Draco: Architectural and Operating System Support for System Call Security
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Google Android
Google Android 2008/3/10 NemusTech, Inc. Lee Seung Min 네무스텍㈜ Agenda Introduction Mobile Platform Overview Background : Current Linux Mobile Platform What is Android? Features Architecture Technical Detail Android SDK Porting Android to Real Target Future of Android A conceptual model for mobile software Software Stack Kernel the core of the SW (HW drivers, memory, filesystem, and process management) Middleware The set of peripheral software libraries (messaging and communication engines, WAP renders, codecs, etc) Application Execution Environment An application manager and set APIs UI framework A set of graphic components and an interaction framework Application Suite The set of core handset application ( IDLE screen, dialer, menu screen, contacts, calendar, etc) Mobile Platforms Feature Phone Vendor Platform : Mocha, PDK, WAVE, WISE, KX, etc...... Carrier Platform : SKTelecom TPAK, NTT i-Mode (WAP), Java, WIPI, BREW, etc…… 3rd Party Solution : TAT Cascade, Qualcomm uiOne Smart Phone MicroSoft Windows Mobile Nokia : Symbian, Series 60 Apple, iPhone – OSX 10.5 Leopard Linux Customers & Licensees Not all customers or licensees are shown Source:vendor data Smartphone OS Market Share by Region Smartphone OS market share by region, 2006 Source : Canalys Current Linux Mobile Platforms LiMo Foundation https://www.limofoundation.org/sf/sfmain/do/home TrollTech Qtopia GreenPhone Acquired by Nokia OpenMoko : GNU/Linux based software development platform http://www.openmoko.org , http://www.openmoko.com Linux -
Benchmarking, Analysis, and Optimization of Serverless Function Snapshots
Benchmarking, Analysis, and Optimization of Serverless Function Snapshots Dmitrii Ustiugov∗ Plamen Petrov Marios Kogias† University of Edinburgh University of Edinburgh Microsoft Research United Kingdom United Kingdom United Kingdom Edouard Bugnion Boris Grot EPFL University of Edinburgh Switzerland United Kingdom ABSTRACT CCS CONCEPTS Serverless computing has seen rapid adoption due to its high scala- • Computer systems organization ! Cloud computing; • In- bility and flexible, pay-as-you-go billing model. In serverless, de- formation systems ! Computing platforms; Data centers; • velopers structure their services as a collection of functions, spo- Software and its engineering ! n-tier architectures. radically invoked by various events like clicks. High inter-arrival time variability of function invocations motivates the providers KEYWORDS to start new function instances upon each invocation, leading to cloud computing, datacenters, serverless, virtualization, snapshots significant cold-start delays that degrade user experience. To reduce ACM Reference Format: cold-start latency, the industry has turned to snapshotting, whereby Dmitrii Ustiugov, Plamen Petrov, Marios Kogias, Edouard Bugnion, and Boris an image of a fully-booted function is stored on disk, enabling a Grot. 2021. Benchmarking, Analysis, and Optimization of Serverless Func- faster invocation compared to booting a function from scratch. tion Snapshots . In Proceedings of the 26th ACM International Conference on This work introduces vHive, an open-source framework for Architectural Support for Programming Languages and Operating Systems serverless experimentation with the goal of enabling researchers (ASPLOS ’21), April 19–23, 2021, Virtual, USA. ACM, New York, NY, USA, to study and innovate across the entire serverless stack. Using 14 pages. https://doi.org/10.1145/3445814.3446714 vHive, we characterize a state-of-the-art snapshot-based serverless infrastructure, based on industry-leading Containerd orchestra- 1 INTRODUCTION tion framework and Firecracker hypervisor technologies. -
Qualifikationsprofil #10309
