digital wallets play a pivotal role in the secure management of cryptographic keys and credentials, and for providing certain identity management services. In this paper, we examine a proof-of-concept digital wallet in the context of Self-Sovereign Identity and provide a practical decentralized key recovery solution using Shamir's secret sharing scheme and Hyperledger Indy distributed ledger technology.
Shehu, Abubakar-Sadiq, Pinto, António, Correia, Manuel E..  2019.  Privacy Preservation and Mandate Representation in Identity Management Systems. 2019 14th Iberian Conference on Information Systems and Technologies (CISTI). :1–6.
The growth in Internet usage has increased the use of electronic services requiring users to register their identity on each service they subscribe to. This has resulted in the prevalence of redundant users data on different services. To protect and regulate access by users to these services identity management systems (IdMs)are put in place. IdMs uses frameworks and standards e.g SAML, OAuth and Shibboleth to manage digital identities of users for identification and authentication process for a service provider. However, current IdMs have not been able to address privacy issues (unauthorised and fine-grained access)that relate to protecting users identity and private data on web services. Many implementations of these frameworks are only concerned with the identification and authentication process of users but not authorisation. They mostly give full control of users digital identities and data to identity and service providers with less or no users participation. This results in a less privacy enhanced solutions that manage users available data in the electronic space. This article proposes a user-centred mandate representation system that empowers resource owners to take full of their digital data; determine and delegate access rights using their mobile phone. Thereby giving users autonomous powers on their resources to grant access to authenticated entities at their will. Our solution is based on the OpenID Connect framework for authorisation service. To evaluate the proposal, we've compared it with some related works and the privacy requirements yardstick outlined in GDPR regulation [1] and [2]. Compared to other systems that use OAuth 2.0 or SAML our solution uses an additional layer of security, where data owner assumes full control over the disclosure of their identity data through an assertion issued from their mobile phones to authorisation server (AS), which in turn issues an access token. This would enable data owners to assert the authenticity of a request, while service providers and requestors also benefit from the correctness and freshness of identity data disclosed to them.
Selvanathan, Nirojan, Jayakody, Dileepa, Damjanovic-Behrendt, Violeta.  2019.  Federated Identity Management and Interoperability for Heterogeneous Cloud Platform Ecosystems. Proceedings of the 14th International Conference on Availability, Reliability and Security. :1–7.
This paper describes an approach to overcome the interoperability challenges related to identity management systems supporting cross-collaboration between heterogeneous manufacturing platforms. Traditional identity management systems have shown many weaknesses when it comes to cloud platforms and their federations, from not being able to support a simplified login process, to information disclosure and complexity of implementation in practice. This paper discusses workflows to practically implement federated identity management across the heterogeneous manufacturing platforms and design interoperability at different levels, e.g. at the platform level and at the platform integration level. Our motivation to find the best federated identity management solution for heterogeneous cloud-based platforms is related to practical requirements coming from the ongoing European project eFactory.
Rana, Rima, Zaeem, Razieh Nokhbeh, Barber, K. Suzanne.  2019.  An Assessment of Blockchain Identity Solutions: Minimizing Risk and Liability of Authentication. 2019 IEEE/WIC/ACM International Conference on Web Intelligence (WI). :26–33.
Personally Identifiable Information (PII) is often used to perform authentication and acts as a gateway to personal and organizational information. One weak link in the architecture of identity management services is sufficient to cause exposure and risk identity. Recently, we have witnessed a shift in identity management solutions with the growth of blockchain. Blockchain-the decentralized ledger system-provides a unique answer addressing security and privacy with its embedded immutability. In a blockchain-based identity solution, the user is given the control of his/her identity by storing personal information on his/her device and having the choice of identity verification document used later to create blockchain attestations. Yet, the blockchain technology alone is not enough to produce a better identity solution. The user cannot make informed decisions as to which identity verification document to choose if he/she is not presented with tangible guidelines. In the absence of scientifically created practical guidelines, these solutions and the choices they offer may become overwhelming and even defeat the purpose of providing a more secure identity solution.We analyze different PII options given to users for authentication on current blockchain-based solutions. Based on our Identity Ecosystem model, we evaluate these options and their risk and liability of exposure. Powered by real world data of about 6,000 identity theft and fraud stories, our model recommends some authentication choices and discourages others. Our work paves the way for a truly effective identity solution based on blockchain by helping users make informed decisions and motivating blockchain identity solution providers to introduce better options to their users.
Petrovska, Jovana, Memeti, Agon, Imeri, Florinda.  2019.  SOA Approach - Identity and Access Management for the Risk Management Platform. 2019 8th Mediterranean Conference on Embedded Computing (MECO). :1–4.
