504 research outputs found
A heterogeneous computing environment to solve the 768-bit RSA challenge
In December 2009 the 768-bit, 232-digit number RSA-768 was factored using the number field sieve. Overall, the computational challenge would take more than 1700 years on a single, standard core. In the article we present the heterogeneous computing approach, involving different compute clusters and Grid computing environments, used to solve this proble
gcodeml: A Grid-enabled Tool for Detecting Positive Selection in Biological Evolution
One of the important questions in biological evolution is to know if certain
changes along protein coding genes have contributed to the adaptation of
species. This problem is known to be biologically complex and computationally
very expensive. It, therefore, requires efficient Grid or cluster solutions to
overcome the computational challenge. We have developed a Grid-enabled tool
(gcodeml) that relies on the PAML (codeml) package to help analyse large
phylogenetic datasets on both Grids and computational clusters. Although we
report on results for gcodeml, our approach is applicable and customisable to
related problems in biology or other scientific domains.Comment: 10 pages, 4 figures. To appear in the HealthGrid 2012 con
On the Cryptanalysis of Public-Key Cryptography
Nowadays, the most popular public-key cryptosystems are based on either the integer factorization or the discrete logarithm problem. The feasibility of solving these mathematical problems in practice is studied and techniques are presented to speed-up the underlying arithmetic on parallel architectures. The fastest known approach to solve the discrete logarithm problem in groups of elliptic curves over finite fields is the Pollard rho method. The negation map can be used to speed up this calculation by a factor √2. It is well known that the random walks used by Pollard rho when combined with the negation map get trapped in fruitless cycles. We show that previously published approaches to deal with this problem are plagued by recurring cycles, and we propose effective alternative countermeasures. Furthermore, fast modular arithmetic is introduced which can take advantage of prime moduli of a special form using efficient "sloppy reduction." The effectiveness of these techniques is demonstrated by solving a 112-bit elliptic curve discrete logarithm problem using a cluster of PlayStation 3 game consoles: breaking a public-key standard and setting a new world record. The elliptic curve method (ECM) for integer factorization is the asymptotically fastest method to find relatively small factors of large integers. From a cryptanalytic point of view the performance of ECM gives information about secure parameter choices of some cryptographic protocols. We optimize ECM by proposing carry-free arithmetic modulo Mersenne numbers (numbers of the form 2M – 1) especially suitable for parallel architectures. Our implementation of these techniques on a cluster of PlayStation 3 game consoles set a new record by finding a 241-bit prime factor of 21181 – 1. A normal form for elliptic curves introduced by Edwards results in the fastest elliptic curve arithmetic in practice. Techniques to reduce the temporary storage and enhance the performance even further in the setting of ECM are presented. Our results enable one to run ECM efficiently on resource-constrained platforms such as graphics processing units
New Secure IoT Architectures, Communication Protocols and User Interaction Technologies for Home Automation, Industrial and Smart Environments
Programa Oficial de Doutoramento en Tecnoloxías da Información e das Comunicacións en Redes Móbiles. 5029V01Tese por compendio de publicacións[Abstract]
The Internet of Things (IoT) presents a communication network where heterogeneous
physical devices such as vehicles, homes, urban infrastructures or industrial machinery
are interconnected and share data. For these communications to be successful, it is
necessary to integrate and embed electronic devices that allow for obtaining environmental
information (sensors), for performing physical actuations (actuators) as well as
for sending and receiving data (network interfaces).
This integration of embedded systems poses several challenges. It is needed for these
devices to present very low power consumption. In many cases IoT nodes are powered by
batteries or constrained power supplies. Moreover, the great amount of devices needed in
an IoT network makes power e ciency one of the major concerns of these deployments,
due to the cost and environmental impact of the energy consumption. This need for low
energy consumption is demanded by resource constrained devices, con
icting with the
second major concern of IoT: security and data privacy. There are critical urban and
industrial systems, such as tra c management, water supply, maritime control, railway
control or high risk industrial manufacturing systems such as oil re neries that will
obtain great bene ts from IoT deployments, for which non-authorized access can posse
severe risks for public safety. On the other hand, both these public systems and the
ones deployed on private environments (homes, working places, malls) present a risk for
the privacy and security of their users. These IoT deployments need advanced security
mechanisms, both to prevent access to the devices and to protect the data exchanged
by them.
As a consequence, it is needed to improve two main aspects: energy e ciency of IoT
devices and the use of lightweight security mechanisms that can be implemented by
these resource constrained devices but at the same time guarantee a fair degree of
security.
The huge amount of data transmitted by this type of networks also presents another
challenge. There are big data systems capable of processing large amounts of data,
but with IoT the granularity and dispersion of the generated information presents a
new scenario very di erent from the one existing nowadays. Forecasts anticipate that there will be a growth from the 15 billion installed devices in 2015 to more than 75
billion devices in 2025. Moreover, there will be much more services exploiting the data
produced by these networks, meaning the resulting tra c will be even higher. The
information must not only be processed in real time, but data mining processes will
have to be performed to historical data.