QUALIFIKATIONSPROFIL #10309 ALLGEMEINE DATEN Geburtsjahr: 1972 Ausbildung: Abitur Diplom, Informatik, (TU, Kaiserslautern) Fremdsprachen: Englisch, Französisch Spezialgebiete: Kubernetes KENNTNISSE Tools Active Directory Apache Application Case CATIA CVS Eclipse Exchange Framework GUI Innovator ITIL J2EE JMS LDAP Lotus Notes make MS Exchange MS Outlook MS-Exchange MS-Office MS-Visual Studio NetBeans OSGI RACF SAS sendmail Together Turbine UML VMWare .NET ADS ANT ASP ASP.NET Flash GEnie IDES Image Intellij IDEA IPC Jackson JBOSS Lex MS-Visio ODBC Oracle Application Server OWL PGP SPSS SQS TesserAct Tivoli Toolbook Total Transform Visio Weblogic WebSphere YACC Tätigkeiten Administration Analyse Beratung Design Dokumentation KI Konzeption Optimierung Support Vertrieb Sprachen Ajax Basic C C# C++ Cobol Delphi ETL Fortran Java JavaScript Natural Perl PHP PL/I PL-SQL Python SAL Smalltalk SQL ABAP Atlas Clips Delta FOCUS HTML Nomad Pascal SPL Spring TAL XML Detaillierte Komponenten AM BI FS-BA MDM PDM PM BW CO FI LO PP Datenbanken Approach IBM Microsoft Object Store Oracle Progress Sybase DMS ISAM JDBC mySQL DC/Netzwerke ATM DDS Gateway HBCI Hub Internet Intranet OpenSSL SSL VPN Asynchronous CISCO Router DNS DSL Firewall Gateways HTTP RFC Router Samba Sockets Switches Finance Business Intelligence Excel Konsolidierung Management Projektleiter Reporting Testing Wertpapiere Einkauf CAD Systeme CATIA V5 sonstige Hardware Digital HP PC Scanner Siemens Spark Teradata Bus FileNet NeXT SUN Switching Tools, Methoden Docker Go Kubernetes Rational RUP -
Gvisor Is a Project to Restrict the Number of Syscalls That the Kernel and User Space Need to Communicate
SED 820 Transcript EPISODE 820 [INTRODUCTION] [0:00:00.3] JM: The Linux operating system includes user space and kernel space. In user space, the user can create and interact with a variety of applications directly. In kernel space, the Linux kernel provides a stable environment in which device drivers interact with hardware and manage low-level resources. A Linux container is a virtualized environment that runs within user space. To perform an operation, a process in a container in user space makes a syscall, which is a system call into kernel space. This allows the container to have access to resources like memory and disk. Kernel space must be kept secure to ensure the operating system’s integrity. Linux includes hundreds of syscalls. Each syscall represents an interface between the user space and the kernel space. Security vulnerabilities can emerge from this wide attack surface of different syscalls and most applications only need a small number of syscalls to provide their required functionality. gVisor is a project to restrict the number of syscalls that the kernel and user space need to communicate. gVisor is a runtime layer between the user space container and the kernel space. gVisor reduces the number of syscalls that can be made into kernel space. The security properties of gVisor make it an exciting project today, but it is the portability features of gVisor that hint at a huge future opportunity. By inserting an interpreter interface between containers and the Linux kernel, gVisor presents the container world with an opportunity to run on operating systems other than Linux. -
Surviving Software Dependencies
practice DOI:10.1145/3347446 is additional code a programmer wants Article development led by queue.acm.org to call. Adding a dependency avoids repeating work: designing, testing, de- bugging, and maintaining a specific Software reuse is finally here unit of code. In this article, that unit of but comes with risks. code is referred to as a package; some systems use the terms library and mod- BY RUSS COX ule instead. Taking on externally written depen- dencies is not new. Most programmers have at one point in their careers had to go through the steps of manually Surviving installing a required library, such as C’s PCRE or zlib; C++’s Boost or Qt; or Java’s JodaTime or JUnit. These pack- ages contain high-quality, debugged Software code that required significant exper- tise to develop. For a program that needs the functionality provided by one of these packages, the tedious work of manually downloading, in- Dependencies stalling, and updating the package is easier than the work of redeveloping that functionality from scratch. The high fixed costs of reuse, however, mean manually reused packages tend to be big; a tiny package would be easier to reimplement. FOR DECADES, DISCUSSION of software reuse was more A dependency manager (a.k.a. pack- common than actual software reuse. Today, the situation age manager) automates the download- ing and installation of dependency is reversed: developers reuse software written by others packages. As dependency managers every day, in the form of software dependencies, and the make individual packages easier to download and install, the lower fixed situation goes mostly unexamined. -