The Risk Management system should help customs to more easily and effectively detect irregularities in import, export or transit of goods. Customs administrations today are required to provide extensive facilitation while maintaining control over the international movement of goods, means of transport and persons. The level of risk is determined in the context of the priorities of the Customs administrations e.g. whether the priority is collection of duties and taxes or checking prohibitions and restrictions or any other specific area that has been identified. The aim of the proposed platform in this paper is to achieve a high-quality, multi-layered approach to risk management that is effective and efficient, i.e. the platform is built on decoupled microservices, the different components are working together and an interruption in one segment does not have major effect on the overall system. The main motivation behind this case study is the hands-on experience we have and the close proximity to the project, i.e. information exchange and team discussions as the main available resources.
Pal, Shantanu.  2019.  Limitations and Approaches in Access Control and Identity Management for Constrained IoT Resources. 2019 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops). :431–432.
The Internet of Things (IoT), smart sensors and mobile wearable devices are helping to provide services that are more ubiquitous, smarter, faster and easily accessible to users. However, security is a significant concern for the IoT, with access control and identity management are being two major issues. With the growing size and presence of these systems and the resource constrained nature of the IoT devices, an important question is how to manage policies in a manner that is both scalable and flexible. In this research, we aim at proposing a fine-grained and flexible access control architecture, and to examine an identity model for constrained IoT resources. To achieve this, first, we outline some key limitations in the state of the art access control and identity management for IoT. Then we devise our approach to address those limitations in a systematic way.
Luo, Yurong, Cao, Jin, Ma, Maode, Li, Hui, Niu, Ben, Li, Fenghua.  2019.  DIAM: Diversified Identity Authentication Mechanism for 5G Multi-Service System. 2019 International Conference on Computing, Networking and Communications (ICNC). :418–424.
The future fifth-generation (5G) mobile communications system has already become a focus around the world. A large number of late-model services and applications including high definition visual communication, internet of vehicles, multimedia interaction, mobile industry automation, and etc, will be added to 5G network platform in the future. Different application services have different security requirements. However, the current user authentication for services and applications: Extensible Authentication Protocol (EAP) suggested by the 3GPP committee, is only a unitary authentication model, which is unable to meet the diversified security requirements of differentiated services. In this paper, we present a new diversified identity management as well as a flexible and composable three-factor authentication mechanism for different applications in 5G multi-service systems. The proposed scheme can provide four identity authentication methods for different security levels by easily splitting or assembling the proposed three-factor authentication mechanism. Without a design of several different authentication protocols, our proposed scheme can improve the efficiency, service of quality and reduce the complexity of the entire 5G multi-service system. Performance analysis results show that our proposed scheme can ensure the security with ideal efficiency.
Haddouti, Samia El, Ech-Cherif El Kettani, M. Dafir.  2019.  Analysis of Identity Management Systems Using Blockchain Technology. 2019 International Conference on Advanced Communication Technologies and Networking (CommNet). :1–7.
The emergence of Blockchain technology as the biggest innovations of the 21stcentury, has given rise to new concepts of Identity Management to deal with the privacy and security challenges on the one hand, and to enhance the decentralization and user control in transactions on Blockchain infrastructures on the other hand. This paper investigates and gives analysis of the most popular Identity Management Systems using Blockchain: uPort, Sovrin, and ShoCard. It then evaluates them under a set of features of digital identity that characterizes the successful of an Identity Management solution. The result of the comparative analysis is presented in a concise way to allow readers to find out easily which systems satisfy what requirements in order to select the appropriate one to fit into a specific scenario.
Gunasinghe, Hasini, Kundu, Ashish, Bertino, Elisa, Krawczyk, Hugo, Chari, Suresh, Singh, Kapil, Su, Dong.  2019.  PrivIdEx: Privacy Preserving and Secure Exchange of Digital Identity Assets.. The World Wide Web Conference. :594–604.
User's digital identity information has privacy and security requirements. Privacy requirements include confidentiality of the identity information itself, anonymity of those who verify and consume a user's identity information and unlinkability of online transactions which involve a user's identity. Security requirements include correctness, ownership assurance and prevention of counterfeits of a user's identity information. Such privacy and security requirements, although conflicting, are critical for identity management systems enabling the exchange of users' identity information between different parties during the execution of online transactions. Addressing all such requirements, without a centralized party managing the identity exchange transactions, raises several challenges. This paper presents a decentralized protocol for privacy preserving exchange of users' identity information addressing such challenges. The proposed protocol leverages advances in blockchain and zero knowledge proof technologies, as the main building blocks. We provide prototype implementations of the main building blocks of the protocol and assess its performance and security.
