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Cryptography Based Dynamic Multi-Keyword Ranked Search Using ECC/B+TRE
Prasanna B T,C B Akki 보안공학연구지원센터 2015 International Journal of Security and Its Applicat Vol.9 No.11
Today, Cloud computing is becoming a household technology. In cloud, a shared pool of computing resources can be accessed on demand through internet and web applications. Since outsourced data is in third party premises i.e. cloud, accountability of user data is paramount. To preserve privacy and security of user data in cloud, many cryptographic techniques have been proposed by many scientists. One among them is searchable encryption. Searchable encryption allows secure search over encrypted data. In our system, a noble approach has been made using the Elliptic Curve Cryptography (ECC), a cryptographic techniques to reduce the overall computation overhead. Dynamic B+ tree data structure is used to perform multi-keyword search over the encrypted data. To retrieve appropriate data files, ranking will be done based on relevance score. Finally, we compare the effectiveness and efficiency of our proposed scheme with our previous work on CRSA/B+ tree through extensive experimental evaluation using Microsoft azure platform.
A 32 ㎚ NPN SOI HBT with Programmable Power Gain and 839 ㎓V f<SUB>t</SUB>BV<SUB>CEO</SUB> Product
Prasanna Kumar Misra,S. Qureshi 대한전자공학회 2014 Journal of semiconductor technology and science Vol.14 No.6
The performance of npn SiGe HBT on thin film SOI is investigated at 32 ㎚ technology node by applying body bias. An n-well is created underneath thin BOX to isolate the body biased SOI HBT from SOI CMOS. The results show that the HBT voltage gain and power gain can be programmed by applying body bias to the n-well. This HBT can be used in variable gain amplifiers that are widely used in the receiver chain of RF systems. The HBT is compatible with 32 ㎚ FDSOI technology having 10 ㎚ film thickness and 30 ㎚ BOX thickness. As the breakdown voltage increases by applying the body bias, the SOI HBT with 3 V VCE has very high ftBVCEO product (839 ㎓V). The self heating performance of the proposed SOI HBT is studied. The high voltage gain and power gain (60 ㏈) of this HBT will be useful in designing analog/RF systems which cannot be achieved using 32 ㎚ SOI CMOS (usually voltage gain is in the range of 10-20 ㏈).
Prasanna Kumar Misra,S. Qureshi 대한전자공학회 2014 Journal of semiconductor technology and science Vol.14 No.3
In this paper, the epi layer of npn SOI HBT with n+ buried layer has been studied through Sentaurus process and device simulator. The doping value of the deposited epi layer has been varied for the npn HBT to achieve improved ftBVCEO product (397 GHzV). As the BVCEO value is higher for low value of epi layer doping, higher supply voltage can be used to increase the ft value of the HBT. At 1.8 V VCE, the ftBVCEO product of HBT is 465.5 GHzV. Further, the film thickness of the epi layer of the SOI HBT has been scaled for better performance (426.8 GHzV ftBVCEO product at 1.2 V VCE). The addition of this HBT module to fully depleted SOI CMOS technology would provide better solution for realizing wireless circuits and systems for 60 GHz short range communication and 77 GHz automotive radar applications. This SOI HBT together with SOI CMOS has potential for future high performance SOI BiCMOS technology.
A 32 nm NPN SOI HBT with Programmable Power Gain and 839 GHzV ftBVCEO Product
Prasanna Kumar Misra,S. Qureshi 대한전자공학회 2014 Journal of semiconductor technology and science Vol.14 No.6
The performance of npn SiGe HBT on thin film SOI is investigated at 32 nm technology node by applying body bias. An n-well is created underneath thin BOX to isolate the body biased SOI HBT from SOI CMOS. The results show that the HBT voltage gain and power gain can be programmed by applying body bias to the n-well. This HBT can be used in variable gain amplifiers that are widely used in the receiver chain of RF systems. The HBT is compatible with 32 nm FDSOI technology having 10 nm film thickness and 30 nm BOX thickness. As the breakdown voltage increases by applying the body bias, the SOI HBT with 3 V VCE has very high ftBVCEO product (839 GHzV). The self heating performance of the proposed SOI HBT is studied. The high voltage gain and power gain (60 dB) of this HBT will be useful in designing analog/RF systems which cannot be achieved using 32 nm SOI CMOS (usually voltage gain is in the range of 10-20 dB).