Firecracker: Lightweight Virtualization for Serverless Applications
Firecracker: Lightweight Virtualization for Serverless Applications Alexandru Agache, Marc Brooker, Andreea Florescu, Alexandra Iordache, Anthony Liguori, Rolf Neugebauer, Phil Piwonka, and Diana-Maria Popa, Amazon Web Services https://www.usenix.org/conference/nsdi20/presentation/agache This paper is included in the Proceedings of the 17th USENIX Symposium on Networked Systems Design and Implementation (NSDI ’20) February 25–27, 2020 • Santa Clara, CA, USA 978-1-939133-13-7 Open access to the Proceedings of the 17th USENIX Symposium on Networked Systems Design and Implementation (NSDI ’20) is sponsored by Firecracker: Lightweight Virtualization for Serverless Applications Alexandru Agache Marc Brooker Andreea Florescu Amazon Web Services Amazon Web Services Amazon Web Services Alexandra Iordache Anthony Liguori Rolf Neugebauer Amazon Web Services Amazon Web Services Amazon Web Services Phil Piwonka Diana-Maria Popa Amazon Web Services Amazon Web Services Abstract vantage over traditional server provisioning processes: mul- titenancy allows servers to be shared across a large num- Serverless containers and functions are widely used for de- ber of workloads, and the ability to provision new func- ploying and managing software in the cloud. Their popularity tions and containers in milliseconds allows capacity to be is due to reduced cost of operations, improved utilization of switched between workloads quickly as demand changes. hardware, and faster scaling than traditional deployment meth- Serverless is also attracting the attention of the research com- ods. The economics and scale of serverless applications de- munity [21,26,27,44,47], including work on scaling out video mand that workloads from multiple customers run on the same encoding [13], linear algebra [20, 53] and parallel compila- hardware with minimal overhead, while preserving strong se- tion [12]. -
Architectural Implications of Function-As-A-Service Computing
Architectural Implications of Function-as-a-Service Computing Mohammad Shahrad Jonathan Balkind David Wentzlaff Princeton University Princeton University Princeton University Princeton, USA Princeton, USA Princeton, USA [email protected] [email protected] [email protected] ABSTRACT Network Serverless computing is a rapidly growing cloud application model, popularized by Amazon’s Lambda platform. Serverless cloud ser- Scheduling vices provide fine-grained provisioning of resources, which scale Platform (priorwork) automatically with user demand. Function-as-a-Service (FaaS) appli- Queueing Management cations follow this serverless model, with the developer providing 35% decrease in IPC Interference their application as a set of functions which are executed in response due to interference 6x variation due to to a user- or system-generated event. Functions are designed to Memory BW invocation pattern 20x MPKI for be short-lived and execute inside containers or virtual machines, Branch MPKI >10x exec time short functions introducing a range of system-level overheads. This paper studies for short functions Cold Start Server the architectural implications of this emerging paradigm. Using (500ms cold start) Up to 20x (thispaper) Container the commercial-grade Apache OpenWhisk FaaS platform on real slowdown servers, this work investigates and identifies the architectural im- Native plications of FaaS serverless computing. The workloads, along with Execution Figure 1: We characterize the server-level overheads of the way that FaaS inherently interleaves short functions from many Function-as-a-Service applications, compared to native exe- tenants frustrates many of the locality-preserving architectural cution. This contrasts with prior work [2–5] which focused structures common in modern processors. -
The Aurora Operating System