The main goal of this Ph.D. thesis is to analyze each one of the previously described
challenges and to provide solutions that allow for an adequate adoption of IoT in
Industrial, domestic and, in general, any scenario that can obtain any bene t from the
interconnection and
exibility that IoT brings.[Resumen]
La internet de las cosas (IoT o Internet of Things) representa una red de intercomunicaciones
en la que participan dispositivos físicos de toda índole, como vehículos,
viviendas, electrodomésticos, infraestructuras urbanas o maquinaria y dispositivos industriales.
Para que esta comunicación se pueda llevar a cabo es necesario integrar
elementos electr onicos que permitan obtener informaci on del entorno (sensores), realizar
acciones f sicas (actuadores) y enviar y recibir la informaci on necesaria (interfaces de
comunicaciones de red).
La integración y uso de estos sistemas electrónicos embebidos supone varios retos. Es
necesario que dichos dispositivos presenten un consumo reducido. En muchos casos
deberían ser alimentados por baterías o fuentes de alimentación limitadas. Además,
la gran cantidad de dispositivos que involucra la IoT hace necesario que la e ciencia
energética de los mismos sea una de las principales preocupaciones, por el coste e
implicaciones medioambientales que supone el consumo de electricidad de los mismos.
Esta necesidad de limitar el consumo provoca que dichos dispositivos tengan unas
prestaciones muy limitadas, lo que entra en conflicto con la segunda mayor preocupación
de la IoT: la seguridad y privacidad de los datos. Por un lado existen sistemas críticos
urbanos e industriales, como puede ser la regulación del tráfi co, el control del suministro
de agua, el control marítimo, el control ferroviario o los sistemas de producción industrial
de alto riesgo, como refi nerías, que son claros candidatos a benefi ciarse de la IoT, pero
cuyo acceso no autorizado supone graves problemas de seguridad ciudadana. Por otro
lado, tanto estos sistemas de naturaleza publica, como los que se desplieguen en entornos
privados (viviendas, entornos de trabajo o centros comerciales, entre otros) suponen
un riesgo para la privacidad y también para la seguridad de los usuarios. Todo esto
hace que sean necesarios mecanismos de seguridad avanzados, tanto de acceso a los
dispositivos como de protección de los datos que estos intercambian.
En consecuencia, es necesario avanzar en dos aspectos principales: la e ciencia energética de los dispositivos y el uso de mecanismos de seguridad e ficientes, tanto
computacional como energéticamente, que permitan la implantación de la IoT sin
comprometer la seguridad y la privacidad de los usuarios. Por otro lado, la ingente cantidad de información que estos sistemas puede llegar
a producir presenta otros dos retos que deben ser afrontados. En primer lugar, el
tratamiento y análisis de datos toma una nueva dimensión. Existen sistemas de big
data capaces de procesar cantidades enormes de información, pero con la internet de
las cosas la granularidad y dispersión de los datos plantean un escenario muy distinto
al actual. La previsión es pasar de 15.000.000.000 de dispositivos instalados en 2015
a más de 75.000.000.000 en 2025. Además existirán multitud de servicios que harán
un uso intensivo de estos dispositivos y de los datos que estos intercambian, por lo
que el volumen de tráfico será todavía mayor. Asimismo, la información debe ser
procesada tanto en tiempo real como a posteriori sobre históricos, lo que permite
obtener información estadística muy relevante en diferentes entornos.
El principal objetivo de la presente tesis doctoral es analizar cada uno de estos retos
(e ciencia energética, seguridad, procesamiento de datos e interacción con el usuario)
y plantear soluciones que permitan una correcta adopción de la internet de las cosas
en ámbitos industriales, domésticos y en general en cualquier escenario que se pueda
bene ciar de la interconexión y
flexibilidad de acceso que proporciona el IoT.[Resumo]
O internet das cousas (IoT ou Internet of Things) representa unha rede de intercomunicaci
óns na que participan dispositivos físicos moi diversos, coma vehículos, vivendas,
electrodomésticos, infraestruturas urbanas ou maquinaria e dispositivos industriais.
Para que estas comunicacións se poidan levar a cabo é necesario integrar elementos
electrónicos que permitan obter información da contorna (sensores), realizar accións
físicas (actuadores) e enviar e recibir a información necesaria (interfaces de comunicacións
de rede).
A integración e uso destes sistemas electrónicos integrados supón varios retos. En
primeiro lugar, é necesario que estes dispositivos teñan un consumo reducido. En
moitos casos deberían ser alimentados por baterías ou fontes de alimentación limitadas.
