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Insiders Dissected: New Foundations and a Systematisation of the Research on Insiders
The insider threat is often cited as one of the most challenging threats for security practitioners. Even though this topic is receiving considerable attention, two main problems remain unsolved. First, research on insider threats is focusing on many ...
Results From Invoking Artificial Neural Networks to Measure Insider Threat Detection & Mitigation
Advances on differentiating between malicious intent and natural “organizational evolution” to explain observed anomalies in operational workplace patterns suggest benefit from evaluating collective behaviors observed in the facilities to improve insider ...
Simulating Organizational Data from Redacted Input for Inference Enterprise Modeling
Organizations that use data to assess insider threats, or other workforce outcomes, need to evaluate the quality of their assessment methods. This evaluation relies on an accurate representation of the predictors and criterion variables within the ...
Using Dirichlet Marked Hawkes Processes for Insider Threat Detection
Malicious insiders cause significant loss to organizations. Due to an extremely small number of malicious activities from insiders, insider threat is hard to detect. In this article, we present a Dirichlet Marked Hawkes Process (DMHP) to detect malicious ...
Investigating Sharing of Cyber Threat Intelligence and Proposing A New Data Model for Enabling Automation in Knowledge Representation and Exchange
- Siri Bromander,
- Morton Swimmer,
- Lilly Pijnenburg Muller,
- Audun Jøsang,
- Martin Eian,
- Geir Skjøtskift,
- Fredrik Borg
For a strong, collective defense in the digital domain, we need to produce, consume, analyze, and share cyber threat intelligence. With an increasing amount of available information, we need automation to ensure adequate efficiency. We present the results ...
Privacy-aware Character Pattern Matching over Outsourced Encrypted Data
Providing a method to efficiently search into outsourced encrypted data, without forsaking strong privacy guarantees, is a pressing concern rising from the separation of data ownership and data management typical of cloud-based applications. While several ...