The Aurora Operating System Revisiting the Single Level Store Emil Tsalapatis Ryan Hancock Tavian Barnes RCS Lab, University of Waterloo RCS Lab, University of Waterloo RCS Lab, University of Waterloo [email protected] [email protected] [email protected] Ali José Mashtizadeh RCS Lab, University of Waterloo [email protected] ABSTRACT KEYWORDS Applications on modern operating systems manage their single level stores, transparent persistence, snapshots, check- ephemeral state in memory, and persistent state on disk. En- point/restore suring consistency between them is a source of significant developer effort, yet still a source of significant bugs inma- ACM Reference Format: ture applications. We present the Aurora single level store Emil Tsalapatis, Ryan Hancock, Tavian Barnes, and Ali José Mash- (SLS), an OS that simplifies persistence by automatically per- tizadeh. 2021. The Aurora Operating System: Revisiting the Single sisting all traditionally ephemeral application state. With Level Store. In Workshop on Hot Topics in Operating Systems (HotOS recent storage hardware like NVMe SSDs and NVDIMMs, ’21), June 1-June 3, 2021, Ann Arbor, MI, USA. ACM, New York, NY, Aurora is able to continuously checkpoint entire applications USA, 8 pages. https://doi.org/10.1145/3458336.3465285 with millisecond granularity. Aurora is the first full POSIX single level store to han- dle complex applications ranging from databases to web 1 INTRODUCTION browsers. Moreover, by providing new ways to interact with Single level storage (SLS) systems provide persistence of and manipulate application state, it enables applications to applications as an operating system service. Their advantage provide features that would otherwise be prohibitively dif- lies in removing the semantic gap between the in-memory ficult to implement. -
Containerd: Integration
containerd: integration Lantao Liu (Google) Wei Fu (Alibaba Cloud) containerd status containerd matures ● 5th project to graduate from CNCF ● Broad support from companies ● All major cloud providers using containerd ● Support Linux and Windows platform Architecture Client-Server Design Client - High level operations using client - New functionality, interfaces may change (rarely) Server - Low level interfaces to resources over GRPC - Stable API, guaranteed 1.x compatibility Backend Service Interface - Provides access to all components - Low level components wrapped by metadata store - Provides namespacing (content/Snapshotter/Image/Container) Snapshotter Snapshotters - COW filesystems - Union FS and Block Device implementations - Container RW Layer Metrics Metric API - Metrics exposed through Prometheus API - Exposes metrics for containerd process & container level metrics Kubernetes Runtime Support Kubernetes Runtime Support - CRI gRPC API exposed from containerd - Kubelet can be configured to use containerd as runtime Summary ● Stable gRPC interface ● Kubernetes Runtime Support Smart Client Model gRPC API Smart Client - Mirrors internal component interfaces - General-Purpose interface - Snapshots, Content, Containers, Task, Events, etc - Direct access to the component (e.g. Snapshots) Pull Image Diff Content Snapshotter Image Registry Client Service Service Service Service Get manifest store manifest each layer Get layer store layer each layer prepare snapshot apply diff read layer mount & unpack layer descriptor commit snapshot create -
Open Ongtang-Phd-Dissertation.Pdf
The Pennsylvania State University The Graduate School SECURING MOBILE PHONES IN THE EVOLVING MOBILE ECOSYSTEM A Dissertation in Computer Science and Engineering by Machigar Ongtang © 2010 Machigar Ongtang Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy August 2010 The dissertation of Machigar Ongtang was reviewed and approved∗ by the following: Patrick D. McDaniel Associate Professor of Computer Science and Engineering Dissertation Advisor, Chair of Committee Thomas F. La Porta Distinguished Professor of Computer Science and Engineering Trent Jaeger Associate Professor of Computer Science and Engineering Ling Rothrock Associate Professor of Industrial and Manufacturing Engineering Raj Acharya Professor of Computer Science and Engineering Department Head ∗Signatures are on file in the Graduate School. Abstract The revolution of mobile phone industry has been altering our life