Zhou, Lin, Feng, Jing, He, Haiguang, Mao, Zhijie, Chen, Yingmei, Gao, Mei, He, Zhuzhen.  2019.  A Construction Method of Security Mechanism Requirement for Wireless Access System Based on CC Standard. 2019 International Conference on Intelligent Transportation, Big Data Smart City (ICITBS). :369–372.
Aiming at the incomplete and incomplete security mechanism of wireless access system in emergency communication network, this paper proposes a security mechanism requirement construction method for wireless access system based on security evaluation standard. This paper discusses the requirements of security mechanism construction in wireless access system from three aspects: the definition of security issues, the construction of security functional components and security assurance components. This method can comprehensively analyze the security threats and security requirements of wireless access system in emergency communication network, and can provide correct and reasonable guidance and reference for the establishment of security mechanism.
Jimenez, Jaime Ibarra, Jahankhani, Hamid.  2019.  ``Privacy by Design'' Governance Framework to Achieve Privacy Assurance of Personal Health Information (PHI) Processed by IoT-Based Telemedicine Devices and Applications Within Healthcare Services. 2019 IEEE 12th International Conference on Global Security, Safety and Sustainability (ICGS3). :212–212.
Future that IoT has to enhance the productivity on healthcare applications.
Hughes, Cameron, Hughes, Tracey.  2019.  What Metrics Should We Use to Measure Commercial AI? AI Matters. 5:41–45.
In AI Matters Volume 4, Issue 2, and Issue 4, we raised the notion of the possibility of an AI Cosmology in part in response to the "AI Hype Cycle" that we are currently experiencing. We posited that our current machine learning and big data era represents but one peak among several previous peaks in AI research in which each peak had accompanying "Hype Cycles". We associated each peak with an epoch in a possible AI Cosmology. We briefly explored the logic machines, cybernetics, and expert system epochs. One of the objectives of identifying these epochs was to help establish that we have been here before. In particular we've been in the territory where some application of AI research finds substantial commercial success which is then closely followed by AI fever and hype. The public's expectations are heightened only to end in disillusionment when the applications fall short. Whereas it is sometimes somewhat of a challenge even for AI researchers, educators, and practitioners to know where the reality ends and hype begins, the layperson is often in an impossible position and at the mercy of pop culture, marketing and advertising campaigns. We suggested that an AI Cosmology might help us identify a single standard model for AI that could be the foundation for a common shared understanding of what AI is and what it is not. A tool to help the layperson understand where AI has been, where it's going, and where it can't go. Something that could provide a basic road map to help the general public navigate the pitfalls of AI Hype.
Headrick, William J, Subramanian, Gokul.  2019.  Using Layer 2 or 3 Switches to Augment Information Assurance in Modern ATE. 2019 IEEE AUTOTESTCON. :1–4.
For modern Automatic Test Equipment (ATE) one of the most daunting tasks is now Information Assurance (IA). What was once at most a secondary item consisting mainly of installing an Anti-Virus suite is now becoming one of the most important aspects of ATE. Given the current climate of IA it has become important to ensure ATE is kept safe from any breaches of security or loss of information. Even though most ATE are not on the Internet (or even on a local network for many) they are still vulnerable to some of the same attack vectors plaguing common computers and other electronic devices. This paper will discuss one method which can be used to ensure that modern ATE can continue to be used to test and detect faults in the systems they are designed to test. Most modern ATE include one or more Ethernet switches to allow communication to the many Instruments or devices contained within them. If the switches purchased are managed and support layer 2 or layer 3 of the Open Systems Interconnection (OSI) model they can also be used to help in the IA footprint of the station. Simple configurations such as limiting broadcast or multicast packets to the appropriate devices is the first step of limiting access to devices to what is needed. If the switch also includes some layer 3 like capabilities Virtual Local Area Networks can be created to further limit the communication pathways to only what is required to perform the required tasks. These and other simple switch configurations while not required can help limit the access of a virus or worm. This paper will discuss these and other configuration tools which can help prevent an ATE system from being compromised.
Greitzer, Frank L..  2019.  Insider Threats: It's the HUMAN, Stupid!. Proceedings of the Northwest Cybersecurity Symposium. :1–8.
