Assessing the Impact of Poverty Reduction Programs in Vietnam

This paper aims to examine the poverty targeting and impacts of three poverty reeducation programs including programs ‘exemption of educational fees’, ‘provision with health care insurance’, and ‘micro-credit for the poor’ in Vietnam. It is found that the three programs have reached the poor quite well as compared to the international standard. The poor account for around 70 percent of participants in these programs. However the coverage of the programs over the poor is rather low, from 5 percent for the credit program to 11 percent for the health insurance program. There is no impact of the programs found on expenditure per capita, since it might take a long time for the programs to have large effects on income and expenditure. On average, households who were provided with preferential credit are more likely to have a pig, cow, buffalo, horse than other households.Poverty reduction program, impact evaluation, matching, household survey, Vietnam

DR.SGX: Hardening SGX Enclaves against Cache Attacks with Data Location Randomization

Recent research has demonstrated that Intel's SGX is vulnerable to various software-based side-channel attacks. In particular, attacks that monitor CPU caches shared between the victim enclave and untrusted software enable accurate leakage of secret enclave data. Known defenses assume developer assistance, require hardware changes, impose high overhead, or prevent only some of the known attacks. In this paper we propose data location randomization as a novel defensive approach to address the threat of side-channel attacks. Our main goal is to break the link between the cache observations by the privileged adversary and the actual data accesses by the victim. We design and implement a compiler-based tool called DR.SGX that instruments enclave code such that data locations are permuted at the granularity of cache lines. We realize the permutation with the CPU's cryptographic hardware-acceleration units providing secure randomization. To prevent correlation of repeated memory accesses we continuously re-randomize all enclave data during execution. Our solution effectively protects many (but not all) enclaves from cache attacks and provides a complementary enclave hardening technique that is especially useful against unpredictable information leakage

Automatic programming methodologies for electronic hardware fault monitoring

This paper presents three variants of Genetic Programming (GP) approaches for intelligent online performance monitoring of electronic circuits and systems. Reliability modeling of electronic circuits can be best performed by the Stressor - susceptibility interaction model. A circuit or a system is considered to be failed once the stressor has exceeded the susceptibility limits. For on-line prediction, validated stressor vectors may be obtained by direct measurements or sensors, which after pre-processing and standardization are fed into the GP models. Empirical results are compared with artificial neural networks trained using backpropagation algorithm and classification and regression trees. The performance of the proposed method is evaluated by comparing the experiment results with the actual failure model values. The developed model reveals that GP could play an important role for future fault monitoring systems.This research was supported by the International Joint Research Grant of the IITA (Institute of Information Technology Assessment) foreign professor invitation program of the MIC (Ministry of Information and Communication), Korea