The Magic of ELFs

We introduce the notion of an \emph{Extremely Lossy Function} (ELF). An ELF is a family of functions with an image size that is tunable anywhere from injective to having a polynomial-sized image. Moreover, for any efficient adversary, for a sufficiently large polynomial $r$ (necessarily chosen to be larger than the running time of the adversary), the adversary cannot distinguish the injective case from the case of image size $r$. We develop a handful of techniques for using ELFs, and show that such extreme lossiness is useful for instantiating random oracles in several settings. In particular, we show how to use ELFs to build secure point function obfuscation with auxiliary input, as well as polynomially-many hardcore bits for any one-way function. Such applications were previously known from strong knowledge assumptions --- for example polynomially-many hardcore bits were only know from differing inputs obfuscation, a notion whose plausibility has been seriously challenged. We also use ELFs to build a simple hash function with \emph{output intractability}, a new notion we define that may be useful for generating common reference strings. Next, we give a construction of ELFs relying on the \emph{exponential} hardness of the decisional Diffie-Hellman problem, which is plausible in pairing-based groups. Combining with the applications above, our work gives several practical constructions relying on qualitatively different --- and arguably better --- assumptions than prior works

Imagining Oppression in Contemporary Young Adult Fiction

This thesis is a qualitative study of the representation of oppression in contemporary young adult fiction with fantasy, science fiction, dystopian, and speculative elements and themes. This paper identifies a number of themes of the depiction of oppression across these texts and explores how these themes relate to social realities of inequality, race, social change, and activism. The insights and conclusions put forward in this paper are intended to be used by scholars and educators interested in address issues of inequality, oppression, and social change in educational and academic settings

On ELFs, Deterministic Encryption, and Correlated-Input Security

We construct deterministic public key encryption secure for any constant number of arbitrarily correlated computationally unpredictable messages. Prior works required either random oracles or non-standard knowledge assumptions. In contrast, our constructions are based on the exponential hardness of DDH, which is plausible in elliptic curve groups. Our central tool is a new trapdoored extremely lossy function, which modifies extremely lossy functions by adding a trapdoor

Exploiting Hardware Abstraction for Parallel Programming Framework: Platform and Multitasking

With the help of the parallelism provided by the fine-grained architecture, hardware accelerators on Field Programmable Gate Arrays (FPGAs) can significantly improve the performance of many applications. However, designers are required to have excellent hardware programming skills and unique optimization techniques to explore the potential of FPGA resources fully. Intermediate frameworks above hardware circuits are proposed to improve either performance or productivity by leveraging parallel programming models beyond the multi-core era. In this work, we propose the PolyPC (Polymorphic Parallel Computing) framework, which targets enhancing productivity without losing performance. It helps designers develop parallelized applications and implement them on FPGAs. The PolyPC framework implements a custom hardware platform, on which programs written in an OpenCL-like programming model can launch. Additionally, the PolyPC framework extends vendor-provided tools to provide a complete development environment including intermediate software framework, and automatic system builders. Designers\u27 programs can be either synthesized as hardware processing elements (PEs) or compiled to executable files running on software PEs. Benefiting from nontrivial features of re-loadable PEs, and independent group-level schedulers, the multitasking is enabled for both software and hardware PEs to improve the efficiency of utilizing hardware resources. The PolyPC framework is evaluated regarding performance, area efficiency, and multitasking. The results show a maximum 66 times speedup over a dual-core ARM processor and 1043 times speedup over a high-performance MicroBlaze with 125 times of area efficiency. It delivers a significant improvement in response time to high-priority tasks with the priority-aware scheduling. Overheads of multitasking are evaluated to analyze trade-offs. With the help of the design flow, the OpenCL application programs are converted into executables through the front-end source-to-source transformation and back-end synthesis/compilation to run on PEs, and the framework is generated from users\u27 specifications