Secure Pick Up: Implicit Authentication When You Start Using the Smartphone

We propose Secure Pick Up (SPU), a convenient, lightweight, in-device, non-intrusive and automatic-learning system for smartphone user authentication. Operating in the background, our system implicitly observes users' phone pick-up movements, the way they bend their arms when they pick up a smartphone to interact with the device, to authenticate the users. Our SPU outperforms the state-of-the-art implicit authentication mechanisms in three main aspects: 1) SPU automatically learns the user's behavioral pattern without requiring a large amount of training data (especially those of other users) as previous methods did, making it more deployable. Towards this end, we propose a weighted multi-dimensional Dynamic Time Warping (DTW) algorithm to effectively quantify similarities between users' pick-up movements; 2) SPU does not rely on a remote server for providing further computational power, making SPU efficient and usable even without network access; and 3) our system can adaptively update a user's authentication model to accommodate user's behavioral drift over time with negligible overhead. Through extensive experiments on real world datasets, we demonstrate that SPU can achieve authentication accuracy up to 96.3% with a very low latency of 2.4 milliseconds. It reduces the number of times a user has to do explicit authentication by 32.9%, while effectively defending against various attacks.Comment: Published on ACM Symposium on Access Control Models and Technologies (SACMAT) 201

Pb2+, Cu2+, Zn2+, Mg2+ and Mn2+ reduce the affinities of flavone, genistein and kaempferol for human serum albumin in vitro

Flavone (Fl), genistein (Gen) and kaempferol (Kol) were studied for their affinities towards human serum albumin (HSA) in the presence and absence of Pb2+,Cu2+,Zn2+,Mg2+ and Mn2+. The fluorescence intensities of HSA decreased with increasing concentration of the three flavonoids. Kaempferol resulted in a blue-shift of the λem of HSA from 336 to 330 nm; flavone showed an obvious red-shift of the λem of HSA from 336 to 342 nm; genistein did not cause an obvious blue-shift or red-shift of the λem of HSA. However, the extents of λem-shifts induced by the flavonoids in the presence of metal ions were much bigger than that in the absence of mental ions. Pb2+,Cu2+,Zn2+,Mg2+ and Mn2+ reduced the quenching constants of the flavonoids for HSA by 14.6% to 60.7% , 28% to 67.9%,3.5% to 59.4%, 23.2% to 63.7% and 14% to 65%, respectively. The affinities of flavone, genistein and kaempferol for HSA decreased about 10.84%, 10.05%and 3.56% in the presence of Pb2+, respectively. Cu2+ decreased the affinities of flavone, genistein and kaempferol for HSA about 14.04%, 5.14%and 8.89%, respectively. Zn2+ decreased the affinities of flavone, genistein and kaempferol for HSA about 3.79%, 0.55% and 3.58%, respectively. Mg2+ decreased the affinities of flavone, genistein and kaempferol for HSA about 16.94%, 2.94%and 7.04%, respectively. Mn2+ decreased the affinities of flavone, genistein and kaempferol for HSA about 14.24%, 3.66% and 4.78%, respectively

Relation of Dietary Carbohydrates Intake to Circulating Sex Hormone-binding Globulin Levels in Postmenopausal Women

Background Low circulating levels of sex hormone‐binding globulin (SHBG) have been shown to be a direct and strong risk factor for type 2 diabetes, cardiovascular diseases, and hormone‐dependent cancers, although the relationship between various aspects of dietary carbohydrates and SHBG levels remains unexplored in population studies. Methods Among postmenopausal women with available SHBG measurements at baseline (n = 11 159) in the Women's Health Initiative, a comprehensive assessment was conducted of total dietary carbohydrates, glycemic load (GL), glycemic index (GI), fiber, sugar, and various carbohydrate‐abundant foods in relation to circulating SHBG levels using multiple linear regressions adjusting for potential covariates. Linear trend was tested across quartiles of dietary variables. Benjamini and Hochberg's procedure was used to calculate the false discovery rate for multiple comparisons. Results Higher dietary GL and GI (both based on total and available carbohydrates) and a higher intake of sugar and sugar‐sweetened beverages were associated with lower circulating SHBG concentrations (all P trend < 0.05; Q ‐values = 0.04,0.01, 0.07, 0.10, 0.01, and <0.0001, respectively). In contrast, women with a greater intake of dietary fiber tended to have elevated SHBG levels (P trend = 0.01, Q ‐value = 0.04). There was no significant association between total carbohydrates or other carbohydrate‐abundant foods and SHBG concentrations. Conclusions The findings suggest that low GL or GI diets with low sugar and high fiber content may be associated with higher serum SHBG concentrations among postmenopausal women. Future studies investigating whether lower GL or GI diets increase SHBG concentrations are warranted

Herb Target Prediction Based on Representation Learning of Symptom related Heterogeneous Network.

Traditional Chinese Medicine (TCM) has received increasing attention as a complementary approach or alternative to modern medicine. However, experimental methods for identifying novel targets of TCM herbs heavily relied on the current available herb-compound-target relationships. In this work, we present an Herb-Target Interaction Network (HTINet) approach, a novel network integration pipeline for herb-target prediction mainly relying on the symptom related associations. HTINet focuses on capturing the low-dimensional feature vectors for both herbs and proteins by network embedding, which incorporate the topological properties of nodes across multi-layered heterogeneous network, and then performs supervised learning based on these low-dimensional feature representations. HTINet obtains performance improvement over a well-established random walk based herb-target prediction method. Furthermore, we have manually validated several predicted herb-target interactions from independent literatures. These results indicate that HTINet can be used to integrate heterogeneous information to predict novel herb-target interactions