scholarly journals Obfuscated Access and Search Patterns in Searchable Encryption

Author(s):  
Zhiwei Shang ◽  
Simon Oya ◽  
Andreas Peter ◽  
Florian Kerschbaum
2021 ◽  
Vol 115 ◽  
pp. 102006
Author(s):  
Yanping Li ◽  
Qiang Cao ◽  
Kai Zhang ◽  
Fang Ren

2021 ◽  
Author(s):  
Hong Liu ◽  
Xueqin Li ◽  
Erchuan Guo ◽  
Yunpeng Xiao ◽  
Tun Li

Abstract Dynamic searchable encryption methods allow a client to perform searches and updates over encrypted data stored in the cloud. However, existing researches show that the general dynamic searchable symmetric encryption (DSSE) scheme is vulnerable to statistical attacks due to the leakage of search patterns and access patterns, which is detrimental to protecting the users’ privacy. Although the traditional Oblivious Random Access Machine (ORAM) can hide the access pattern, it also incurs significant communication overhead and cannot hide the search pattern. These limitations make it difficult to deploy the ORAM method in real cloud environments. To overcome this limitation, a DSSE scheme called obliviously shuffled incidence matrix DSSE (OSM-DSSE) is proposed in this paper to access the encrypted data obliviously. The OSM-DSSE scheme realizes efficient search and update operations based on an incidence matrix. In particular, a shuffling algorithm using Paillier encryption is combined with 1-out-of-n obliviously transfer (OT) protocol and local differential privacy to obfuscate the search targets. Besides, a formalized security analysis and performance analysis on the proposed scheme is provided, which indicates that the OSM-DSSE scheme achieves high security, efficient searches, and low storage overhead. Also, this scheme not only completely hides the search and access patterns but also provides adaptive security against malicious attacks by adversaries. Furthermore, experimental results show that the OSM-DSSE scheme obtains 3-4x better execution efficiency than the state-of-art solutions.


2020 ◽  
Vol 51 (2) ◽  
pp. 479-493
Author(s):  
Jenny A. Roberts ◽  
Evelyn P. Altenberg ◽  
Madison Hunter

Purpose The results of automatic machine scoring of the Index of Productive Syntax from the Computerized Language ANalysis (CLAN) tools of the Child Language Data Exchange System of TalkBank (MacWhinney, 2000) were compared to manual scoring to determine the accuracy of the machine-scored method. Method Twenty transcripts of 10 children from archival data of the Weismer Corpus from the Child Language Data Exchange System at 30 and 42 months were examined. Measures of absolute point difference and point-to-point accuracy were compared, as well as points erroneously given and missed. Two new measures for evaluating automatic scoring of the Index of Productive Syntax were introduced: Machine Item Accuracy (MIA) and Cascade Failure Rate— these measures further analyze points erroneously given and missed. Differences in total scores, subscale scores, and individual structures were also reported. Results Mean absolute point difference between machine and hand scoring was 3.65, point-to-point agreement was 72.6%, and MIA was 74.9%. There were large differences in subscales, with Noun Phrase and Verb Phrase subscales generally providing greater accuracy and agreement than Question/Negation and Sentence Structures subscales. There were significantly more erroneous than missed items in machine scoring, attributed to problems of mistagging of elements, imprecise search patterns, and other errors. Cascade failure resulted in an average of 4.65 points lost per transcript. Conclusions The CLAN program showed relatively inaccurate outcomes in comparison to manual scoring on both traditional and new measures of accuracy. Recommendations for improvement of the program include accounting for second exemplar violations and applying cascaded credit, among other suggestions. It was proposed that research on machine-scored syntax routinely report accuracy measures detailing erroneous and missed scores, including MIA, so that researchers and clinicians are aware of the limitations of a machine-scoring program. Supplemental Material https://doi.org/10.23641/asha.11984364


Aerospace ◽  
2021 ◽  
Vol 8 (7) ◽  
pp. 170
Author(s):  
Ricardo Palma Fraga ◽  
Ziho Kang ◽  
Jerry M. Crutchfield ◽  
Saptarshi Mandal

The role of the en route air traffic control specialist (ATCS) is vital to maintaining safety and efficiency within the National Airspace System (NAS). ATCSs must vigilantly scan the airspace under their control and adjacent airspaces using an En Route Automation Modernization (ERAM) radar display. The intent of this research is to provide an understanding of the expert controller visual search and aircraft conflict mitigation strategies that could be used as scaffolding methods during ATCS training. Interviews and experiments were conducted to elicit visual scanning and conflict mitigation strategies from the retired controllers who were employed as air traffic control instructors. The interview results were characterized and classified using various heuristics. In particular, representative visual scanpaths were identified, which accord with the interview results of the visual search strategies. The highlights of our findings include: (1) participants used systematic search patterns, such as circular, spiral, linear or quadrant-based, to extract operation-relevant information; (2) participants applied an information hierarchy when aircraft information was cognitively processed (altitude -> direction -> speed); (3) altitude or direction changes were generally preferred over speed changes when imminent potential conflicts were mitigated. Potential applications exist in the implementation of the findings into the training curriculum of candidates.


Author(s):  
Chloe Ah-Ryung Lim ◽  
Paris-Ann Ingledew ◽  
Fan Yang ◽  
Brian Thiessen ◽  
Rosemary Cashman ◽  
...  

BMC Neurology ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
John Angelo Luigi S. Perez ◽  
Adrian I. Espiritu ◽  
Roland Dominic G. Jamora

Abstract Background The internet has made significant contributions towards health education. Analyzing the pattern of online behavior regarding meningitis and vaccinations may be worthwhile. It is hypothesized that the online search patterns in meningitis are correlated with its number of cases and the search patterns of its related vaccines. Methods This was an infodemiological study that determined the relationship among online search interest in meningitis, its worldwide number of cases and its associated vaccines. Using Google Trends™ Search Volume Indices (SVIs), we evaluated the search queries “meningitis,” “pneumococcal vaccine,” “BCG vaccine,” “meningococcal vaccine” and “influenza vaccine” in January 2021, covering January 2008 to December 2020. Spearman rank correlation was used to determine correlations between these queries. Results The worldwide search interest in meningitis from 2008 to 2020 showed an average SVI of 46 ± 8.8. The most searched topics were symptoms, vaccines, and infectious agents with SVIs of 100, 52, and 39, respectively. The top three countries with the highest search interest were Ghana, Kazakhstan, and Kenya. There were weak, but statistically significant correlations between meningitis and the BCG (ρ = 0.369, p < 0.001) and meningococcal (ρ = 0.183, p < 0.05) vaccines. There were no statistically significant associations between the number of cases, influenza vaccine, and pneumococcal vaccine. Conclusion The relationships among the Google SVIs for meningitis and its related vaccines and number of cases data were inconsistent and remained unclear. Future infodemiological studies may expand their scopes to social media, semantics, and big data for more robust conclusions.


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