Origin authentication of distillers' dried grains and solubles (DDGS) - Application and comparison of different analytical strategies

In the context of products from certain regions or countries being banned because of an identified or non-identified hazard, proof of geographical origin is essential with regard to feed and food safety issues. Usually, the product labeling of an affected feed lot shows origin, and the paper documentation shows traceability. Incorrect product labeling is common in embargo situations, however, and alternative analytical strategies for controlling feed authenticity are therefore needed. In this study, distillers' dried grains and solubles (DDGS) were chosen as the product on which to base a comparison of analytical strategies aimed at identifying the most appropriate one. Various analytical techniques were investigated for their ability to authenticate DDGS, including spectroscopic and spectrometric techniques combined with multivariate data analysis, as well as proven techniques for authenticating food, such as DNA analysis and stable isotope ratio analysis. An external validation procedure (called the system challenge) was used to analyze sample sets blind and to compare analytical techniques. All the techniques were adapted so as to be applicable to the DDGS matrix. They produced positive results in determining the botanical origin of DDGS (corn vs. wheat), and several of them were able to determine the geographical origin of the DDGS in the sample set. The maintenance and extension of the databanks generated in this study through the analysis of new authentic samples from a single location are essential in order to monitor developments and processing that could affect authentication.

Discrimination of honey of different floral origins by a combination of various chemical parameters

Abstract Honey is a high value food commodity with recognized nutraceutical properties. A primary driver of the value of honey is its floral origin. The feasibility of applying multivariate data analysis to various chemical parameters for the discrimination of honeys was explored. This approach was applied to four authentic honeys with different floral origins (rata, kamahi, clover and manuka) obtained from producers in New Zealand. Results from elemental profiling, stable isotope analysis, metabolomics (UPLC-QToF MS), and NIR, FT-IR, and Raman spectroscopic fingerprinting were analyzed. Orthogonal partial least square discriminant analysis (OPLS-DA) was used to determine which technique or combination of techniques provided the best classification and prediction abilities. Good prediction values were achieved using metabolite data (for all four honeys, Q² = 0.52; for manuka and clover, Q² = 0.76) and the trace element/isotopic data (for manuka and clover, Q² = 0.65), while the other chemical parameters showed promise when combined (for manuka and clover, Q² = 0.43).

A secure authentication and key management scheme for Wireless Sensors Network

In recent years, the adaptation of Wireless Sensor Networks (WSNs) to application areas requiring mobility increased the security threats against confidentiality, integrity and privacy of the information as well as against their connectivity. Since, key management plays an important role in securing both information and connectivity, a proper authentication and key management scheme is required in mobility enabled applications where the authentication of a node with the network is a critical issue. In this paper, we present an authentication and key management scheme supporting node mobility in a heterogeneous WSN that consists of several low capabilities sensor nodes and few high capabilities sensor nodes. We analyze our proposed solution by using MATLAB (analytically) and by simulation (OMNET++ simulator) to show that it has less memory requirement and has good network connectivity and resilience against attacks compared to some existing schemes. We also propose two levels of secure authentication methods for the mobile sensor nodes for secure authentication and key establishment.

Fuzzy logic-based implicit authentication for mobile access control

In order to address the increasing compromise of user privacy on mobile devices, a Fuzzy Logic based implicit authentication scheme is proposed in this paper. The proposed scheme computes an aggregate score based on selected features and a threshold in real-time based on current and historic data depicting user routine. The tuned fuzzy system is then applied to the aggregated score and the threshold to determine the trust level of the current user. The proposed fuzzy-integrated implicit authentication scheme is designed to: operate adaptively and completely in the background, require minimal training period, enable high system accuracy while provide timely detection of abnormal activity. In this paper, we explore Fuzzy Logic based authentication in depth. Gaussian and triangle-based membership functions are investigated and compared using real data over several weeks from different Android phone users. The presented results show that our proposed Fuzzy Logic approach is a highly effective, and viable scheme for lightweight real-time implicit authentication on mobile devices.