23,061 research outputs found
When an attacker meets a cipher-image in 2018: A Year in Review
This paper aims to review the encountered technical contradictions when an
attacker meets the cipher-images encrypted by the image encryption schemes
(algorithms) proposed in 2018 from the viewpoint of an image cryptanalyst. The
most representative works among them are selected and classified according to
their essential structures. Almost all image cryptanalysis works published in
2018 are surveyed due to their small number. The challenging problems on design
and analysis of image encryption schemes are summarized to receive the
attentions of both designers and attackers (cryptanalysts) of image encryption
schemes, which may promote solving scenario-oriented image security problems
with new technologies.Comment: 12 page
Hardware Engines for Bus Encryption: A Survey of Existing Techniques
The widening spectrum of applications and services provided by portable and
embedded devices bring a new dimension of concerns in security. Most of those
embedded systems (pay-TV, PDAs, mobile phones, etc...) make use of external
memory. As a result, the main problem is that data and instructions are
constantly exchanged between memory (RAM) and CPU in clear form on the bus.
This memory may contain confidential data like commercial software or private
contents, which either the end-user or the content provider is willing to
protect. The goal of this paper is to clearly describe the problem of
processor-memory bus communications in this regard and the existing techniques
applied to secure the communication channel through encryption - Performance
overheads implied by those solutions will be extensively discussed in this
paper.Comment: Submitted on behalf of EDAA (http://www.edaa.com/
A novel JXTA-based architecture for implementing heterogenous Networks of Things
This paper presents EmbJXTAChord, a novel peer-to-peer (P2P) architecture
that integrates the good features of different sources, such as JXTA, EXI,
CoAP, combining and augmenting them to provide a framework that is specifically
devised for developing IoT applications over heterogeneous networks.
EmbJXTAChord provides for several interesting properties, such as, distributed
and fault-tolerant resource discovery, transparent routing over subnetworks,
application protocol independence from the transport protocol in narrowband
WSN, thus eliminating the need for using dedicated software or configuring
custom gateways to achieve these functionalities. Moreover, EmbJXTAChord offers
native support not only for TCP/HTTP, but also for Bluetooth RFCOMM and
6LoWPAN, thus opening to a broad range of IoT devices in supernetworks composed
of networks using different interconnection technologies, not necessarily
IP-based. In addition, EmbJXTAChord offers security over heterogeneous networks
providing support for secure peergroups (even nested) and for group encryption,
thus allowing for unicast and multicast communication between groups of objects
sharing the same resources. Finally, EmbJXTAChord provides jxCOAP-E, a new CoAP
implementation that leverages on the transport mechanisms for heterogeneous
networks offered by EmbJXTAChord. jxCOAP-E enables to realize a RESTful service
architecture for peer-to-peer narrowband or broadband networks composed of
devices connected via Ethernet, Wi-Fi, Bluetooth, BLE or IEEE 802.15.4.
Differently from CoAP, jxCOAP-E provides a distributed and fault-tolerant
service discovery mechanism and support for secure multicast communications.
The paper presents EmbJXTAChord, discusses all the relevant design challenges
and presents a comparative experimental performance assessment with
state-of-the-art solutions on commercial-off-the-shelf devices.Comment: 54 pages, 16 figure
Logic BIST: State-of-the-Art and Open Problems
Many believe that in-field hardware faults are too rare in practice to
justify the need for Logic Built-In Self-Test (LBIST) in a design. Until now,
LBIST was primarily used in safety-critical applications. However, this may
change soon. First, even if costly methods like burn-in are applied, it is no
longer possible to get rid of all latent defects in devices at leading-edge
technology. Second, demands for high reliability spread to consumer electronics
as smartphones replace our wallets and IDs. However, today many ASIC vendors
are reluctant to use LBIST. In this paper, we describe the needs for successful
deployment of LBIST in the industrial practice and discuss how these needs can
be addressed. Our work is hoped to attract a wider attention to this important
research topic.Comment: 6 pages, 3 figure
A Non-Blind Watermarking Scheme for Gray Scale Images in Discrete Wavelet Transform Domain using Two Subbands
Digital watermarking is the process to hide digital pattern directly into a
digital content. Digital watermarking techniques are used to address digital
rights management, protect information and conceal secrets. An invisible
non-blind watermarking approach for gray scale images is proposed in this
paper. The host image is decomposed into 3-levels using Discrete Wavelet
Transform. Based on the parent-child relationship between the wavelet
coefficients the Set Partitioning in Hierarchical Trees (SPIHT) compression
algorithm is performed on the LH3, LH2, HL3 and HL2 subbands to find out the
significant coefficients. The most significant coefficients of LH2 and HL2
bands are selected to embed a binary watermark image. The selected significant
coefficients are modulated using Noise Visibility Function, which is considered
as the best strength to ensure better imperceptibility. The approach is tested
against various image processing attacks such as addition of noise, filtering,
cropping, JPEG compression, histogram equalization and contrast adjustment. The
experimental results reveal the high effectiveness of the method.Comment: 9 pages, 7 figure
HiDDeN: Hiding Data With Deep Networks
Recent work has shown that deep neural networks are highly sensitive to tiny
perturbations of input images, giving rise to adversarial examples. Though this
property is usually considered a weakness of learned models, we explore whether
it can be beneficial. We find that neural networks can learn to use invisible
perturbations to encode a rich amount of useful information. In fact, one can
exploit this capability for the task of data hiding. We jointly train encoder
and decoder networks, where given an input message and cover image, the encoder
produces a visually indistinguishable encoded image, from which the decoder can
recover the original message. We show that these encodings are competitive with
existing data hiding algorithms, and further that they can be made robust to
noise: our models learn to reconstruct hidden information in an encoded image
despite the presence of Gaussian blurring, pixel-wise dropout, cropping, and
JPEG compression. Even though JPEG is non-differentiable, we show that a robust
model can be trained using differentiable approximations. Finally, we
demonstrate that adversarial training improves the visual quality of encoded
images
Cryptographically secure multiparty evaluation of system reliability
The precise design of a system may be considered a trade secret which should
be protected, whilst at the same time component manufacturers are sometimes
reluctant to release full test data (perhaps only providing mean time to
failure data). In this situation it seems impractical to both produce an
accurate reliability assessment and satisfy all parties' privacy requirements.
