A Systematic Survey of Firmware Extraction Techniques for Iot Devices
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Bootstomp: on the Security of Bootloaders in Mobile Devices
BootStomp: On the Security of Bootloaders in Mobile Devices Nilo Redini, Aravind Machiry, Dipanjan Das, Yanick Fratantonio, Antonio Bianchi, Eric Gustafson, Yan Shoshitaishvili, Christopher Kruegel, and Giovanni Vigna, UC Santa Barbara https://www.usenix.org/conference/usenixsecurity17/technical-sessions/presentation/redini This paper is included in the Proceedings of the 26th USENIX Security Symposium August 16–18, 2017 • Vancouver, BC, Canada ISBN 978-1-931971-40-9 Open access to the Proceedings of the 26th USENIX Security Symposium is sponsored by USENIX BootStomp: On the Security of Bootloaders in Mobile Devices Nilo Redini, Aravind Machiry, Dipanjan Das, Yanick Fratantonio, Antonio Bianchi, Eric Gustafson, Yan Shoshitaishvili, Christopher Kruegel, and Giovanni Vigna fnredini, machiry, dipanjan, yanick, antoniob, edg, yans, chris, [email protected] University of California, Santa Barbara Abstract by proposing simple mitigation steps that can be im- plemented by manufacturers to safeguard the bootloader Modern mobile bootloaders play an important role in and OS from all of the discovered attacks, using already- both the function and the security of the device. They deployed hardware features. help ensure the Chain of Trust (CoT), where each stage of the boot process verifies the integrity and origin of 1 Introduction the following stage before executing it. This process, in theory, should be immune even to attackers gaining With the critical importance of the integrity of today’s full control over the operating system, and should pre- mobile and embedded devices, vendors have imple- vent persistent compromise of a device’s CoT. However, mented a string of inter-dependent mechanisms aimed at not only do these bootloaders necessarily need to take removing the possibility of persistent compromise from untrusted input from an attacker in control of the OS in the device. -
Mediatek Linkit™ Development Platform for RTOS Get Started Guide
MediaTek LinkIt™ Development Platform for RTOS Get Started Guide Version: 3.0 Release date: 30 June 2016 © 2015 - 2016 MediaTek Inc. This document contains information that is proprietary to MediaTek Inc. (“MediaTek”) and/or its licensor(s). MediaTek cannot grant you permission for any material that is owned by third parties. You may only use or reproduce this document if you have agreed to and been bound by the applicable license agreement with MediaTek (“License Agreement”) and been granted explicit permission within the License Agreement (“Permitted User”). If you are not a Permitted User, please cease any access or use of this document immediately. Any unauthorized use, reproduction or disclosure of this document in whole or in part is strictly prohibited. THIS DOCUMENT IS PROVIDED ON AN “AS-IS” BASIS ONLY. MEDIATEK EXPRESSLY DISCLAIMS ANY AND ALL WARRANTIES OF ANY KIND AND SHALL IN NO EVENT BE LIABLE FOR ANY CLAIMS RELATING TO OR ARISING OUT OF THIS DOCUMENT OR ANY USE OR INABILITY TO USE THEREOF. Specifications contained herein are subject to change without notice. MediaTek LinkIt™ Development Platform for RTOS Get Started Guide Document Revision History Revision Date Description 1.0 24 March 2016 Initial version. 2.0 17 May 2016 Move the contents relative to flash, HDK, and build comments to corresponding documents. Add the support of Keil 3.0 30 June 2016 Add the support of IAR. Refine the architecture and provide more information on the SDK usage. © 2015 - 2016 MediaTek Inc. Page i of v This document contains information that is proprietary to MediaTek Inc. -
We Shape the Connected World Automotive Autonomy Generating Energy Effectively Wearable Technology ARM’S Technology Is Cars Are Becoming Mobile Computing Platforms
