arXiv subjects

Omid Hajihassani

Publications and source records attributed to Omid Hajihassani.

3 recordsLinked to original sources

arXiv2021

Anonymizing Sensor Data on the Edge: A Representation Learning and Transformation Approach

The abundance of data collected by sensors in Internet of Things (IoT) devices, and the success of deep neural networks in uncovering hidden patterns in time series data have led to mounting privacy concerns. This is because private and sensitive information can be potentially learned from sensor data by applications that have access to this data. In this paper, we aim to examine the tradeoff between utility and privacy loss by learning low-dimensional representations that are useful for data obfuscation. We propose deterministic and probabilistic transformations in the latent space of a variational autoencoder to synthesize time series data such that intrusive inferences are prevented while desired inferences can still be made with sufficient accuracy. In the deterministic case, we use a linear transformation to move the representation of input data in the latent space such that the reconstructed data is likely to have the same public attribute but a different private attribute than the original input data. In the probabilistic case, we apply the linear transformation to the latent representation of input data with some probability. We compare our technique with autoencoder-based anonymization techniques and additionally show that it can anonymize data in real time on resource-constrained edge devices.

cs.LG↗

arXiv2019

Generating High Quality Random Numbers: A High Throughput Parallel Bitsliced Approach

In this work, by employing a bitsliced data representation as building blocks of algorithms, we showcase the capability and scalability of our proposed method in a variety of PRNG methods in the category of block and stream ciphers. While demonstrating the suitability of stream-ciphers for high throughput PRNG, as an example, we implement and investigate a bitsliced MICKEY 2.0 PRNG by altering the paradigm of internal functions and data structure. The LFSR-based (Linear Feedback Shift Register) nature of the PRNG in our implementation perfectly suits the GPU's many-core structure due to its register oriented architecture and allows the usage of bit slicing technique to further improve the performance. In our SIMD vectorized fully parallel GPU implementation, each GPU thread is capable of generating a remarkable number of 32 pseudo-random bits in each LFSR clock cycle. We then compare our implementation with some of the most significant PRNGs that display a satisfactory performance in both throughput and randomness criteria. The proposed implementation successfully passes the NIST test for statistical randomness and bit-wise correlation criteria. To the best of authors' best knowledge, our method outperforms the current best implementations in the literature for computer-based PRNG and the optical solutions in terms of performance and performance per cost, while maintaining an acceptable measure of randomness. Our highest performance among all of the implemented CPRNGs with the proposed method is achieved by the MICKEY 2.0 algorithm which shows 1.9x improvement over the state of the art NVIDIA's proprietary high-performance PRNG, cuRAND library, achieving 1.6 Tb/s of throughput on the affordable NVIDIA GTX 980 Ti.

cs.CR↗

arXiv2019

Low-power and Reliable Solid-state Drive with Inverted Limited Weight Coding

In this work, we propose a novel coding scheme which based on the characteristics of NAND flash cells, generates codewords that reduce the energy consumption and improve the reliability of solid-state drives. This novel coding scheme, namely Inverted Limited Weight Coding (ILWC), favors a greater number of '1's appearing in its generated codewords at the cost of added information redundancy, as a form of flag bits. This increase in the number of bits valued as logical '1', in the generated codewords, will increase the number of cells that have lower threshold voltages. Through cells with lower threshold voltages, ILWC fruitfully reduces the SSD's program operation energy consumption. Moreover, it increases the SSD's data retention rate and reliability by decreasing the threshold voltage of the cells. The evaluation of our proposed coding method on three different SSDs, indicates more than 20% reduction in the SSD's program operation energy consumption. In addition, ILWC improves the cells' data retention rate by decreasing their intrinsic electric field by more than 18%. Moreover, the SSD's cell-to-cell coupling noise is diminished with the help of 35% reduction in the worst-case threshold voltage shift in a cell's adjacent cells. All this leads to 5.3% reduction in the MLC's cell error rate. In addition, ILWC achieves 37.5% improvement in the performance of the SSD program operation.

cs.IT↗