DATA CENTERS HEAT UTILIZATION

В статье рассматривается специфика работы Центров обработки данных (ЦОД), примеры использования сбросной низкопотенциальной тепловой энергии от ЦОД, перспективы использования тепла ЦОД российских объектов.The article discusses the work specifics of the data center, examples of the use of low-potential heat energy from the data center, the prospects for the use of heat from Russian data centers

Cryptographically Secure Information Flow Control on Key-Value Stores

We present Clio, an information flow control (IFC) system that transparently incorporates cryptography to enforce confidentiality and integrity policies on untrusted storage. Clio insulates developers from explicitly manipulating keys and cryptographic primitives by leveraging the policy language of the IFC system to automatically use the appropriate keys and correct cryptographic operations. We prove that Clio is secure with a novel proof technique that is based on a proof style from cryptography together with standard programming languages results. We present a prototype Clio implementation and a case study that demonstrates Clio's practicality.Comment: Full version of conference paper appearing in CCS 201

A limited-size ensemble of homogeneous CNN/LSTMs for high-performance word classification

The strength of long short-term memory neural networks (LSTMs) that have been applied is more located in handling sequences of variable length than in handling geometric variability of the image patterns. In this paper, an end-to-end convolutional LSTM neural network is used to handle both geometric variation and sequence variability. The best results for LSTMs are often based on large-scale training of an ensemble of network instances. We show that high performances can be reached on a common benchmark set by using proper data augmentation for just five such networks using a proper coding scheme and a proper voting scheme. The networks have similar architectures (convolutional neural network (CNN): five layers, bidirectional LSTM (BiLSTM): three layers followed by a connectionist temporal classification (CTC) processing step). The approach assumes differently scaled input images and different feature map sizes. Three datasets are used: the standard benchmark RIMES dataset (French); a historical handwritten dataset KdK (Dutch); the standard benchmark George Washington (GW) dataset (English). Final performance obtained for the word-recognition test of RIMES was 96.6%, a clear improvement over other state-of-the-art approaches which did not use a pre-trained network. On the KdK and GW datasets, our approach also shows good results. The proposed approach is deployed in the Monk search engine for historical-handwriting collections

Outbound Authentication for Programmable Secure Coprocessors

A programmable secure coprocessor platform can help solve many security problems in distributed computing. However, these solutions usually require that coprocessor applications be able to participate as full-fledged parties in distributed cryptographic protocols. Thus, to fully enable these solutions, a generic platform must not only provide programmability, maintenance, and configuration in the hostile field---it must also provide outbound authentication for the entities that result. A particular application on a particular untampered device must be able to prove who it is to a party on the other side of the Internet