Development of a Methodology for Customizing Insider Threat Auditing on a Microsoft Windows XP® Operating System

Most organizations are aware that threats from trusted insiders pose a great risk to their organization and are very difficult to protect against. Auditing is recognized as an effective technique to detect malicious insider activities. However, current auditing methods are typically applied with a one-size-fits-all approach and may not be an appropriate mitigation strategy, especially towards insider threats. This research develops a 4-step methodology for designing a customized auditing template for a Microsoft Windows XP operating system. Two tailoring methods are presented which evaluate both by category and by configuration. Also developed are various metrics and weighting factors as a mechanism to evaluate auditing effectiveness for the purpose of optimizing the template according to organizational security requirements. Various industry standard auditing templates are evaluated against a custom designed template. Results indicate that a customized auditing template tailored for an insider threat scenario is more effective at detecting insider malicious activities

Training a machine-learning based object detector for use in photography

Cameras and other photography systems include the capability to detect objects of interest. Object detectors trained using sample data have a classification loss, e.g., due to insufficient training owing to a finite number of negative samples used during training. An increase in complexity of the object detector increases running time which necessitates a tradeoff between recall, precision, and speed. A common approach is to minimize the average loss across the entire training database. This disclosure proposes a new framework that takes the final image quality into account while training an object detector, by using a modified loss calculation function for the object detection framework used in photography. The framework enables better decisions regarding the various tradeoffs involved in loss calculation. The loss of classification during training is calculated by comparison of an image captured with and without successful detection of the object. The object detector, trained to take into account the impact of detecting or missing an object on a captured image, can improve the quality of captured images

View images with unprecedented resolution in integral microscopy

Integral microscopy is a novel technique that allows the simultaneous capture of multiple perspective images of microscopic samples. This feature is achieved at the cost of a significant reduction of the spatial resolution. In fact, it is assumed that in the best cases the resolution is reduced by a factor that is not smaller than ten, what poses a hard drawback to the utility of the technique. However, to the best of our knowledge, this resolution limitation has never been researched rigorously. For this reason, the aim of this paper is to explore the real limitations in resolution of integral microscopy and to obtain optically, without the need of any image-processing algorithm, perspective images with the best resolution ever achieved in integral microscopy. This result opens a wide range of new possibilities of using integral microscopy in any imaging application were micron resolution is required

Embedded FIR filter design for real-time refocusing using a standard plenoptic video camera

Copyright 2014 Society of Photo-Optical Instrumentation Engineers and IS&T—The Society for Imaging Science and Technology. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.A novel and low-cost embedded hardware architecture for real-time refocusing based on a standard plenoptic camera is presented in this study. The proposed layout design synthesizes refocusing slices directly from micro images by omitting the process for the commonly used sub-aperture extraction. Therefore, intellectual property cores, containing switch controlled Finite Impulse Response (FIR) filters, are developed and applied to the Field Programmable Gate Array (FPGA) XC6SLX45 from Xilinx. Enabling the hardware design to work economically, the FIR filters are composed of stored product as well as upsampling and interpolation techniques in order to achieve an ideal relation between image resolution, delay time, power consumption and the demand of logic gates. The video output is transmitted via High-Definition Multimedia Interface (HDMI) with a resolution of 720p at a frame rate of 60 fps conforming to the HD ready standard. Examples of the synthesized refocusing slices are presented