PPT-Instrument Kernel

IK November 2014 Instrument Kernel 2 The Instrument Kernel serves as a repository for instrument specific information that may be useful within the SPICE context Always included Specifications for an instruments fieldofview FOV size shape and orientation. Osck. Owen Hofmann, Alan Dunn, . Sangman. Kim, . Indrajit Roy*, Emmett Witchel. UT Austin. *HP Labs. Rootkits are dangerous. Adversary exploits insecure system. Leave backdoor . to facilitate long-term access. with Multiple Labels. Lei Tang. , . Jianhui. Chen and . Jieping. Ye. Kernel-based Methods. Kernel-based methods . Support Vector Machine (SVM). Kernel Linear Discriminate Analysis (KLDA). Demonstrate success in various domains. Mode, space, and context: the basics. Jeff Chase. Duke University. 64 bytes: 3 ways. p + 0x0. 0x1f. 0x0. 0x1f. 0x1f. 0x0. char p[]. char *p. int p[]. int* p. p. char* p[]. char** p. Pointers (addresses) are 8 bytes on a 64-bit machine.. 0.2 0.4 0.6 0.8 1.0 0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 kernel(b) kernel(c) kernel(d) (a)blurredimage(b)no-blurredimage0.900.981.001.021.10 (5.35,3.37)(4.80,3.19)(4.71,3.22)(4.93,3.23)(5.03,3.22 KAIST . CySec. Lab. 1. Contents. About Rootkit. Concept and Methods. Examples. Ubuntu Linux (Network Hiding. ). Windows 7 (File Hiding). Android Rootkit Demonstration (DNS Spoofing). Exercise (Rootkit Detection). Rootkits. with lightweight Hook Protection. Authors: . Zhi. Wang, . Xuxian. Jiang, . Weidong. Cui, . Peng. . Ning. Presented by: . Purva. . Gawde. Outline. Introduction. Prior research. Problem overview. A B M Shawkat Ali. 1. 2. Data Mining. ¤. . DM or KDD (Knowledge Discovery in Databases). Extracting previously unknown, valid, and actionable information . . . crucial decisions. ¤. . Approach. Presented by:. Nacer Khalil. Table of content. Introduction. Definition of robustness. Robust Kernel Density Estimation. Nonparametric . Contamination . Models. Scaled project Kernel Density Estimator. Syscall. Hijacking. Jeremy Fields. Intro. Ubuntu 14.04 in Hyper-V. Linux-lts-vivid-3.19.0-69. Compile vanilla kernel & load. Create basic module for learning. Kernel Module. Kernel Module . Let’s do some statistics on speed in kernel space vs user space. method . introduction. hyperplane. Margin. W. . =. . 0.  .  . . =. . -1.  . separating hyperplane. support hyperplane. support hyperplane. hyperplane. /||w||=1/||w||.  . /||w||=1/||w||.  . Margin. John Erickson, . Madanlal. . Musuvathi. , Sebastian Burckhardt, Kirk . Olynyk. Microsoft . Research. Motivations. Need for race detection in Kernel modules. Also must detect race conditions between hardware and Kernel. David Ferry, Chris Gill. Department of Computer Science and Engineering. Washington University, St. Louis MO. davidferry@wustl.edu. 1. Traditional View of Process Execution. However, the kernel is not a traditional process!. CSE . 422S . - . Operating . Systems Organization. Washington University in St. Louis. St. Louis, MO 63143. 1. Things Happen: Kernel Oops vs Panic. A kernel . panic. is unrecoverable and results in an instant halt. Object Recognition. Murad Megjhani. MATH : 6397. 1. Agenda. Sparse Coding. Dictionary Learning. Problem Formulation (Kernel). Results and Discussions. 2. Motivation. Given a 16x16(or . nxn. ) image .