and business practices over the past few decades. Driven by user demands and technological advancement, we now experience rich mobile phone applications and sophisticated cellular services ranging from mobile payment, stock trading, to social networking, vehicle tracking to in-car control. As more players joining the community, this mobile phone environment has transformed into a complex network of interacting companies, known as mobile ecosystem. Unfortunately, this opening and converging mobile ecosystem has brought in more opportunities for more attacks on mobile phones, a key element of the system. This dissertation aims to achieve mobile phone security. We reveal two main chal- lenges that we need to overcome, namely developing a clear definition of secure phones, and building security infrastructure that imposes such definition on the phones. We also identify three key elements that contribute to the fidelity of mobile phones, namely, mobile phone platforms, mobile phone applications, and mobile content. -
Cours Système Embarqué Et Système D'exploitation Mobile
COURS SYSTÈME EMBARQUÉ ET SYSTÈME D’EXPLOITATION MOBILE Ikbel Daly Briki 2018/2019 SYSTÈME EMBARQUÉ Un système embarqué: c’est une combinaison de matériels et logiciels permettant de remplir une ou plusieurs fonctions spécifiques avec des contraintes plus ou moins sévères tel que la consommation, la température, la taille, les performances…[Patrice Kadionik, 2004] Un système embarqué est susceptible d’être utilisé dans un environnement matériel de faibles performances (si l’on compare au PC de bureau d’aujourd’hui). Si l’ajout de quelques Mo de mémoire sur un PC de bureau n’a pas une grosse influence sur le budget d’un utilisateur, le gain de quelques Mo sur un produit de grande consommation (téléphone, équipement auto mobile, organiseur personnel) a une énorme influence sur le coût final. [Pierre Ficheux, 2003] 2 SYSTÈME EMBARQUÉ Ébauche d’une définition: c’est un système électronique et informatique autonome qui est dédié à une tâche particulière et contenue dans un système englobant. Il n’est « généralement » pas programmable. Pas d’E/S standards Matériel et application intimement liés Logiciel enfoui … noyé dans le matériel … pas facilement discernable comme dans un PC. Il sont partout ; Radio/réveil Machine à café Télévision / télécommande Moyen de transport 3 Téléphone portable …. CARACTÉRISTIQUES D’UN SYSTÈME EMBARQUÉ Un système embarqué: des ressources limitées Système principalement numérique Le moins cher possible Une puissance de calcul limitée Pas de consommation d’énergie inutile Exécution de logiciel dédié -
Linux Kernel Debugging Advanced Operating Systems 2020/2021
Linux Kernel Debugging Advanced Operating Systems 2020/2021 Vlastimil Babka Linux Kernel Developer, SUSE Labs [email protected] Agenda – Debugging Scenarios • Debugging production kernels – Post-mortem analysis: interpreting kernel oops/panic output, creating and analyzing kernel crash dumps – Kernel observability – dynamic debug, tracing, alt-sysrq dumps, live crash session • Debugging during individual kernel development – Debug prints – printk() facilitiy – Debugger (gdb) support • Finding (latent) bugs during collaborative development – Optional runtime checks configurable during build – Testing and fuzzing – Static analysis 2 Enterprise Linux Distro and Bugs (incl. Kernel) • The software installation (e.g. ISO) itself is free (and open source, obviously) • Customers pay for support subscription – Delivery of (tested by QA) package updates – fixing known bugs, CVE’s… but not more! – Getting reported bugs fixed • Bugs specific to customer’s workload, hardware, “luck”, large number of machines… • Upstream will also fix reported bugs, but only with latest kernel and no effort guarantees • Dealing with kernel bugs, e.g. crashes – Find out the root cause (buggy code) with limited possibilities (compared to local development) • Typically no direct access to customer’s system or workload • Long turnarounds for providing a modified debug kernel and reproducing the bug – Write and deliver a fix (upstream first!) or workaround; fix goes to next update • Possibly a livepatch in some cases – Is a lot of fun ;-) 3 Kernel Oops - The Real World Example