3,198 research outputs found
Keys in the Clouds: Auditable Multi-device Access to Cryptographic Credentials
Personal cryptographic keys are the foundation of many secure services, but
storing these keys securely is a challenge, especially if they are used from
multiple devices. Storing keys in a centralized location, like an
Internet-accessible server, raises serious security concerns (e.g. server
compromise). Hardware-based Trusted Execution Environments (TEEs) are a
well-known solution for protecting sensitive data in untrusted environments,
and are now becoming available on commodity server platforms.
Although the idea of protecting keys using a server-side TEE is
straight-forward, in this paper we validate this approach and show that it
enables new desirable functionality. We describe the design, implementation,
and evaluation of a TEE-based Cloud Key Store (CKS), an online service for
securely generating, storing, and using personal cryptographic keys. Using
remote attestation, users receive strong assurance about the behaviour of the
CKS, and can authenticate themselves using passwords while avoiding typical
risks of password-based authentication like password theft or phishing. In
addition, this design allows users to i) define policy-based access controls
for keys; ii) delegate keys to other CKS users for a specified time and/or a
limited number of uses; and iii) audit all key usages via a secure audit log.
We have implemented a proof of concept CKS using Intel SGX and integrated this
into GnuPG on Linux and OpenKeychain on Android. Our CKS implementation
performs approximately 6,000 signature operations per second on a single
desktop PC. The latency is in the same order of magnitude as using
locally-stored keys, and 20x faster than smart cards.Comment: Extended version of a paper to appear in the 3rd Workshop on
Security, Privacy, and Identity Management in the Cloud (SECPID) 201
ReCon: Revealing and Controlling PII Leaks in Mobile Network Traffic
It is well known that apps running on mobile devices extensively track and
leak users' personally identifiable information (PII); however, these users
have little visibility into PII leaked through the network traffic generated by
their devices, and have poor control over how, when and where that traffic is
sent and handled by third parties. In this paper, we present the design,
implementation, and evaluation of ReCon: a cross-platform system that reveals
PII leaks and gives users control over them without requiring any special
privileges or custom OSes. ReCon leverages machine learning to reveal potential
PII leaks by inspecting network traffic, and provides a visualization tool to
empower users with the ability to control these leaks via blocking or
substitution of PII. We evaluate ReCon's effectiveness with measurements from
controlled experiments using leaks from the 100 most popular iOS, Android, and
Windows Phone apps, and via an IRB-approved user study with 92 participants. We
show that ReCon is accurate, efficient, and identifies a wider range of PII
than previous approaches.Comment: Please use MobiSys version when referencing this work:
http://dl.acm.org/citation.cfm?id=2906392. 18 pages, recon.meddle.mob
Overcoming Poverty through Digital Inclusion
A growing body of research is showing how digital inclusion can help communities overcome poverty and injustice. The main challenge lies in how best to achieve this goal. The authors argue that digital inclusion must occur in two distinct stages. The first stage is digital literacy, accomplished with the Symbiotic Computer (SC)-smartphones and tablets. The second stage will be professional capacity-building, accomplished with the more traditional Personal Computer (PC)
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