Insider threats refer to threats posed by individuals who intentionally or unintentionally destroy, exfiltrate, or leak sensitive information, or expose their organization to outside attacks. Surveys of organizations in government and industry consistently show that threats posed by insiders rival those posed by hackers, and that insider attacks are even more costly. Emerging U.S. government guidelines and policies for establishing insider threat programs tend to specify only minimum standards for insider threat monitoring, analysis, and mitigation programs. Arguably, one of the most serious challenges is to identify and integrate behavioral (sociotechnical) indicators of insider threat r isk in addition to cyber/technical indicators. That is, in focusing on data that are most readily obtained, insider threat programs most often miss the human side of the problem. This talk briefly describes research aiming to catalog human as well as technical factors associated with insider threat risk and summarizes several recent studies that seek to inform the development of more comprehensive, proactive approaches to insider threat assessment.
Ebert, David S..  2019.  Visual Spatial Analytics and Trusted Information for Effective Decision Making. Proceedings of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems. :2.
Information, not just data, is key to today's global challenges. To solve these challenges requires not only advancing geospatial and big data analytics but requires new analysis and decision-making environments that enable reliable decisions from trustable, understandable information that go beyond current approaches to machine learning and artificial intelligence. These environments are successful when they effectively couple human decision making with advanced, guided spatial analytics in human-computer collaborative discourse and decision making (HCCD). Our HCCD approach builds upon visual analytics, natural scale templates, traceable information, human-guided analytics, and explainable and interactive machine learning, focusing on empowering the decisionmaker through interactive visual spatial analytic environments where non-digital human expertise and experience can be combined with state-of-the-art and transparent analytical techniques. When we combine this approach with real-world application-driven research, not only does the pace of scientific innovation accelerate, but impactful change occurs. I'll describe how we have applied these techniques to challenges in sustainability, security, resiliency, public safety, and disaster management.
Dabbaghi Varnosfaderani, Shirin, Kasprzak, Piotr, Pohl, Christof, Yahyapour, Ramin.  2019.  A Flexible and Compatible Model for Supporting Assurance Level through a Central Proxy. 2019 6th IEEE International Conference on Cyber Security and Cloud Computing (CSCloud)/ 2019 5th IEEE International Conference on Edge Computing and Scalable Cloud (EdgeCom). :46–52.
Generally, methods of authentication and identification utilized in asserting users' credentials directly affect security of offered services. In a federated environment, service owners must trust external credentials and make access control decisions based on Assurance Information received from remote Identity Providers (IdPs). Communities (e.g. NIST, IETF and etc.) have tried to provide a coherent and justifiable architecture in order to evaluate Assurance Information and define Assurance Levels (AL). Expensive deployment, limited service owners' authority to define their own requirements and lack of compatibility between heterogeneous existing standards can be considered as some of the unsolved concerns that hinder developers to openly accept published works. By assessing the advantages and disadvantages of well-known models, a comprehensive, flexible and compatible solution is proposed to value and deploy assurance levels through a central entity called Proxy.
Boitan, Alexandru, B\u atu\c sic\u a, R\u azvan, Halunga, Simona, Fratu, Octavian.  2019.  Electromagnetic Vulnerabilities of LCD Projectors. Proceedings of the 6th Conference on the Engineering of Computer Based Systems. :1–6.
This paper presents for the first time a study on the security of information processed by video projectors. Examples of video recovery from the electromagnetic radiation of these equipment will be illustrated both in laboratory and real-field environment. It presents the results of the time parameters evaluation for the analyzed video signal that confirm the video standards specifications. There will also be illustrated the results of a vulnerability analysis based on the colors used to display the images but also the remote video recovery capabilities.
Bao, Xuhua, Zhang, Xiaokun, Lin, Jingqiang, Chu, Dawei, Wang, Qiongxiao, Li, Fengjun.  2019.  Towards the Trust-Enhancements of Single Sign-On Services. 2019 IEEE Conference on Dependable and Secure Computing (DSC). :1–8.
Single sign-on (SSO) becomes popular as the identity management and authentication infrastructure in the Internet. A user receives an SSO ticket after being authenticated by the identity provider (IdP), and this IdP-issued ticket enables him to sign onto the relying party (RP). However, there are vulnerabilities (e.g., Golden SAML) that allow attackers to arbitrarily issue SSO tickets and then sign onto any RP on behalf of any user. Meanwhile, several incidents of certification authorities (CAs) also indicate that the trusted third party of security services is not so trustworthy as expected, and fraudulent TLS server certificates are signed by compromised or deceived CAs to launch TLS man-in-the-middle attacks. Various approaches are then proposed to tame the absolute authority of (compromised) CAs, to detect or prevent fraudulent TLS server certificates in the TLS handshakes. The trust model of SSO services is similar to that of certificate services. So this paper investigates the defense strategies of these trust-enhancements of certificate services, and attempts to apply these strategies to SSO to derive the trust-enhancements applicable in the SSO services. Our analysis derives (a) some security designs which have been commonly-used in the SSO services or non-SSO authentication services, and (b) two schemes effectively improving the trustworthiness of SSO services, which are not widely discussed or adopted.
