A STATISTICAL SEARCH ON CONVERTED GEOGRAPHICAL DATA

More specifically, you can expand and encrypt past searches, especially dealing with system comparisons or encrypting the save command, to allow the parallel rectangle range to explore spatial data. An information analyst can study the ability of social achievement according to the site's record for countless users by evaluating multiple forms of circular domain queries. Although most search-based file encryption systems focus on common SQL queries, for example, keyword queries and logical queries, some investigations have specifically investigated geometric range via encrypted spatial data. Our main contributions are the fact that our design is indeed a general approach, which can support several types of engineering term queries. None of these previous works have been studied in special engineering queries that are expressed as triangles or rectangles that are not parallel to the axis. With the rapid development of social systems, location-based services and travel on a laptop, the amount of data people creates each day continues to grow exponentially. It is no longer easy or perhaps profitable for companies to maintain a large amount of data in their area. More importantly, the general approach still does not exist, which can flexibly and securely support various types of geometric field queries on encrypted spatial data, regardless of their specific geometric shapes. Our design has great potential for use and is implemented in extensive applications, for example, location-based services and spatial databases, requiring the use of confidential spatial data based on a strong privacy guarantee

Probing protein sequences as sources for encrypted antimicrobial peptides

Starting from the premise that a wealth of potentially biologically active peptides may lurk within proteins, we describe here a methodology to identify putative antimicrobial peptides encrypted in protein sequences. Candidate peptides were identified using a new screening procedure based on physicochemical criteria to reveal matching peptides within protein databases. Fifteen such peptides, along with a range of natural antimicrobial peptides, were examined using DSC and CD to characterize their interaction with phospholipid membranes. Principal component analysis of DSC data shows that the investigated peptides group according to their effects on the main phase transition of phospholipid vesicles, and that these effects correlate both to antimicrobial activity and to the changes in peptide secondary structure. Consequently, we have been able to identify novel antimicrobial peptides from larger proteins not hitherto associated with such activity, mimicking endogenous and/or exogenous microorganism enzymatic processing of parent proteins to smaller bioactive molecules. A biotechnological application for this methodology is explored. Soybean (Glycine max) plants, transformed to include a putative antimicrobial protein fragment encoded in its own genome were tested for tolerance against Phakopsora pachyrhizi, the causative agent of the Asian soybean rust. This procedure may represent an inventive alternative to the transgenic technology, since the genetic material to be used belongs to the host organism and not to exogenous sources

Roadmap on optical security

Postprint (author's final draft

Practical and Secure Circular Range Search on Private Spatial Data

With the location-based services (LBS) booming, the volume of spatial data inevitably explodes. In order to reduce local storage and computational overhead, users tend to outsource data and initiate queries to the cloud. However, sensitive data or queries may be compromised if cloud server has access to raw data and plaintext token. To cope with this problem, searchable encryption for geometric range is applied. Geometric range search has wide applications in many scenarios, especially the circular range search. In this paper, a practical and secure circular range search scheme (PSCS) is proposed to support searching for spatial data in a circular range. With our scheme, a semi-honest cloud server will return data for a given circular range correctly without uncovering index privacy or query privacy. We propose a polynomial split algorithm which can decompose the inner product calculation neatly. Then, we define the security of our PSCS formally and prove that it is secure under same-closeness-pattern chosen-plaintext attacks (CLS-CPA) in theory. In addition, we demonstrate the efficiency and accuracy through analysis and experiments compared with existing schemes