7,087 research outputs found
Security, Performance and Energy Trade-offs of Hardware-assisted Memory Protection Mechanisms
The deployment of large-scale distributed systems, e.g., publish-subscribe
platforms, that operate over sensitive data using the infrastructure of public
cloud providers, is nowadays heavily hindered by the surging lack of trust
toward the cloud operators. Although purely software-based solutions exist to
protect the confidentiality of data and the processing itself, such as
homomorphic encryption schemes, their performance is far from being practical
under real-world workloads.
The performance trade-offs of two novel hardware-assisted memory protection
mechanisms, namely AMD SEV and Intel SGX - currently available on the market to
tackle this problem, are described in this practical experience.
Specifically, we implement and evaluate a publish/subscribe use-case and
evaluate the impact of the memory protection mechanisms and the resulting
performance. This paper reports on the experience gained while building this
system, in particular when having to cope with the technical limitations
imposed by SEV and SGX.
Several trade-offs that provide valuable insights in terms of latency,
throughput, processing time and energy requirements are exhibited by means of
micro- and macro-benchmarks.Comment: European Commission Project: LEGaTO - Low Energy Toolset for
Heterogeneous Computing (EC-H2020-780681
A Survey on Wireless Security: Technical Challenges, Recent Advances and Future Trends
This paper examines the security vulnerabilities and threats imposed by the
inherent open nature of wireless communications and to devise efficient defense
mechanisms for improving the wireless network security. We first summarize the
security requirements of wireless networks, including their authenticity,
confidentiality, integrity and availability issues. Next, a comprehensive
overview of security attacks encountered in wireless networks is presented in
view of the network protocol architecture, where the potential security threats
are discussed at each protocol layer. We also provide a survey of the existing
security protocols and algorithms that are adopted in the existing wireless
network standards, such as the Bluetooth, Wi-Fi, WiMAX, and the long-term
evolution (LTE) systems. Then, we discuss the state-of-the-art in
physical-layer security, which is an emerging technique of securing the open
communications environment against eavesdropping attacks at the physical layer.
We also introduce the family of various jamming attacks and their
counter-measures, including the constant jammer, intermittent jammer, reactive
jammer, adaptive jammer and intelligent jammer. Additionally, we discuss the
integration of physical-layer security into existing authentication and
cryptography mechanisms for further securing wireless networks. Finally, some
technical challenges which remain unresolved at the time of writing are
summarized and the future trends in wireless security are discussed.Comment: 36 pages. Accepted to Appear in Proceedings of the IEEE, 201
LightBox: Full-stack Protected Stateful Middlebox at Lightning Speed
Running off-site software middleboxes at third-party service providers has
been a popular practice. However, routing large volumes of raw traffic, which
may carry sensitive information, to a remote site for processing raises severe
security concerns. Prior solutions often abstract away important factors
pertinent to real-world deployment. In particular, they overlook the
significance of metadata protection and stateful processing. Unprotected
traffic metadata like low-level headers, size and count, can be exploited to
learn supposedly encrypted application contents. Meanwhile, tracking the states
of 100,000s of flows concurrently is often indispensable in production-level
middleboxes deployed at real networks.
We present LightBox, the first system that can drive off-site middleboxes at
near-native speed with stateful processing and the most comprehensive
protection to date. Built upon commodity trusted hardware, Intel SGX, LightBox
is the product of our systematic investigation of how to overcome the inherent
limitations of secure enclaves using domain knowledge and customization. First,
we introduce an elegant virtual network interface that allows convenient access
to fully protected packets at line rate without leaving the enclave, as if from
the trusted source network. Second, we provide complete flow state management
for efficient stateful processing, by tailoring a set of data structures and
algorithms optimized for the highly constrained enclave space. Extensive
evaluations demonstrate that LightBox, with all security benefits, can achieve
10Gbps packet I/O, and that with case studies on three stateful middleboxes, it
can operate at near-native speed.Comment: Accepted at ACM CCS 201
MemShield: GPU-assisted software memory encryption
Cryptographic algorithm implementations are vulnerable to Cold Boot attacks,
which consist in exploiting the persistence of RAM cells across reboots or
power down cycles to read the memory contents and recover precious sensitive
data. The principal defensive weapon against Cold Boot attacks is memory
encryption. In this work we propose MemShield, a memory encryption framework
for user space applications that exploits a GPU to safely store the master key
and perform the encryption/decryption operations. We developed a prototype that
is completely transparent to existing applications and does not require changes
to the OS kernel. We discuss the design, the related works, the implementation,
the security analysis, and the performances of MemShield.Comment: 14 pages, 2 figures. In proceedings of the 18th International
Conference on Applied Cryptography and Network Security, ACNS 2020, October
19-22 2020, Rome, Ital
An IoT Endpoint System-on-Chip for Secure and Energy-Efficient Near-Sensor Analytics
Near-sensor data analytics is a promising direction for IoT endpoints, as it
minimizes energy spent on communication and reduces network load - but it also
poses security concerns, as valuable data is stored or sent over the network at
various stages of the analytics pipeline. Using encryption to protect sensitive
data at the boundary of the on-chip analytics engine is a way to address data
security issues. To cope with the combined workload of analytics and encryption
in a tight power envelope, we propose Fulmine, a System-on-Chip based on a
tightly-coupled multi-core cluster augmented with specialized blocks for
compute-intensive data processing and encryption functions, supporting software
programmability for regular computing tasks. The Fulmine SoC, fabricated in
65nm technology, consumes less than 20mW on average at 0.8V achieving an
efficiency of up to 70pJ/B in encryption, 50pJ/px in convolution, or up to
25MIPS/mW in software. As a strong argument for real-life flexible application
of our platform, we show experimental results for three secure analytics use
cases: secure autonomous aerial surveillance with a state-of-the-art deep CNN
consuming 3.16pJ per equivalent RISC op; local CNN-based face detection with
secured remote recognition in 5.74pJ/op; and seizure detection with encrypted
data collection from EEG within 12.7pJ/op.Comment: 15 pages, 12 figures, accepted for publication to the IEEE
Transactions on Circuits and Systems - I: Regular Paper
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