PPT-How & When The Kernel Runs

David Ferry Chris Gill Department of Computer Science and Engineering Washington University St Louis MO davidferrywustledu 1 Traditional View of Process Execution However the kernel is not a traditional process. 1 Hilbert Space and Kernel An inner product uv can be 1 a usual dot product uv 2 a kernel product uv vw where may have in64257nite dimensions However an inner product must satisfy the following conditions 1 Symmetry uv vu uv 8712 X 2 Bilinearity 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. . Dr. M. . Asaduzzaman. . Professor. Department  of  Mathematics . University . of . Rajshahi. Rajshahi. -6205, Bangladesh. E-mail: md_asaduzzaman@hotmail.com. Definition. Let . H. be a Hilbert space comprising of complex valued . 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.. Debugging as Engineering. Much of your time in this course will be spent debugging. In industry, 50% of software dev is debugging. Even more for kernel development. How do you reduce time spent debugging?. Attributed . Graphs . Yu Su. University of California at Santa Barbara. with . Fangqiu. Han, Richard E. . Harang. , and . Xifeng. Yan . Introduction. A Fast Kernel for Attributed Graphs. Graph Kernel. 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. 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!. Practice Runs Training Outline. Defining practice runs. Purpose of a practice run. Allowed practice runs. IRB determinations. What is a practice run?. Practice Run (aka Dry Run or Walk Through):. Investigators and study staff who practice a study or conduct a ‘dry run’ to ensure feasibility . 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 .