Philanthropy in BRICS countries and the UN Sustainable Development Goals

Philanthropy in the BRICS countries and the UN Sustainable Development Goals is a review prepared by Russian Donors Forum alongside with the research Philanthropy and social investment in the BRICS countries. The review analyses how philanthropy in Brazil, Russia, India, China and South Africa is aligning its activity with the UN Sustainable Development Goals (SDGs), what progress has already been made and what challenges the sector faces.The review studies the common features of philanthropy of the BRICS countries, as well as the role of Agenda 2030 in the sector of philanthropy and social investment in each of the countries

Analysis of random oracle instantiation scenarios for OAEP and other practical schemes

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HardIDX: Practical and Secure Index with SGX

Software-based approaches for search over encrypted data are still either challenged by lack of proper, low-leakage encryption or slow performance. Existing hardware-based approaches do not scale well due to hardware limitations and software designs that are not specifically tailored to the hardware architecture, and are rarely well analyzed for their security (e.g., the impact of side channels). Additionally, existing hardware-based solutions often have a large code footprint in the trusted environment susceptible to software compromises. In this paper we present HardIDX: a hardware-based approach, leveraging Intel's SGX, for search over encrypted data. It implements only the security critical core, i.e., the search functionality, in the trusted environment and resorts to untrusted software for the remainder. HardIDX is deployable as a highly performant encrypted database index: it is logarithmic in the size of the index and searches are performed within a few milliseconds rather than seconds. We formally model and prove the security of our scheme showing that its leakage is equivalent to the best known searchable encryption schemes. Our implementation has a very small code and memory footprint yet still scales to virtually unlimited search index sizes, i.e., size is limited only by the general - non-secure - hardware resources

Detection of Truthful, Semi-Truthful, False and Other News with Arbitrary Topics Using BERT-Based Models

Easy and uncontrolled access to the Internet provokes the wide propagation of false information, which freely circulates in the Internet. Researchers usually solve the problem of fake news detection (FND) in the framework of a known topic and binary classification. In this paper we study possibilities of BERT-based models to detect fake news in news flow with unknown topics and four categories: true, semi-true, false and other. The object of consideration is the dataset CheckThat! Lab proposed for the conference CLEF-2022. The subjects of consideration are the models SBERT, RoBERTa, and mBERT. To improve the quality of classification we use two methods: the addition of a known dataset (LIAR), and the combination of several classes (true + semi-true, false + semi-true). The results outperform the existing achievements, although the state-of-the-art in the FND area is still far from practical applications

Pholidosis Abnormalities and Injuries in the European Pond Turtle (Emys orbicularis) in the Conditions of the Khopersky Nature Reserve

Pholidosis abnormalities and injuries were studied through 194 specimens of European pond turtle (Emys orbicularis) in the Khopersky nature reserve (Voronezh Province, Russia) in 2008, 2009 and 2011. Six types of abnormalities (on the carapace only) were detected. The occurrence of individuals with all types of abnormalities, the partial occurrence of various abnormalities and the average number of abnormalities per individual were analyzed. Most individuals showed signs of predator attack, mostly on the carapace and tail. During winter hibernation, animals with limb injuries were noted

On Notions of Security for Deterministic Encryption, and Efficient Constructions Without Random Oracles

The study of deterministic public-key encryption was initiated by Bellare et al. (CRYPTO ’07), who provided the “strongest possible” notion of security for this primitive (called PRIV) and constructions in the random oracle (RO) model. We focus on constructing efficient deterministic encryption schemes without random oracles. To do so, we propose a slightly weaker notion of security, saying that no partial information about encrypted messages should be leaked as long as each message is a-priori hard-to-guess given the others (while PRIV did not have the latter restriction). Nevertheless, we argue that this version seems adequate for many practical applications. We show equivalence of this definition to single-message and indistinguishability-based ones, which are easier to work with. Then we give general constructions of both chosen-plaintext (CPA) and chosen-ciphertext-attack (CCA) secure deterministic encryption schemes, as well as efficient instantiations of them under standard number-theoretic assumptions. Our constructions build on the recently-introduced framework of Peikert and Waters (STOC ’08) for constructing CCA-secure probabilistic encryption schemes, extending it to the deterministic-encryption setting as well

Practical Architectures for Deployment of Searchable Encryption in a Cloud Environment

Public cloud service providers provide an infrastructure that gives businesses and individuals access to computing power and storage space on a pay-as-you-go basis. This allows these entities to bypass the usual costs associated with having their own data centre such as: hardware, construction, air conditioning and security costs, for example, making this a cost-effective solution for data storage. If the data being stored is of a sensitive nature, encrypting it prior to outsourcing it to a public cloud is a good method of ensuring the confidentiality of the data. With the data being encrypted, however, searching over it becomes unfeasible. In this paper, we examine different architectures for supporting search over encrypted data and discuss some of the challenges that need to be overcome if these techniques are to be engineered into practical systems

GMDH-based Models for Mid-term Forecast of Cryptocurrencies (on example of Waves)

Cryptocurrencies became one of the main trends in modern economy. However by the moment the forecast of cryptocurrencies values is an open problem, which is almost non-reflected in publications related to finance market. Reasons consist in its novelty, large volatility and its strong dependence on subjective factors. In this experimental research we show possibilities of GMDH-technology to give weekly and monthly forecast for values of cryptocurrency \u27Waves\u27 (waves/euro rate). The source information is week data covering the period 2017-2019. We tests 4 algorithms from the GMDH Shell platform on the whole period and on the crisis period 4-th quarter 2017 - 2nd quarter 2018. Baseline is provided by the popular statistical method of double exponential smoothing. The results of Pilot study can be considered as the very promising ones having in view the large variability of data