Get an update on changes of the IACR web-page here. For questions, contact newsletter (at) iacr.org. You can also receive updates via:
To receive your credentials via mail again, please click here.
You can also access the full news archive.
In 2014, IACR started to sponsor a small number of Cryptology Schools providing intensive training on clearly identified topics in cryptology. The aim of this program is to develop awareness and increased capacity for research in cryptology.
A Cryptology School is typically held full-time for 4-5 days of intensive learning and constitutes an efficient way to provide high-quality training for graduate students, as well as for professionals. Attendance should be open to anyone who is interested and qualified. In order to facilitate learning, a school is usually taught by a few domain experts with a focus on educating the audience rather than impressing with results. In line with the mission of IACR, a Cryptology School should enable the audience to advance the theory and practice of cryptology and related fields.
There are two rounds of submissions every year. The submission deadlines are:
For more information about this new program and how to prepare a proposal, please refer to http://www.iacr.org/schools/
In this paper, we propose a different approach to outsourcing computational tasks. We are not concerned with hiding the job or the data, but our main task is to ensure that the job is computed correctly. We also observe that not all contractors are malicious; rather, majority are rational. Thus, our approach brings together elements from cryptography, as well as game theory and mechanism design. We achieve the following results: (1) We incentivize all the rational contractors to perform the outsourced job correctly, (2) we guarantee high fraction (e.g., 99.9%) of correct results even in the existence of a relatively large fraction (e.g., 33%) of malicious irrational contractors in the system, (3) and we show that our system achieves these while being almost as efficient as running the job locally (e.g., with only 3% overhead). Such a high correctness guarantee was not known to be achieved with such efficiency.