Application Layer Transport Security (LOAS)

Production systems at Google consist of a constellation of microservices1 that collectively issue O(1010) Remote Procedure Calls (RPCs) per second. When a Google engineer schedules a production workload2, any RPCs issued or received by that workload are protected with ALTS by default. This automatic, zero-configuration protection is provided by Google’s Application Layer Transport Security (ALTS). In addition to the automatic protections conferred on RPC’s, ALTS also facilitates easy service replication, load balancing, and rescheduling across production machines. This paper describes ALTS and explores its deployment over Google’s production infrastructure.

Source: https://cloud.google.com/security/encryption-in-transit/application-layer-transport-security/resources/alts-whitepaper.pdf

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Retpoline: a software construct for preventing branch-target-injection – Google Help

“Retpoline” sequences are a software construct which allow indirect branches to be isolated from speculative execution.  This may be applied to protect sensitive binaries (such as operating system or hypervisor implementations) from branch target injection attacks against their indirect branches.  

The name “retpoline” is a portmanteau of “return” and “trampoline.”  It is a trampoline construct constructed using return operations which also figuratively ensures that any associated speculative execution will “bounce” endlessly.  

(If it brings you any amusement: imagine speculative execution as an overly energetic 7-year old that we must now build a warehouse of trampolines around.)

Source: https://support.google.com/faqs/answer/7625886

Logic in Access Control (Tutorial Notes)

Abstract. Access control is central to security in computer systems. Over the
years, there have been many efforts to explain and to improve access control,
sometimes with logical ideas and tools. This paper is a partial survey and discussion
of the role of logic in access control. It considers logical foundations
for access control and their applications, in particular in languages for security
policies. It focuses on some specific logics and their properties. It is intended
as a written counterpart to a tutorial given at the 2009 International School on
Foundations of Security Analysis and Design.

Source: https://users.soe.ucsc.edu/~abadi/Papers/fosad-acllogic.pdf

Logic in Access Control

Access control is central to security in computer systems.
Over the years, there have been many efforts to explain and
to improve access control, sometimes with logical ideas and
tools. This paper is a partial survey and discussion of the
role of logic in access control. It considers logical foundations
for access control and their applications, in particular
in languages for programming security policies.

Source: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.4.7963&rep=rep1&type=pdf

Fleet management at scale

Google’s employees are spread across the globe, and with job functions
ranging from software engineers to financial analysts, they require a broad
spectrum of technology to get their jobs done. As a result, we manage a fleet
of nearly a quarter-million computers (workstations and laptops) across four
operating systems (macOS, Windows, Linux, and Chrome OS).
Our colleagues often ask how we’re able to manage such a diverse fleet. Do
we have access to unlimited resources? Impose draconian security policies
on users? Shift the maintenance burden to our support staff?
The truth is that the bigger we get, the more we look for ways to increase
efficiency without sacrificing security or user productivity. We scale our
engineering teams by relying on reviewable, repeatable, and automated
backend processes and minimizing GUI-based configuration tools. Using and
developing open-source software saves money and provides us with a level
of flexibility that’s often missing from proprietary software and closed
systems. And we strike a careful balance between user uptime and security
by giving users freedom to get their work done while preventing them from
doing harm, like installing malware or exposing Google data.
This paper describes some of the tools and systems that we use to image,
manage, and secure our varied inventory of workstations and laptops . Some
1
tools were built by third parties—sometimes with our own modifications to
make them work for us. We also created several tools to meet our own
enterprise needs, often open sourcing them later for wider use. By sharing
this information, we hope to help others navigate some of the challenges
we’ve faced—and ultimately overcame—throughout our enterprise fleet
management journey.

Source: https://services.google.com/fh/files/misc/fleet_management_at_scale_white_paper.pdf

A Mathematical Theory of Communication

THE recent development of various methods of modulation such as PCM and PPM which exchange
bandwidth for signal-to-noise ratio has intensified the interest in a general theory of communication. A
basis for such a theory is contained in the important papers of Nyquist1 and Hartley2 on this subject. In the
present paper we will extend the theory to include a number of new factors, in particular the effect of noise
in the channel, and the savings possible due to the statistical structure of the original message and due to the
nature of the final destination of the information.

Source: http://math.harvard.edu/~ctm/home/text/others/shannon/entropy/entropy.pdf

Design patterns for container-based distributed systems

In the late 1980s and early 1990s, object-oriented pro-
gramming revolutionized software development, popu-
larizing the approach of building of applications as col-
lections of modular components. Today we are seeing
a similar revolution in distributed system development,
with the increasing popularity of microservice archi-
tectures built from containerized software components.
Containers [15] [22] [1] [2] are particularly well-suited
as the fundamental “object” in distributed systems by
virtue of the walls they erect at the container bound-
ary. As this architectural style matures, we are seeing the
emergence of design patterns, much as we did for object-
oriented programs, and for the same reason – thinking in
terms of objects (or containers) abstracts away the low-
level details of code, eventually revealing higher-level
patterns that are common to a variety of applications and
algorithms.
This paper describes three types of design patterns
that we have observed emerging in container-based dis-
tributed systems: single-container patterns for container
management, single-node patterns of closely cooperat-
ing containers, and multi-node patterns for distributed
algorithms. Like object-oriented patterns before them,
these patterns for distributed computation encode best
practices, simplify development, and make the systems
where they are used more reliable.

Source: https://static.googleusercontent.com/media/research.google.com/en//pubs/archive/45406.pdf