Ademais, a gran cantidade de dispositivos que se empregan na IoT fai necesario que a
e ciencia enerxética dos mesmos sexa unha das principais preocupacións, polo custo e
implicacións medioambientais que supón o consumo de electricidade dos mesmos. Esta
necesidade de limitar o consumo provoca que estes dispositivos teñan unhas prestacións
moi limitadas, o que entra en con
ito coa segunda maior preocupación da IoT: a
seguridade e privacidade dos datos. Por un lado existen sistemas críticos urbanos e
industriais, como pode ser a regulación do tráfi co, o control de augas, o control marítimo,
o control ferroviario ou os sistemas de produción industrial de alto risco, como refinerías,
que son claros candidatos a obter benefi cios da IoT, pero cuxo acceso non autorizado
supón graves problemas de seguridade cidadá. Por outra parte tanto estes sistemas de
natureza pública como os que se despreguen en contornas privadas (vivendas, contornas
de traballo ou centros comerciais entre outros) supoñen un risco para a privacidade e
tamén para a seguridade dos usuarios. Todo isto fai que sexan necesarios mecanismos
de seguridade avanzados, tanto de acceso aos dispositivos como de protección dos datos
que estes intercambian.
En consecuencia, é necesario avanzar en dous aspectos principais: a e ciencia enerxética
dos dispositivos e o uso de mecanismos de seguridade re cientes, tanto computacional
como enerxéticamente, que permitan o despregue da IoT sen comprometer a seguridade
e a privacidade dos usuarios.
Por outro lado, a inxente cantidade de información que estes sistemas poden chegar
a xerar presenta outros retos que deben ser tratados. O tratamento e a análise de
datos toma unha nova dimensión. Existen sistemas de big data capaces de procesar
cantidades enormes de información, pero coa internet das cousas a granularidade e
dispersión dos datos supón un escenario moi distinto ao actual. A previsión e pasar
de 15.000.000.000 de dispositivos instalados no ano 2015 a m ais de 75.000.000.000 de
dispositivos no ano 2025. Ademais existirían multitude de servizos que farían un uso
intensivo destes dispositivos e dos datos que intercambian, polo que o volume de tráfico
sería aínda maior. Do mesmo xeito a información debe ser procesada tanto en tempo
real como posteriormente sobre históricos, o que permite obter información estatística
moi relevante en diferentes contornas.
O principal obxectivo da presente tese doutoral é analizar cada un destes retos
(e ciencia enerxética, seguridade, procesamento de datos e interacción co usuario) e
propor solucións que permitan unha correcta adopción da internet das cousas en ámbitos
industriais, domésticos e en xeral en todo aquel escenario que se poda bene ciar da
interconexión e
flexibilidade de acceso que proporciona a IoT
On the Analysis of Public-Key Cryptologic Algorithms
The RSA cryptosystem introduced in 1977 by Ron Rivest, Adi Shamir and Len Adleman is the most commonly deployed public-key cryptosystem. Elliptic curve cryptography (ECC) introduced in the mid 80's by Neal Koblitz and Victor Miller is becoming an increasingly popular alternative to RSA offering competitive performance due the use of smaller key sizes. Most recently hyperelliptic curve cryptography (HECC) has been demonstrated to have comparable and in some cases better performance than ECC. The security of RSA relies on the integer factorization problem whereas the security of (H)ECC is based on the (hyper)elliptic curve discrete logarithm problem ((H)ECDLP). In this thesis the practical performance of the best methods to solve these problems is analyzed and a method to generate secure ephemeral ECC parameters is presented. The best publicly known algorithm to solve the integer factorization problem is the number field sieve (NFS). Its most time consuming step is the relation collection step. We investigate the use of graphics processing units (GPUs) as accelerators for this step. In this context, methods to efficiently implement modular arithmetic and several factoring algorithms on GPUs are presented and their performance is analyzed in practice. In conclusion, it is shown that integrating state-of-the-art NFS software packages with our GPU software can lead to a speed-up of 50%. In the case of elliptic and hyperelliptic curves for cryptographic use, the best published method to solve the (H)ECDLP is the Pollard rho algorithm. This method can be made faster using classes of equivalence induced by curve automorphisms like the negation map. We present a practical analysis of their use to speed up Pollard rho for elliptic curves and genus 2 hyperelliptic curves defined over prime fields. As a case study, 4 curves at the 128-bit theoretical security level are analyzed in our software framework for Pollard rho to estimate their practical security level. In addition, we present a novel many-core architecture to solve the ECDLP using the Pollard rho algorithm with the negation map on FPGAs. This architecture is used to estimate the cost of solving the Certicom ECCp-131 challenge with a cluster of FPGAs. Our design achieves a speed-up factor of about 4 compared to the state-of-the-art. Finally, we present an efficient method to generate unique, secure and unpredictable ephemeral ECC parameters to be shared by a pair of authenticated users for a single communication. It provides an alternative to the customary use of fixed ECC parameters obtained from publicly available standards designed by untrusted third parties. The effectiveness of our method is demonstrated with a portable implementation for regular PCs and Android smartphones. On a Samsung Galaxy S4 smartphone our implementation generates unique 128-bit secure ECC parameters in 50 milliseconds on average
- …