ARM Holdings plc Annual Report 2015: Strategic Report We shape the connected world Automotive autonomy Generating energy effectively Wearable technology ARM’s technology is Cars are becoming mobile computing platforms. Wind turbines and solar panels can be made Smart watches, biometric-monitors and More sensors and cameras are being included more effective by including technology that augmented reality headsets are intelligent, to assist the driver with lane detection, reading controls and monitors the wind turbine, and connected devices that can give us extra shaping the way we roadside signage and identifying potential hazards aggregates data across the entire wind farm. information to improve our health and or people crossing the road. In time, driver wellness, or just to help us have more fun. all live our lives; in the assistance may lead to a fully automated vehicle. home, as we travel, at school or work, and as we have fun with our friends Mobile computing Smart city streets Intelligent networks Smarter homes ARM-based mobile computers, including City infrastructure from street lights to car Broadband and mobile phone network speeds Cost-efficiency in the home can be improved smartphones, tablets and some laptops are, parking meters can be made more effective by are increasing, and latency decreasing, enabling through learning thermostats that understand for many people, the primary device for their embedding intelligent chips. Street lights that new services for operators to provide to your daily routine, domestic appliances that use work, whether in an office or on the road; can dim when no one is nearby will save energy consumers and enterprises, from delivering advanced algorithms for calculating water and for researching and writing school assignments; and reduce carbon emissions, and prognostics in more movie and TV options to collating and detergent requirements, and smart meters that and for engaging with friends. -
Valorising the Iot Databox: Creating Value for Everyone Charith Perera1*, Susan Y
TRANSACTIONS ON EMERGING TELECOMMUNICATIONS TECHNOLOGIES Trans. Emerging Tel. Tech. 2017; 28:e3125 Published online 11 November 2016 in Wiley Online Library (wileyonlinelibrary.com). DOI: 10.1002/ett.3125 RESEARCH ARTICLE Valorising the IoT Databox: creating value for everyone Charith Perera1*, Susan Y. L. Wakenshaw2, Tim Baarslag3, Hamed Haddadi4, Arosha K. Bandara1, Richard Mortier5, Andy Crabtree6, Irene C. L. Ng2, Derek McAuley6 and Jon Crowcroft5 1 School of Computing and Communications, The Open University, Walton Hall, Milton Keynes MK7 6AA, UK 2 Warwick Manufacturing Group, University of Warwick, Coventry CV4 7AL, UK 3 University of Southampton, Southampton SO17 1BJ, UK 4 School of Electronic Engineering and Computer Science, Queen Mary University of London, Mile End Road, London E1 4NS, UK 5 Computer Laboratory, University of Cambridge, Cambridge CB3 0FD, UK 6 School of Computer Science, University of Nottingham, Jubilee Campus, Nottingham NG8 1BB, UK ABSTRACT The Internet of Things is expected to generate large amounts of heterogeneous data from diverse sources including physical sensors, user devices and social media platforms. Over the last few years, significant attention has been focused on personal data, particularly data generated by smart wearable and smart home devices. Making personal data available for access and trade is expected to become a part of the data-driven digital economy. In this position paper, we review the research challenges in building personal Databoxes that hold personal data and enable data access by other parties and potentially thus sharing of data with other parties. These Databoxes are expected to become a core part of future data marketplaces. Copyright © 2016 The Authors Transactions on Emerging Telecommunications Technologies Published by John Wiley & Sons, Ltd. -
Mediatek Inc
01 May 2015 Asia Pacific/Taiwan Equity Research Semiconductor Devices MediaTek Inc. (2454.TW / 2454 TT) Rating NEUTRAL* Price (30 Apr 15, NT$) 395.00 RESULTS Target price (NT$) 405.00¹ Upside/downside (%) 2.5 Mkt cap (NT$ mn) 708,117 (US$ 23,121) 2Q lacks growth, but a high bar is set for 2H Enterprise value (NT$ mn) 544,619 ■ 1Q15 results in line with CS, but below street. 