ON BINARY SIMILARITY MEASURES FOR PRIVACY-PRESERVING TOP-N RECOMMENDATIONS

2010 ◽  
Keyword(s):  
Similarity Measures ◽  
Privacy Preserving ◽  
Binary Similarity Measures

scholarly journals PRIVACY PRESERVING CLUSTERING BASED ON LINEAR APPROXIMATION OF FUNCTION

2013 ◽  
Vol 12 (5) ◽  
pp. 3443-3451
Author(s):  
Rajesh Pasupuleti ◽  
Narsimha Gugulothu
Keyword(s):  
Linear Approximation ◽  
Clustering Algorithms ◽  
Similarity Measures ◽  
Privacy Preserving ◽  
Distance Measures ◽  
Clustering Methods ◽  
Sensitive Data ◽  
Processing Information ◽  
Data Objects ◽  
Approximation Of Function

Clustering analysis initiatives  a new direction in data mining that has major impact in various domains including machine learning, pattern recognition, image processing, information retrieval and bioinformatics. Current clustering techniques address some of the  requirements not adequately and failed in standardizing clustering algorithms to support for all real applications. Many clustering methods mostly depend on user specified parametric methods and initial seeds of clusters are randomly selected by  user.  In this paper, we proposed new clustering method based on linear approximation of function by getting over all idea of behavior knowledge of clustering function, then pick the initial seeds of clusters as the points on linear approximation line and perform clustering operations, unlike grouping data objects into clusters by using distance measures, similarity measures and statistical distributions in traditional clustering methods. We have shown experimental results as clusters based on linear approximation yields good  results in practice with an example of  business data are provided.  It also  explains privacy preserving clusters of sensitive data objects.

scholarly journals Improved binary similarity measures for software modularization

2017 ◽  
Vol 18 (8) ◽  
pp. 1082-1107 ◽  
Author(s):  
Rashid Naseem ◽  
Mustafa Bin Mat Deris ◽  
Onaiza Maqbool ◽  
Jing-peng Li ◽  
Sara Shahzad ◽  
...  
Keyword(s):  
Similarity Measures ◽  
Software Modularization ◽  
Binary Similarity Measures

scholarly journals Image Steganalysis with Binary Similarity Measures

2005 ◽  
Vol 2005 (17) ◽  
Author(s):  
İsmail Avcıbaş ◽  
Mehdi Kharrazi ◽  
Nasir Memon ◽  
Bülent Sankur
Keyword(s):  
Similarity Measures ◽  
Image Steganalysis ◽  
Binary Similarity Measures

scholarly journals Analisis Perbandingan Ketahanan Metode Steganografi LSB dan BPCS Menggunakan Metode Steganalisis Binary Similarity Measures

2012 ◽  
Vol 3 (1) ◽  
Author(s):  
Ngurah Agus Sanjaya ER ◽  
I Putu Edy Suardiyana Putra
Keyword(s):  
Detection Probability ◽  
Similarity Measures ◽  
Test Results ◽  
Least Significant Bit ◽  
Bit Plane ◽  
Binary Similarity Measures

Abstract. Least significant bit (LSB) and Bit Plane Complexity Segmentation (BPCS) are two of the most commonly used steganoraphy methods. LSB is relatively simple and can be quickly implemented while BPCS offers an advantage in the capacity of storing hidden messages. These two methods are considered good if and only if the hidden messages in each of them are robust from a steganalysis implementation. This research specifically performs the robustness checks for both methods by using the Binary Similarity Measures (BSM). BSM measures the correlations between bits in a bit-plane to detect the message hidden in an image. Our test results show that the larger the size of the message hidden by using the BPCS method, the smaller is its detection probability. On the contrary, the size of the hidden message is directly proportional to its probability of being discovered in the LSB method. Keywords: steganography, Least Significant Bit, Bit Plane Complexity Segmentation, steganalysis, Binary Similarity Measures Abstrak. Least Significant Bit (LSB) dan Bit Plane Complexity Segmentation (BPCS) merupakan dua metode steganografi yang umum digunakan. LSB dapat diimplementasikan secara cepat dan sederhana sedangkan BPCS menawarkan kelebihan dalam penampungan kapasitas pesan rahasia. Agar dapat dikatakan sebagai metode steganografi yang baik maka kedua metode tersebut harus dapat mempertahankan pesan yang disisipkan dari serangan metode steganalisis. Penelitian yang dilakukan bertujuan untuk mengetahui ketahanan dari masing-masing metode menggunakan metode steganalisis Binary Similarity Measures (BSM). BSM mengukur korelasi antar bit-bit dalam suatu bit-plane untuk mengetahui keberadaan pesan pada citra. Hasil penelitian mengungkapkan bahwa semakin besar pesan yang disisipkan pada suatu citra menggunakan metode BPCS, maka kemungkinan terdeteksinya pesan akan berkurang. Hal ini berbanding terbalik dengan metode LSB dimana ukuran pesan yang disisipkan berbanding lurus dengan kemungkinan terdeteksinya pesan tersebut.Kata Kunci: Steganografi, Least Significant Bit, Bit Plane Complexity Segmentation, Steganalisis, Binary Similarity Measures

scholarly journals Binary similarity measures for fingerprint analysis of qualitative metabolomic profiles

Metabolomics ◽  
2018 ◽  
Vol 14 (3) ◽  
Author(s):  
Anita Rácz ◽  
Filip Andrić ◽  
Dávid Bajusz ◽  
Károly Héberger
Keyword(s):  
Similarity Measures ◽  
Fingerprint Analysis ◽  
Binary Similarity Measures
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