scholarly journals Hill-Climbing and Brute-Force Attacks on Biometric Systems: A Case Study in Match-on-Card Fingerprint Verification

2006 ◽  
Author(s):  
M. Martinez-Diaz ◽  
J. Fierrez-Aguilar ◽  
F. Alonso-Fernandez ◽  
J. Ortega-Garcia ◽  
J.A. Siguenza
Keyword(s):  
Hill Climbing ◽  
Brute Force ◽  
Fingerprint Verification ◽  
Biometric Systems

scholarly journals Introducing an Educational Tool for Learning Branch & Bound Strategy

2017 ◽  
Vol 3 (1) ◽  
pp. 8 ◽  
Author(s):  
Sofriesilero Zumaytis ◽  
Oscar Karnalim
Keyword(s):  
Qualitative Evaluation ◽  
Performance Comparison ◽  
Brute Force ◽  
Educational Tool ◽  
Breadth First Search ◽  
Cost Matrix ◽  
Algorithm Visualization ◽  
Case Based

Abstract—According to our informal survey, Branch & Bound strategy is considerably difficult to learn compared to other strategies. This strategy consists of several complex algorithmic steps such as Reduced Cost Matrix (RCM) calculation and Breadth First Search. Thus, to help students understanding this strategy, AP-BB, an educational tool for learning Branch & Bound is developed. This tool includes four modules which are Brute Force solving visualization, Branch & Bound solving visualization, RCM calculator, and case-based performance comparison. These modules are expected to enhance student’s understanding about Branch & Bound strategy and its characteristics. Furthermore, our work incorporates TSP as its case study and Brute Force strategy as a baseline to provide a concrete impact of Branch & Bound strategy. According to our qualitative evaluation, AP-BB and all of its features fulfil student necessities for learning Branch & Bound strategy. Keywords— Educational Tool; Branch & Bound; Algorithm Strategy; Algorithm Visualization

scholarly journals Perbandingan Algoritma Boyer-Moore dan Brute Force pada Pencarian Kamus Besar Bahasa Indonesia Berbasis Android

2021 ◽  
Vol 1 (2) ◽  
pp. 54-60
Author(s):  
Candra Irawan ◽  
Mudafiq Riyan Pratama
Keyword(s):  
String Matching ◽  
Search Process ◽  
Brute Force ◽  
Text Search ◽  
Matching Algorithm ◽  
Running Time ◽  
The Right ◽  
Bahasa Indonesia ◽  
Testing Criteria

String matching is an algorithm for matching a text to another text or also known as a text search. There are several algorithms that can be used for string matching, including the Boyer-Moore algorithm and the Brute Force algorithm. The Boyer-Moore algorithm is a string matching algorithm published by Robert S. Boyer and J. Strother Moore in 1977. This algorithm is considered the most efficient algorithm in general applications. The Boyer-Moore algorithm starts matching characters from the pattern on the right. While the Brute Force algorithm is an algorithm that matches a pattern with all text between 0 and n-m to find the existence of a pattern in the text. These two algorithms have different patterns in the search process. In this article, a comparative analysis of the performance of the Boyer-Moore and Brute Force algorithms is carried out in a case study of the search for the Big Indonesian Dictionary (KBBI) based on Android. The search process is carried out by searching based on words and word descriptions. The results of this study indicate that the criteria for running time, the Brute Force algorithm is faster than the Boyer-Moore algorithm with the total running time of the Brute Force algorithm is 168.3 ms in words, 6994.16 ms in word descriptions, while the Boyer-Moore algorithm for running time reached 304.7 ms on the word, 8654.77 ms on the word description. In the testing criteria based on related keywords, the two algorithms can display the same list of related keywords.

scholarly journals Modifikasi Algoritma Steepest-Ascent Hill Climbing Dan Backtracking Untuk Pencarian Lintasan Kritis Proyek

2019 ◽  
Vol 4 (2) ◽  
pp. 268
Author(s):  
Elvina Elvina ◽  
Lukman Hakim
Keyword(s):  
Hill Climbing ◽  
Brute Force ◽  
Steepest Ascent ◽  
Slack Time

Lintasan kritis merupakan suatu hal yang sangat penting dan perlu diperhatikan dalam penjadwalan proyek, karena lintasan kritis mempunyai dampak terhadap terlambat atau tidaknya suatu proyek. Terdapat kenaikan pada angka pertumbuhan proyek di Indonesia. Oleh karena itu, untuk mendukung keberhasilan proyek tersebut, maka dilakukanlah penelitian terhadap pencarian lintasan kritis. Sehingga nantinya hasil dari penelitian ini berguna bagi para developer yang ingin membuat aplikasi yang menerapkan pencarian lintasan kritis. Parameter dari algoritma ini adalah waktu, yaitu : Earliest Start (ES), Early Finish (EF), Last Start (LS), dan Last Finish (LF). Algoritma Steepest-ascent Hill Climbing  berguna untuk mencari goal berdasarkan nilai heuristik terbaik. Nilai heuristik terbaik yang dijadikan acuan adalah slack time dari kegiatan. Algoritma Backtracking merupakan perbaikan dari algoritma Brute-Force yang berbasis DFS (Deep-First Search). Jurnal ini membahas tentang algoritma Steepest-ascent Hill Climbing yang berguna untuk mencari slack (keterlambatan) guna menjadi tolak ukur dari lintasan kritis, dan backtracking yang berguna untuk mencari ES, EF, LS, dan LF guna menjadi parameter dalam mencari slack (keterlambatan). Angka keberhasilan dari penggabungan algoritma ini untuk mencari lintasan kritis adalah sebesar 80%.

scholarly journals Palmprint False Acceptance Attack with a Generative Adversarial Network (GAN)

2020 ◽  
Vol 10 (23) ◽  
pp. 8547
Author(s):  
Fei Wang ◽  
Lu Leng ◽  
Andrew Beng Jin Teoh ◽  
Jun Chu
Keyword(s):  
Multimedia Systems ◽  
Generative Adversarial Networks ◽  
Clustering Method ◽  
Generative Adversarial Network ◽  
Adversarial Network ◽  
Adversarial Networks ◽  
Biometric Systems ◽  
Biometric Based Authentication ◽  
False Acceptance

Biometric-based authentication is widely deployed on multimedia systems currently; however, biometric systems are vulnerable to image-level attacks for impersonation. Reconstruction attack (RA) and presentation attack (PA) are two typical instances for image-level attacks. In RA, the reconstructed images often have insufficient naturalness due to the presence of remarkable counterfeit appearance, thus their forgeries can be easily detected by machine or human. The PA requires genuine users’ original images, which are difficult to acquire in practice and to counterfeit fake biometric images on spoofing carriers. In this paper, we develop false acceptance attack (FAA) for a palmprint biometric, which overcomes the aforementioned problems of RA and PA. FAA does not require genuine users’ images, and it can be launched simply with the synthetic images with high naturalness, which are generated by the generative adversarial networks. As a case study, we demonstrate the feasibility of FAA against coding-based palmprint biometric systems. To further improve the efficiency of FAA, we employ a clustering method to select diverse fake images in order to enhance the diversity of the fake images used, so the number of attack times is reduced. Our experimental results show the success rate and effectiveness of the FAA.

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