1Q15 sales were already Number of shares (mn) 1,792.70 Free float (%) 89.1 reported at NT$47.5 bn, -14.3% QoQ. Smartphone shipments were 85 mn 52-week price range 535.0 - 390.0 (30mn LTE), down from 95-100mn in 4Q14 due to seasonality and emerging ADTO - 6M (US$ mn) 101.0 market weakness. GMs met our 47.3% vs 46-48% guidance and OpM was also *Stock ratings are relative to the coverage universe in each analyst's or each team's respective sector. in line at 16.1% on cost controls. Lower non-op income kept EPS only in line ¹Target price is for 12 months. with our NT$4.62 and below street's NT$4.97. Research Analysts ■ 2Q15 guidance below, inventory elevated. Sales were guided -5% to +3% Randy Abrams, CFA QoQ, below CS/street's +9%/+18% QoQ on 3G price pressure and 4G mix 886 2 2715 6366 [email protected] skewed to the entry level. Margins are in line, with GMs at 45.5-47.5% and Nickie Yue OpM at 12.5-16.5%. Inventory is elevated, at 102 days and guided to stay 886 2 2715 6364 98-110 days in 2Q15, requiring 2H15 acceleration. -
IN the UNITED STATES DISTRICT COURT for the WESTERN DISTRICT of TEXAS WACO DIVISION AMERICAN PATENTS LLC, Plaintiff, V. ANALOG D
Case 6:18-cv-00356 Document 1 Filed 12/06/18 Page 1 of 64 IN THE UNITED STATES DISTRICT COURT FOR THE WESTERN DISTRICT OF TEXAS WACO DIVISION AMERICAN PATENTS LLC, CIVIL ACTION NO. 6:18-CV-356 Plaintiff, ORIGINAL COMPLAINT FOR v. PATENT INFRINGEMENT ANALOG DEVICES, INC., CYPRESS JURY TRIAL DEMANDED SEMICONDUCTOR CORPORATION, MARVELL INTERNATIONAL, LTD., MEDIATEK INC., and MEDIATEK USA INC., Defendants. ORIGINAL COMPLAINT FOR PATENT INFRINGEMENT Plaintiff American Patents LLC (“American Patents” or “Plaintiff”) files this original complaint against Defendants Analog Devices, Inc., Cypress Semiconductor Corporation, Marvell International, Ltd., MediaTek Inc., and MediaTek USA Inc. (collectively “Defendants”), alleging, based on its own knowledge as to itself and its own actions and based on information and belief as to all other matters, as follows: PARTIES 1. American Patents is a limited liability company formed under the laws of the State of Texas, with its principal place of business at 2325 Oak Alley, Tyler, Texas, 75703. 2. Analog Devices, Inc. (“Analog”) is a corporation organized and existing under the laws of the state of Massachusetts. It can be served via its registered agent: CT Corp System, 1999 Bryan Street, Suite 900, Dallas, TX 75201. 3. Analog is one of the world’s largest manufacturers of integrated circuits. Case 6:18-cv-00356 Document 1 Filed 12/06/18 Page 2 of 64 4. Cypress Semiconductor Corporation (“Cypress”) is a corporation organized under the laws of the state of Delaware. Cypress can be served with process by serving its registered agent: Corporation Service Company d/b/a CSC-Lawyers Incorporating Service Company, 211 E. -
ARM Roadmap Spring 2017
ARM Roadmap Spring 2017 Robert Boys [email protected] Version 9.0 Agenda . Roadmap . Architectures ARM1™ die . Issues . What is NEW ! . big.LITTLE™ . 64 Bit . Cortex®-A15 . 64 BIT . DynamIQ 3 © ARM 2017 In the Beginning… . 1985 32 years ago in a barn.... 12 engineers . Cash from Apple and VLSI . IP from Acorn Computers . Proof of concept . No patents, no independent customers, product not ready for mass market. A barn, some energy, experience and belief: “We’re going to be the Global Standard” 4 © ARM 2017 The Cortex Processor Roadmap in 2008 Application Real-time Microcontroller Cortex-A9 Cortex-A8 ARM11 Cortex-R4F ARM9 Cortex-R4 ARM7TDMI ARM7 Cortex-M3 SC300 Cortex-M1 5 © ARM 2017 5 Cortex-A73 ARM 2017 Processor Roadmap Cortex-A35 Cortex-A32 Cortex-A72 Cortex-A57 ARM 7, 9, 11 Cortex-A17 Application Cortex-A53 Cortex-A15 Real-time Not to scale to Not Cortex-A9 (Dual) Microcontroller Cortex-A9 (MPCore) Cortex-A8 Cortex-A7 ARM11(MP) Cortex-A5 MMU ARM926EJ-S Cortex-R52 No MMU Cortex-R8 200+ MHz Cortex-R7 ARM9 Cortex-R5 Cortex-R4 Cortex-M7 200+ MHz Cortex-M33 ARM7TDM 72 – 150 + MHz Cortex-M4 Cortex-M3 ARM7I SC300 Cortex-M23 DesignStart™ Cortex-M1 SC000 Cortex-M0+ Cortex-M0 6 © ARM 2017 6 Versions, cores and architectures ? Family Architecture Cores ARM7TDMI ARMv4T ARM7TDMI(S) ARM9 ARM9E ARMv5TE ARM926EJ-S, ARM966E-S ARM11 ARMv6 (T2) ARM1136(F), 1156T2(F)-S, 1176JZ(F), ARM11 MPCore™ Cortex-A ARMv7-A Cortex-A5, A7, A8, A9, A12, A15, A17 Cortex-R ARMv7-R Cortex-R4(F), Cortex-R5, R7, R8 … Cortex-M ARMv7-M Cortex-M3, M4, M7 (M7 is ARMv7-ME) ARMv6-M Cortex-M1, M0, M0+ NEW ! ARMv8-A 64 Bit: Cortex-A35/A53/57/A72 Cortex-A73 Cortex-A32 NEW ! ARMv8-R 32 Bit: Cortex-R52 NEW ! ARMv8-M 32 Bit: Cortex-M23 & M33 TrustZone® 7 © ARM 2017 What is New ? DynamIQ ! . -
