The widespread use of the Internet of Things (IoT) has raised many concerns, including the protection of private information. Existing privacy preservation methods cannot provide a good balance between data utility and privacy, and also have problems with efficiency and scalability. This paper proposes an efficient data stream perturbation method (named as P 2 RoCAl). P 2 RoCAl offers better data utility than similar methods: classification accuracies of P 2 RoCAl perturbed data streams are very close to those of the original data streams. P 2 RoCAl also provides higher resilience against data reconstruction attacks.

Diagnosis of dermatophytosis employing conventional laboratory procedures has been complicated by the slow growth and varied morphological features shown by dermatophytes. After analysis of the nucleotide base sequences of a 1.2-kb fragment ampli®ed from a dermatophyte fungus Trichophyton rubrum by arbitrarily primed PCR with random primer OPD18, a pair of primers (TR1F and TR1R) was designed and evaluated for speci®c identi®cation of T. rubrum. The sensitivity of the primers TR1F and TR1R was high, as a speci®c PCR band of c. 600 bp was detected from as little as 7 pg of T. rubrum DNA. By examining 92 dermatophyte strains and clinical isolates, it was found that this pair of primers reacted in PCR with T. rubrum, T. soudanense and T. gourvilii through formation of the speci®c fragment of 600 bp, but not with any other of the dermatophyte species or varieties, fungi, yeasts or bacteria tested. As T. rubrum is one of the most frequently isolated dermatophyte fungi, and T. soudanense and T. gourvilii are relatively uncommon in many parts of the world, these primers can be used for rapid, sensitive and speci®c identi®cation and differentiation of T. rubrum from other fungi and micro-organisms.

No abstract