PPT-Tamper Detection

and nonmalleable codes Daniel Wichs Northeastern U Protecting Data Against Tampering Question How can we protect data against tampering by an adversary Variants of this question studied in . 02nT Faster cycle rates Up to 10Hz Longer range detection Pros brPage 5br Magnetometers Magnetometers Large distant targets mask small local targets Difficult to pick out small target due to background noise No sense of direction of target on single Mahmoud. . Abdallah. Daniel . Eiland. The detection of traffic signals within a moving video is problematic due to issues caused by:. Low-light, Day and Night situations. Inter/Intra-frame motion. Similar light sources (such as tail lights). • Increase - . Public Safety. • Reduce - . Liability. Specialty Media, LLC. Prepared By: Bob Lisenko. For Specialty Media, LLC. Summary. Tamper-resistant water filters, intended for . public. locations, will reduce the risk for potential contamination of drinking water and improve . Ross . Girshick. , Jeff Donahue, Trevor Darrell, . Jitandra. Malik (UC Berkeley). Presenter: . Hossein. . Azizpour. Abstract. Can CNN improve . s.o.a. . object detection results?. Yes, it helps by learning rich representations which can then be combined with computer vision techniques.. What is perfection?. If someone/something/somewhere is perfect, what does that mean? . Can you give specific examples? . Is perfection a good thing?. Unit Questions. How do humans cope with an imperfect world? . Physical tamper Resistance. Physical Tamper Resistance. Eustace Asanghanwa. 1. Overview of talk. Ross Anderson on Physical Tamper Resistance. Chapter report. Critique. Commentary on Tamper Resistance since 2000. Abstract. Link error and malicious packet dropping are two sources for packet losses in multi-hop wireless ad hoc network. In this paper, while observing a sequence of packet losses in the network, we are interested in determining whether the losses are caused by link errors only, or by the combined effect of link errors and malicious drop. . and . non-malleable codes. Daniel Wichs (Northeastern U). Protecting Data Against “Tampering”. Question: . How can we protect data against tampering by an adversary?. Variants of this question studied in . All-in-one security solution. Two-Way wireless support . Two-Way Audio verification over GSM. Premium lighting. Quick enrollment for wireless devices. Wireless carbon monoxide support. SCW9057 Key Features/Benefits. MURAMURA-M-45-L-40-20-9-40K-H5-M4-MV-1C-EM-DM SERIESSECURITY LEVELDIMENSIONSSOURCELUMENS UPLUMENS DOWNCRIKELVINSDIFFUSERSLENSVOLTAGECIRCUITSOPTIONSDRIVERx0000Specification-grade direct/indirect wall m State-of-the-art face detection demo. (Courtesy . Boris . Babenko. ). Face detection and recognition. Detection. Recognition. “Sally”. Face detection. Where are the faces? . Face Detection. What kind of features?. Limit of Detection (LOD). The detection limit is the concentration that is obtained when the measured signal differs significantly from the background.. Calculated by this equation for the ARCOS.. C. Xindian. Long. 2018.09. Outline. Introduction. Object Detection Concept and the YOLO Algorithm. Object Detection Example (CAS Action). Facial Keypoint Detection Example (. DLPy. ). Why SAS Deep Learning . for . a TEE. Francisco . Corella. fcorella@pomcor.com. Karen . Lewison. kplewison@pomcor.com. 9/30/14. 1. Presentation to the . GlobalPlatform. 2014 TEE Conference. Smart cards and mobile devices. as credential carriers.