Multi Label Deep Learning classification approach for False Data Injection Attacks in Smart Grid
( Prasanna Srinivasan. V ),( Balasubadra. K ),( Saravanan. K ),( Arjun. V. S ),( Malarkodi. S ) 한국인터넷정보학회 2021 KSII Transactions on Internet and Information Syst Vol.15 No.6
The smart grid replaces the traditional power structure with information inventiveness that contributes to a new physical structure. In such a field, malicious information injection can potentially lead to extreme results. Incorrect, FDI attacks will never be identified by typical residual techniques for false data identification. Most of the work on the detection of FDI attacks is based on the linearized power system model DC and does not detect attacks from the AC model. Also, the overwhelming majority of current FDIA recognition approaches focus on FDIA, whilst significant injection location data cannot be achieved. Building on the continuous developments in deep learning, we propose a Deep Learning based Locational Detection technique to continuously recognize the specific areas of FDIA. In the development area solver gap happiness is a False Data Detector (FDD) that incorporates a Convolutional Neural Network (CNN). The FDD is established enough to catch the fake information. As a multi-label classifier, the following CNN is utilized to evaluate the irregularity and cooccurrence dependency of power flow calculations due to the possible attacks. There are no earlier statistical assumptions in the architecture proposed, as they are "model-free." It is also "cost-accommodating" since it does not alter the current FDD framework and it is only several microseconds on a household computer during the identification procedure. We have shown that ANN-MLP, SVM-RBF, and CNN can conduct locational detection under different noise and attack circumstances through broad experience in IEEE 14, 30, 57, and 118 bus systems. Moreover, the multi-name classification method used successfully improves the precision of the present identification.
Development of daily gridded rainfall dataset over the Ganga, Brahmaputra and Meghna river basins
Prasanna, Venkatraman,Subere, Juvy,Das, Dwijendra K.,Govindarajan, Srinivasan,Yasunari, Tetsuzo John Wiley Sons, Ltd 2014 Meteorological applications Vol.21 No.2
<P><B>Abstract</B></P><P>The India Meteorological Department (IMD) gridded rainfall dataset, the 47 Bangladesh gauge rainfall observations and the Tropical Rainfall Measuring Mission (TRMM) 3B42V6 satellite data are used in the present analysis. The nearest neighbour interpolation scheme is used, wherein the interpolated values are computed from a weighted sum of observations. The Bangladesh daily gauge measured rainfall is interpolated into regular grids of 0.5° × 0.5° resolution every day from January 1988 to December 2007 and appended with the daily gridded dataset of the IMD over the Indian region. A similar resolution dataset of 0.5° × 0.5° for the TRMM‐3B42V6 data from January 1998 to December 2007 is created from the original data of 0.25° × 0.25° resolution. To produce a merged rainfall product, all the gridded datasets are merged. The merging of datasets is done in such a way as to include the highest rainfall at each grid point from the three products. Based on the three available sets of daily observations (IMD dataset (1° × 1°), TRMM‐3B42 (0.25° × 0.25°) and 46 daily station observations over Bangladesh), a dataset of 0.5° × 0.5° resolution on a daily scale is generated. The focus of this study is to compare the TRMM‐3B42V6 rainfall data over the Ganga, Brahmaputra and Meghna (GBM) domain with observed point gauge data, and assess the possibility of using them for application in real time flood forecasting as well as to serve as a comparison tool for the baseline simulation of high resolution atmospheric models aimed at flood forecasting and climate change projections. Copyright © 2012 Royal Meteorological Society</P>
Prasanna Vadhanan 대한치과마취과학회 2022 Journal of Dental Anesthesia and Pain Medicine Vol.22 No.1
Persistent idiopathic facial pain is a rare and difficult condition to treat. Several pharmacological, non- pharmacological, and invasive treatment options have been used, with varying results. We report the case of a patient with intractable persistent idiopathic facial pain who responded favorably to a combination of botulinum toxin injections and pulsed radiofrequency treatment of the infraorbital nerve.