15,774 research outputs found
Resilient networking in wireless sensor networks
This report deals with security in wireless sensor networks (WSNs),
especially in network layer. Multiple secure routing protocols have been
proposed in the literature. However, they often use the cryptography to secure
routing functionalities. The cryptography alone is not enough to defend against
multiple attacks due to the node compromise. Therefore, we need more
algorithmic solutions. In this report, we focus on the behavior of routing
protocols to determine which properties make them more resilient to attacks.
Our aim is to find some answers to the following questions. Are there any
existing protocols, not designed initially for security, but which already
contain some inherently resilient properties against attacks under which some
portion of the network nodes is compromised? If yes, which specific behaviors
are making these protocols more resilient? We propose in this report an
overview of security strategies for WSNs in general, including existing attacks
and defensive measures. In this report we focus at the network layer in
particular, and an analysis of the behavior of four particular routing
protocols is provided to determine their inherent resiliency to insider
attacks. The protocols considered are: Dynamic Source Routing (DSR),
Gradient-Based Routing (GBR), Greedy Forwarding (GF) and Random Walk Routing
(RWR)
The weak password problem: chaos, criticality, and encrypted p-CAPTCHAs
Vulnerabilities related to weak passwords are a pressing global economic and
security issue. We report a novel, simple, and effective approach to address
the weak password problem. Building upon chaotic dynamics, criticality at phase
transitions, CAPTCHA recognition, and computational round-off errors we design
an algorithm that strengthens security of passwords. The core idea of our
method is to split a long and secure password into two components. The first
component is memorized by the user. The second component is transformed into a
CAPTCHA image and then protected using evolution of a two-dimensional dynamical
system close to a phase transition, in such a way that standard brute-force
attacks become ineffective. We expect our approach to have wide applications
for authentication and encryption technologies.Comment: 5 pages, 6 figer
Still Wrong Use of Pairings in Cryptography
Several pairing-based cryptographic protocols are recently proposed with a
wide variety of new novel applications including the ones in emerging
technologies like cloud computing, internet of things (IoT), e-health systems
and wearable technologies. There have been however a wide range of incorrect
use of these primitives. The paper of Galbraith, Paterson, and Smart (2006)
pointed out most of the issues related to the incorrect use of pairing-based
cryptography. However, we noticed that some recently proposed applications
still do not use these primitives correctly. This leads to unrealizable,
insecure or too inefficient designs of pairing-based protocols. We observed
that one reason is not being aware of the recent advancements on solving the
discrete logarithm problems in some groups. The main purpose of this article is
to give an understandable, informative, and the most up-to-date criteria for
the correct use of pairing-based cryptography. We thereby deliberately avoid
most of the technical details and rather give special emphasis on the
importance of the correct use of bilinear maps by realizing secure
cryptographic protocols. We list a collection of some recent papers having
wrong security assumptions or realizability/efficiency issues. Finally, we give
a compact and an up-to-date recipe of the correct use of pairings.Comment: 25 page
CryptGraph: Privacy Preserving Graph Analytics on Encrypted Graph
Many graph mining and analysis services have been deployed on the cloud,
which can alleviate users from the burden of implementing and maintaining graph
algorithms. However, putting graph analytics on the cloud can invade users'
privacy. To solve this problem, we propose CryptGraph, which runs graph
analytics on encrypted graph to preserve the privacy of both users' graph data
and the analytic results. In CryptGraph, users encrypt their graphs before
uploading them to the cloud. The cloud runs graph analysis on the encrypted
graphs and obtains results which are also in encrypted form that the cloud
cannot decipher. During the process of computing, the encrypted graphs are
never decrypted on the cloud side. The encrypted results are sent back to users
and users perform the decryption to obtain the plaintext results. In this
process, users' graphs and the analytics results are both encrypted and the
cloud knows neither of them. Thereby, users' privacy can be strongly protected.
Meanwhile, with the help of homomorphic encryption, the results analyzed from
the encrypted graphs are guaranteed to be correct. In this paper, we present
how to encrypt a graph using homomorphic encryption and how to query the
structure of an encrypted graph by computing polynomials. To solve the problem
that certain operations are not executable on encrypted graphs, we propose hard
computation outsourcing to seek help from users. Using two graph algorithms as
examples, we show how to apply our methods to perform analytics on encrypted
graphs. Experiments on two datasets demonstrate the correctness and feasibility
of our methods
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