Secure Outsourced Computation on Encrypted Data

Homomorphic encryption (HE) is a promising cryptographic technique that supports computations on encrypted data without requiring decryption first. This ability allows sensitive data, such as genomic, financial, or location data, to be outsourced for evaluation in a resourceful third-party such as the cloud without compromising data privacy. Basic homomorphic primitives support addition and multiplication on ciphertexts. These primitives can be utilized to represent essential computations, such as logic gates, which subsequently can support more complex functions. We propose the construction of efficient cryptographic protocols as building blocks (e.g., equality, comparison, and counting) that are commonly used in data analytics and machine learning. We explore the use of these building blocks in two privacy-preserving applications. One application leverages our secure prefix matching algorithm, which builds on top of the equality operation, to process geospatial queries on encrypted locations. The other applies our secure comparison protocol to perform conditional branching in private evaluation of decision trees. There are many outsourced computations that require joint evaluation on private data owned by multiple parties. For example, Genome-Wide Association Study (GWAS) is becoming feasible because of the recent advances of genome sequencing technology. Due to the sensitivity of genomic data, this data is encrypted using different keys possessed by different data owners. Computing on ciphertexts encrypted with multiple keys is a non-trivial task. Current solutions often require a joint key setup before any computation such as in threshold HE or incur large ciphertext size (at best, grows linearly in the number of involved keys) such as in multi-key HE. We propose a hybrid approach that combines the advantages of threshold and multi-key HE to support computations on ciphertexts encrypted with different keys while vastly reducing ciphertext size. Moreover, we propose the SparkFHE framework to support large-scale secure data analytics in the Cloud. SparkFHE integrates Apache Spark with Fully HE to support secure distributed data analytics and machine learning and make two novel contributions: (1) enabling Spark to perform efficient computation on large datasets while preserving user privacy, and (2) accelerating intensive homomorphic computation through parallelization of tasks across clusters of computing nodes. To our best knowledge, SparkFHE is the first addressing these two needs simultaneously

CHARACTERIZING dsRNA PRODUCTION IN VIRUS-INFECTED FISH CELLS

Viral dsRNA is produced by almost all viruses sometime during their replicative cycle. These viral nucleic acids are potent inducers of both innate and adaptive immune responses, and are therefore considered important immuno-modulators. Previous studies have shown that viruses produce dsRNA when replicating in mammalian cells; however, to date no one has demonstrated viral dsRNA production in virus infected fish cells. Therefore, the goal of this study is to investigate dsRNA production by fish viruses in fish cells, verifying production and performing initial characterization of the dsRNA molecules being produced. Three different rainbow trout cell lines were used in this study: rainbow trout gill (RTgill-W1, epithelial), rainbow trout gut (RTgutGC, epithelial) and rainbow trout gonad (RTG-2, fibroblast). These cell lines were selected because innate immune responses are relatively well characterized in RTG-2; while RTgill and RTgut represent two tissues that would be first to ‘see’ a virus infection in vivo. The study also includes three different fish viruses: viral haemorrhagic septicaemia virus (VHSV), which has a negative sense single stranded RNA (-ssRNA) genome, chum salmon reovirus (CSV), which has a double stranded RNA (dsRNA) genome, and frog virus3 (FV3), which has a dsDNA genome. These viruses were selected because they have different genomes and thus different replication cycles, which is important for verifying dsRNA production is not specific to one virus genome type. dsRNA production was measured using immunofluorescence, a technique which relies on J2, a mouse anti-dsRNA antibody. Not only does immunofluorescence with J2 verify that fish viruses produce dsRNA in fish cells, but it also indicates the location of dsRNA production within the cell. An acridine orange stain was also performed to indicate the relative amount of dsRNA produced during a virus infection as well as the length of the dsRNA molecules to provide further evidence for dsRNA production by fish viruses in fish cells using an antibody-independent method. Because dsRNA is an important immuno-modulator, it has possible applications as a novel adjuvant for vaccines or as an antiviral therapy. The results from this study are important not only because it contributes to a better understanding of virus-host interactions, but characterizing viral dsRNA in fish cells could provide basic research evidence on which to build novel dsRNA-based therapies in fish

A Cognitive Theory-based Approach for the Evaluation and Enhancement of Internet Security Awareness among Children Aged 3-12 Years

In the age of technology, the Internet has spread widely and used for multiple purposes by users of all ages, especially children who start using it frequently to play in their spare time. With the use of the Internet, children must have a sufficient security awareness to avoid security risks found online. This study takes us through the journey of evaluating and enhancing the level of the Internet security awareness among a group of Saudi children aged 3-12 years. The developed evaluation survey shows that there is some awareness among the Saudi Children; however, they still need more concrete ways of ensuring secure practices as they showed a poor knowledge of proper Internet security practices in areas such as interacting with anonymous advertisements as well as understanding some of the Internet Security symbols. The study also presents a suggested Awareness Enhancement solution to raise the security awareness among children. The solution’s design takes into consideration the Piaget’s theory of children’s cognitive development, which states that children in different age groups have different perceptual and learning abilities. The test of the suggested solution shows a significant increase in the sample’s Internet security level. The work of this study emphasizes on the importance of targeting the Saudi children with interactive training sessions to raise their Internet security awareness level

Fast design space exploration of vibration-based energy harvesting wireless sensors

An energy-harvester-powered wireless sensor node is a complicated system with many design parameters. To investigate the various trade-offs among these parameters, it is desirable to explore the multi-dimensional design space quickly. However, due to the large number of parameters and costly simulation CPU times, it is often difficult or even impossible to explore the design space via simulation. This paper presents a response surface model (RSM) based technique for fast design space exploration of a complete wireless sensor node powered by a tunable energy harvester. As a proof of concept, a software toolkit has been developed which implements the proposed design flow and incorporates either real data or parametrized models of the vibration source, the energy harvester, tuning controller and wireless sensor node. Several test scenarios are considered, which illustrate how the proposed approach permits the designer to adjust a wide range of system parameters and evaluate the effect almost instantly but still with high accuracy. In the developed toolkit, the estimated CPU time of one RSM estimation is 25s and the average RSM estimation error is less than 16.5