042Cf377-Ed0c-4715-9260-770F680082fc.Pdf
WiFi Tablets 70 Neon + The ARCHOS 70 Neon Plus is one of the most affordable tablets on the market. It includes a powerful quad-core processor running the latest Android operating system: Android™ 5.1 Lollipop®. The 7-inch IPS display provides incredible colors and wide viewing angles, perfect for enjoying your content on-the-go. The ARCHOS 70 Neon Plus is designed to offer a unique multimedia experience. AndroidTM 5.1, Lollipop® Android™ 5.1, “Lollipop” 7” IPS Capacitive Screen 1024x 600 pixels Rockchip 3126 Quad-Core CPU @ 1.3 GHz 1 GB RAM 8 GB flash memory (+ microSD slot) GB Micro SD Wifi WiFi, dual cameras, micro USB host, G-sensor, speaker... 8 4 5 90b Neon Featuring a powerful 1.2 GHz Quad-core processor and Dual-core graphics processor, the ARCHOS 90b Neon has a super smooth interface. At an affordable price, the ARCHOS 90b Neon delivers an amazing experience to meet all your needs: emails, movies, photos, web browsing… Android™ 4.4, “Kitkat” 9” Capacitive Screen 1024 x 600 pixels All Winner A33 Quad-Core CPU @ 1.2 GHz 512 MB RAM 8 GB flash memory (+ microSD slot) GB Wifi WiFi, dual cameras, micro USB host, G-sensor, 8 speaker... 6 7 101d Neon A mix between large screen and productivity, the ARCHOS 101d Neon includes a large 10.1” screen and ARCHOS media applications, perfect for your multimedia, wherever you are. Featuring a powerful Quad-core processor and Quad-core graphics processor, the ARCHOS 101d Neon offers a super smooth interface for an affordable price and delivers an amazing experience to meet all your needs. -
2017 Iot & Consumer Electronics Guide
PRESENTED BY 2017 IoT & CONSUMER ELECTRONICS ELECTRONICS COOLING® GUIDE SERIES | www.electronics-cooling.com 2017 IoT & CONSUMER ELECTRONICS GUIDE www.electronics-cooling.com | 2 | Electronics Cooling® Guide 2017 IoT & CONSUMER ELECTRONICS GUIDE TABLE OF CONTENTS Product Matrix (Thermal Management Manufacturers) 6 Product Selector 8 Electronics Cooling of Humans 10 MP DIVAKAR, PHD Technical Editor, Electronics Cooling Thermal Management in 12 Consumer-Grade Digital Cameras MP DIVAKAR, PHD Technical Editor, Electronics Cooling Thermal Management-Enabled 14 Products at CES 2017 MP DIVAKAR, PHD Technical Editor, Electronics Cooling Thermal Management of IoT 19 Hardware: Gateways MP DIVAKAR, PHD Technical Editor, Electronics Cooling Inductive Wireless Charging is 23 Now a Thermal Design Problem DR. VINIT SINGH NuCurrent, CTO REFERENCE SECTION Ecosystems 28 Overview of Components of 29 IoT & Consumer Electronics Products Design Aids & Tools 32 Calculations 33 Index of Advertisers 34 www.electronics-cooling.com | 3 | Electronics Cooling® Guide FOREWARD In this inaugural issue of Electronics Cooling®’s series of digital guides, IoT & Consumer Electronics, we seek to sup- ply you with the latest in thermal management of consumer electronics and the Internet of Things. The intent of these digital guides is to bring you a collection of articles and information on thermal management ma- terials. This issue features a brief description of the ecosystem for thermal management products, an overview of thermal management challenges, and some high-level descriptions of thermal design elements. We also feature more in-depth coverage in longer articles on select products. There are many unique challenges that every thermal management professional has to address with respect to IoT and Consumer Electronics products. -
Table of Contents
43rdDAC-2C 7/3/06 9:16 AM Page 1 The 43rd Design Automation Conference • July 24 - 28, 2006 • San Francisco, CA Table of Contents 44th DAC Call For Papers ........................................................................................64-65 Keynote Addresses Additional Conference and Hotel Information........................................inside back cover • Monday Keynote Address . 6 • Conference Shuttle Bus Service • Tuesday Keynote Address. 