76 research outputs found
On the Security of Cryptographic Protocols Using the Little Theorem of Witness Functions
In this paper, we show how practical the little theorem of witness functions
is in detecting security flaws in some category of cryptographic protocols. We
convey a formal analysis of the Needham-Schroeder symmetric-key protocol in the
theory of witness functions. We show how it helps to teach about a security
vulnerability in a given step of this protocol where the value of security of a
particular sensitive ticket in a sent message unexpectedly plummets compared
with its value when received. This vulnerability may be exploited by an
intruder to mount a replay attack as described by Denning and Sacco.Comment: Accepted at the 2019 IEEE Canadian Conference on Electrical &
Computer Engineering (CCECE) on March 1, 201
Undermining User Privacy on Mobile Devices Using AI
Over the past years, literature has shown that attacks exploiting the
microarchitecture of modern processors pose a serious threat to the privacy of
mobile phone users. This is because applications leave distinct footprints in
the processor, which can be used by malware to infer user activities. In this
work, we show that these inference attacks are considerably more practical when
combined with advanced AI techniques. In particular, we focus on profiling the
activity in the last-level cache (LLC) of ARM processors. We employ a simple
Prime+Probe based monitoring technique to obtain cache traces, which we
classify with Deep Learning methods including Convolutional Neural Networks. We
demonstrate our approach on an off-the-shelf Android phone by launching a
successful attack from an unprivileged, zeropermission App in well under a
minute. The App thereby detects running applications with an accuracy of 98%
and reveals opened websites and streaming videos by monitoring the LLC for at
most 6 seconds. This is possible, since Deep Learning compensates measurement
disturbances stemming from the inherently noisy LLC monitoring and unfavorable
cache characteristics such as random line replacement policies. In summary, our
results show that thanks to advanced AI techniques, inference attacks are
becoming alarmingly easy to implement and execute in practice. This once more
calls for countermeasures that confine microarchitectural leakage and protect
mobile phone applications, especially those valuing the privacy of their users
Cutting Through the Complexity of Reverse Engineering Embedded Devices
Performing security analysis of embedded devices is a challenging task. They present many difficulties not usually found when analyzing commodity systems: undocumented peripherals, esoteric instruction sets, and limited tool support. Thus, a significant amount of reverse engineering is almost always required to analyze such devices. In this paper, we present Incision, an architecture and operating-system agnostic reverse engineering framework. Incision tackles the problem of reducing the upfront effort to analyze complex end-user devices. It combines static and dynamic analyses in a feedback loop, enabling information from each to be used in tandem to improve our overall understanding of the firmware analyzed. We use Incision to analyze a variety of devices and firmware. Our evaluation spans firmware based on three RTOSes, an automotive ECU, and a 4G/LTE baseband. We demonstrate that Incision does not introduce significant complexity to the standard reverse engineering process and requires little manual effort to use. Moreover, its analyses produce correct results with high confidence and are robust across different OSes and ISAs
FSPVDsse: A Forward Secure Publicly Verifiable Dynamic SSE scheme
A symmetric searchable encryption (SSE) scheme allows a client (data owner)
to search on encrypted data outsourced to an untrusted cloud server. The search
may either be a single keyword search or a complex query search like
conjunctive or Boolean keyword search. Information leakage is quite high for
dynamic SSE, where data might be updated. It has been proven that to avoid this
information leakage an SSE scheme with dynamic data must be forward private. A
dynamic SSE scheme is said to be forward private, if adding a keyword-document
pair does not reveal any information about the previous search result with that
keyword.
In SSE setting, the data owner has very low computation and storage power. In
this setting, though some schemes achieve forward privacy with
honest-but-curious cloud, it becomes difficult to achieve forward privacy when
the server is malicious, meaning that it can alter the data. Verifiable dynamic
SSE requires the server to give a proof of the result of the search query. The
data owner can verify this proof efficiently. In this paper, we have proposed a
generic publicly verifiable dynamic SSE (DSSE) scheme that makes any forward
private DSSE scheme verifiable without losing forward privacy. The proposed
scheme does not require any extra storage at owner-side and requires minimal
computational cost as well for the owner. Moreover, we have compared our scheme
with the existing results and show that our scheme is practical.Comment: 17 pages, Published in ProvSec 201
Efficient Strong Privacy-Preserving Conjunctive Keyword Search Over Encrypted Cloud Data
Searchable symmetric encryption (SSE) supports keyword search over outsourced
symmetrically encrypted data. Dynamic searchable symmetric encryption (DSSE), a
variant of SSE, further enables data updating. Most DSSE works with conjunctive
keyword search primarily consider forward and backward privacy. Ideally, the
server should only learn the result sets involving all keywords in the
conjunction. However, existing schemes suffer from keyword pair result pattern
(KPRP) leakage, revealing the partial result sets containing two of query
keywords. We propose the first DSSE scheme to address aforementioned concerns
that achieves strong privacy-preserving conjunctive keyword search.
Specifically, our scheme can maintain forward and backward privacy and
eliminate KPRP leakage, offering a higher level of security. The search
complexity scales with the number of documents stored in the database in
several existing schemes. However, the complexity of our scheme scales with the
update frequency of the least frequent keyword in the conjunction, which is
much smaller than the size of the entire database. Besides, we devise a least
frequent keyword acquisition protocol to reduce frequent interactions between
clients. Finally, we analyze the security of our scheme and evaluate its
performance theoretically and experimentally. The results show that our scheme
has strong privacy preservation and efficiency
SoK: Privacy-Preserving Signatures
Modern security systems depend fundamentally on the ability of users to authenticate their communications to other parties in a network. Unfortunately, cryptographic authentication can substantially undermine the privacy of users. One possible solution to this problem is to use privacy-preserving cryptographic authentication. These protocols allow users to authenticate their communications without revealing their identity to the verifier. In the non-interactive setting, the most common protocols include blind, ring, and group signatures, each of which has been the subject of enormous research in the security and cryptography literature. These primitives are now being deployed at scale in major applications, including Intel\u27s SGX software attestation framework. The depth of the research literature and the prospect of large-scale deployment motivate us to systematize our understanding of the research in this area. This work provides an overview of these techniques, focusing on applications and efficiency
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