Appana, Pranavi, Sun, Xiaoyan, Cheng, Yuan.  2019.  What To Do First: Ranking The Mission Impact Graph for Effective Mission Assurance. 2019 International Conference on Computing, Networking and Communications (ICNC). :567–571.
Network attacks continue to pose threats to missions in cyber space. To prevent critical missions from getting impacted or minimize the possibility of mission impact, active cyber defense is very important. Mission impact graph is a graphical model that enables mission impact assessment and shows how missions can be possibly impacted by cyber attacks. Although the mission impact graph provides valuable information, it is still very difficult for human analysts to comprehend due to its size and complexity. Especially when given limited resources, human analysts cannot easily decide which security measures to take first with respect to mission assurance. Therefore, this paper proposes to apply a ranking algorithm towards the mission impact graph so that the huge amount of information can be prioritized. The actionable conditions that can be managed by security admins are ranked with numeric values. The rank enables efficient utilization of limited resources and provides guidance for taking security countermeasures.
Zhang, Jiange, Chen, Yue, Yang, Kuiwu, Zhao, Jian, Yan, Xincheng.  2019.  Insider Threat Detection Based on Adaptive Optimization DBN by Grid Search. 2019 IEEE International Conference on Intelligence and Security Informatics (ISI). :173–175.
Aiming at the problem that one-dimensional parameter optimization in insider threat detection using deep learning will lead to unsatisfactory overall performance of the model, an insider threat detection method based on adaptive optimization DBN by grid search is designed. This method adaptively optimizes the learning rate and the network structure which form the two-dimensional grid, and adaptively selects a set of optimization parameters for threat detection, which optimizes the overall performance of the deep learning model. The experimental results show that the method has good adaptability. The learning rate of the deep belief net is optimized to 0.6, the network structure is optimized to 6 layers, and the threat detection rate is increased to 98.794%. The training efficiency and the threat detection rate of the deep belief net are improved.
Singh, Malvika, Mehtre, B.M., Sangeetha, S..  2019.  User Behavior Profiling Using Ensemble Approach for Insider Threat Detection. 2019 IEEE 5th International Conference on Identity, Security, and Behavior Analysis (ISBA). :1–8.
The greatest threat towards securing the organization and its assets are no longer the attackers attacking beyond the network walls of the organization but the insiders present within the organization with malicious intent. Existing approaches helps to monitor, detect and prevent any malicious activities within an organization's network while ignoring the human behavior impact on security. In this paper we have focused on user behavior profiling approach to monitor and analyze user behavior action sequence to detect insider threats. We present an ensemble hybrid machine learning approach using Multi State Long Short Term Memory (MSLSTM) and Convolution Neural Networks (CNN) based time series anomaly detection to detect the additive outliers in the behavior patterns based on their spatial-temporal behavior features. We find that using Multistate LSTM is better than basic single state LSTM. The proposed method with Multistate LSTM can successfully detect the insider threats providing the AUC of 0.9042 on train data and AUC of 0.9047 on test data when trained with publically available dataset for insider threats.
Novikova, Evgenia, Bekeneva, Yana, Shorov, Andrey.  2019.  The Location-Centric Approach to Employee's Interaction Pattern Detection. 2019 27th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP). :373–378.
The task of the insider threat detection is one of the most sophisticated problems of the information security. The analysis of the logs of the access control system may reveal on how employees move and interact providing thus better understanding on how personnel observe security policies and established business processes. The paper presents an approach to the detection of the location-centric employees' interaction patterns. The authors propose the formal definition of the interaction patterns and present the visualization-driven technique to the extraction of the patterns from the data when any prior information about existing interaction routine and procedures is not available. The proposed approach is demonstrated on the data set provided within VAST MiniChallenge-2 2016 contest.
Le, Duc C., Nur Zincir-Heywood, A..  2019.  Machine Learning Based Insider Threat Modelling and Detection. 2019 IFIP/IEEE Symposium on Integrated Network and Service Management (IM). :1–6.
Recently, malicious insider attacks represent one of the most damaging threats to companies and government agencies. This paper proposes a new framework in constructing a user-centered machine learning based insider threat detection system on multiple data granularity levels. System evaluations and analysis are performed not only on individual data instances but also on normal and malicious insiders, where insider scenario specific results and delay in detection are reported and discussed. Our results show that the machine learning based detection system can learn from limited ground truth and detect new malicious insiders with a high accuracy.