7 • First Aid Rooms • Thursday Keynote Address. .8 • Guest/Family Program MEGa Sessions..............................................................................................................5 • Hotel Locations Monday Schedule ........................................................................................................13 • On-Site Information Desk Monday Tutorial Descriptions..................................................................................42 • San Francisco Attractions New Exhibitors ............................................................................................................4 • Weather Panel Committee ........................................................................................................67 • Wednesday Night Party Pavilion Panels ..............................................................................................................9-12 Additional Meetings ....................................................................................................61-63 Proceedings ..................................................................................................................56 -
Intel Celeron Mediatek Education Comparison
A Principled Technologies report: Hands-on testing. Real-world results. HP Chromebook x360 with an Intel® Celeron® processor Encode an HD Merge audio Print a diagram video and save tracks and save and save over 5 minutes 10 seconds over a second in the PowerDirector in the SoundTrap in the Lucidchart Android™ app web app Chrome app Encode HD Merge Encode HD Merge Merge Print video audio tracks video audio tracks audio tracks diagram Enable students to do more in less time with an Intel processor-powered Chromebook A Chromebook powered by an Intel Celeron N3450 processor completed several media-focused activities faster than a Chromebook powered by a MediaTek processor Every day, students use apps to navigate the digital spaces that classrooms have become. If devices running media-based apps take too long to complete an action, students can lose their way, become distracted, and feel frustrated. Putting Chromebooks powered by Intel Celeron N3450 processors in the hands of your students could help them stay engaged and focused. At Principled Technologies, we pitted a new Intel Celeron N3450 processor-powered HP Chromebook against a MediaTek M8173C processor-powered Lenovo Chromebook. The Chromebook powered by Intel took less time to complete several media-focused classroom activities. When students wait less on apps, they face fewer opportunities for distraction and have more time to finish assignments. Enable students to do more in less time with an Intel processor-powered Chromebook March 2018 (revised) The following pages describe a fictional scenario in which middle school students use the Intel Celeron N3450 processor-powered HP Chromebook x360 11 G1 EE and the MediaTek M8173C processor-powered Lenovo N23 Yoga Chromebook. -
Arxiv:1910.06663V1 [Cs.PF] 15 Oct 2019
AI Benchmark: All About Deep Learning on Smartphones in 2019 Andrey Ignatov Radu Timofte Andrei Kulik ETH Zurich ETH Zurich Google Research [email protected] [email protected] [email protected] Seungsoo Yang Ke Wang Felix Baum Max Wu Samsung, Inc. Huawei, Inc. Qualcomm, Inc. MediaTek, Inc. [email protected] [email protected] [email protected] [email protected] Lirong Xu Luc Van Gool∗ Unisoc, Inc. ETH Zurich [email protected] [email protected] Abstract compact models as they were running at best on devices with a single-core 600 MHz Arm CPU and 8-128 MB of The performance of mobile AI accelerators has been evolv- RAM. The situation changed after 2010, when mobile de- ing rapidly in the past two years, nearly doubling with each vices started to get multi-core processors, as well as power- new generation of SoCs. The current 4th generation of mo- ful GPUs, DSPs and NPUs, well suitable for machine and bile NPUs is already approaching the results of CUDA- deep learning tasks. At the same time, there was a fast de- compatible Nvidia graphics cards presented not long ago, velopment of the deep learning field, with numerous novel which together with the increased capabilities of mobile approaches and models that were achieving a fundamentally deep learning frameworks makes it possible to run com- new level of performance for many practical tasks, such as plex and deep AI models on mobile devices. In this pa- image classification, photo and speech processing, neural per, we evaluate the performance and compare the results of language understanding, etc.