However, we present recent developments in cryptography which, when combined
with the recently developed survival signature in reliability theory, allows
almost total privacy to be maintained in a cryptographically strong manner in
precisely this setting. Thus, the system designer does not have to reveal their
trade secret design and the component manufacturer can retain component test
data in-house.Comment: 13 pages; supplemental material at http://www.louisaslett.com
Data Protection: Combining Fragmentation, Encryption, and Dispersion, a final report
Hardening data protection using multiple methods rather than 'just'
encryption is of paramount importance when considering continuous and powerful
attacks in order to observe, steal, alter, or even destroy private and
confidential information.Our purpose is to look at cost effective data
protection by way of combining fragmentation, encryption, and dispersion over
several physical machines. This involves deriving general schemes to protect
data everywhere throughout a network of machines where they are being
processed, transmitted, and stored during their entire life cycle. This is
being enabled by a number of parallel and distributed architectures using
various set of cores or machines ranging from General Purpose GPUs to multiple
clouds. In this report, we first present a general and conceptual description
of what should be a fragmentation, encryption, and dispersion system (FEDS)
including a number of high level requirements such systems ought to meet. Then,
we focus on two kind of fragmentation. First, a selective separation of
information in two fragments a public one and a private one. We describe a
family of processes and address not only the question of performance but also
the questions of memory occupation, integrity or quality of the restitution of
the information, and of course we conclude with an analysis of the level of
security provided by our algorithms. Then, we analyze works first on general
dispersion systems in a bit wise manner without data structure consideration;
second on fragmentation of information considering data defined along an object
oriented data structure or along a record structure to be stored in a
relational database
Hierarchical Watermarking Framework Based on Analysis of Local Complexity Variations
Increasing production and exchange of multimedia content has increased the
need for better protection of copyright by means of watermarking. Different
methods have been proposed to satisfy the tradeoff between imperceptibility and
robustness as two important characteristics in watermarking while maintaining
proper data-embedding capacity. Many watermarking methods use image independent
set of parameters. Different images possess different potentials for robust and
transparent hosting of watermark data. To overcome this deficiency, in this
paper we have proposed a new hierarchical adaptive watermarking framework. At
the higher level of hierarchy, complexity of an image is ranked in comparison
with complexities of images of a dataset. For a typical dataset of images, the
statistical distribution of block complexities is found. At the lower level of
the hierarchy, for a single cover image that is to be watermarked, complexities
of blocks can be found. Local complexity variation (LCV) among a block and its
neighbors is used to adaptively control the watermark strength factor of each
block. Such local complexity analysis creates an adaptive embedding scheme,
which results in higher transparency by reducing blockiness effects. This two
level hierarchy has enabled our method to take advantage of all image blocks to
elevate the embedding capacity while preserving imperceptibility. For testing
the effectiveness of the proposed framework, contourlet transform (CT) in
conjunction with discrete cosine transform (DCT) is used to embed pseudo-random
binary sequences as watermark. Experimental results show that the proposed
framework elevates the performance the watermarking routine in terms of both
robustness and transparency.Comment: 12 pages, 14 figures, 8 table
SAR Image Segmentation using Vector Quantization Technique on Entropy Images
The development and application of various remote sensing platforms result in
the production of huge amounts of satellite image data. Therefore, there is an
increasing need for effective querying and browsing in these image databases.
In order to take advantage and make good use of satellite images data, we must
be able to extract meaningful information from the imagery. Hence we proposed a
new algorithm for SAR image segmentation. In this paper we propose segmentation
using vector quantization technique on entropy image. Initially, we obtain
entropy image and in second step we use Kekre's Fast Codebook Generation (KFCG)
algorithm for segmentation of the entropy image. Thereafter, a codebook of size
128 was generated for the Entropy image. These code vectors were further
clustered in 8 clusters using same KFCG algorithm and converted into 8 images.
These 8 images were displayed as a result. This approach does not lead to over
segmentation or under segmentation. We compared these results with well known
Gray Level Co-occurrence Matrix. The proposed algorithm gives better
segmentation with less complexity.Comment: IEEE Publication format, International Journal of Computer Science
and Information Security, IJCSIS, Vol. 7 No. 3, March 2010, USA. ISSN 1947
5500, http://sites.google.com/site/ijcsis
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