Slezak / Kim / Fang Security Technology

International Conference, SecTech 2009, Held as Part of the Future Generation Information Technology Conference, FGIT 2009, Jeju Island, Korea, December 10-12, 2009. Proceedings
1. Auflage 2009
ISBN: 978-3-642-10847-1
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, Band 58, 319 Seiten

Reihe: Communications in Computer and Information Science

This volume constitutes the selected papers of the International Conference on Security Technology, SecTech 2009, held as part of the Future Generation Information Technology Conference, FGIT 2009, on Jeju Island, Korea, in December 2009.

Autoren/Hrsg.

Slezak, Dominik

Kim, Tai-Hoon

Fang, Wai-chi

Inhaltsverzeichnis

1;Foreword;5
2;Preface;7
3;Organization;8
4;Table of Contents;10
5;Applications of Reversible Data Hiding Techniques with the Quick Response Codes;13
5.1;Introduction;13
5.2;Background Descriptions of QR Codes;14
5.3;Algorithms of Reversible Data Hiding and Integration with QR Codes;15
5.3.1;Histogram-Modification for Reversible Data Hiding;16
5.3.2;Difference-Expansion for Reversible Data Hiding;16
5.3.3;Proposed Scheme for Integration;17
5.4;Simulation Results;18
5.5;Conclusions;19
5.6;References;20
6;A New Approach in T-FA Authentication with OTP Using Mobile Phone;21
6.1;Introduction;21
6.2;T-FA (Two-Factor Authentication);22
6.2.1;T-FA Implementations;22
6.2.2;Authentication Types;22
6.3;OTP (One Time Password);23
6.4;Related Technology;23
6.4.1;Benefits;23
6.5;Related Work;24
6.5.1;Time Factor Based;24
6.5.2;Java MIDlet;24
6.6;The Proposed System;25
6.6.1;Solution Overview;25
6.6.2;One Time Password Generation;25
6.6.3;Working of the System;26
6.6.4;Comparison and Advantages;27
6.7;Conclusion;28
6.8;References;29
7;Correlating Alerts into Compressed Graphs Using an Attribute-Based Method and Time Windows;30
7.1;Introduction;30
7.2;Alert Correlation Method;31
7.2.1;Correlation Knowledge Base;31
7.2.2;Similarity Vectors;31
7.2.3;Correlation Probability Estimation;32
7.2.4;Correlating Alerts;32
7.3;Compression Method;34
7.4;Experimental Results;34
7.4.1;Method Validation;34
7.4.2;Method Evaluation;35
7.5;Related Works;36
7.6;Conclusion and Future Works;36
7.7;References;37
8;A Study on Secure Contents Using in Urban Computing;38
8.1;Introduction;38
8.2;Secure Context Operating;39
8.2.1;Security Functions;39
8.2.2;Urban Life;39
8.2.3;Each Step;40
8.2.4;Security Processing;42
8.3;Discussion;42
8.3.1;Algorithm;42
8.3.2;Result of Experiments;44
8.4;Conclusion;45
8.5;References;45
9;Shadow Generation Protocol in Linguistic Threshold Schemes;47
9.1;Introduction;47
9.2;Shadow Generation Protocol in Linguistic Schemes;48
9.3;Application of Linguistic Threshold Schemes in Layered and Hierarchical Structures;51
9.4;Conclusion;53
9.5;References;53
10;Analysis of Handwritten Signature Image;55
10.1;Introduction;55
10.2;Previous Works;56
10.3;Our Work;57
10.3.1;Transform Gray Signature Image to Bi-Color Signature Image;57
10.3.2;Extracting Region of Interest (ROI);57
10.3.3;Scaling;58
10.3.4;Image Thinning Algorithm (ITA);58
10.4;Result;59
10.5;Conclusion;61
10.6;References;62
11;The Design of Signature Selection for Protecting Illegal Outflow of Sensitive Information in Mobile Device;63
11.1;Introduction;63
11.2;Backgrounds;64
11.3;The Strategy of Selection of Signature;65
11.3.1;Considerations for Signature Selection;65
11.3.2;Considerations for Hardware Limitations;65
11.4;The Method of Signature Selection;66
11.5;Conclusions;67
11.6;References;68
12;Hardware Based Data Inspection for USB Data Leakage Prevention;69
12.1;Introduction;69
12.2;Architecture;70
12.3;Design;71
12.3.1;Signature Management Application;71
12.3.2;USB DLP Board;72
12.4;Implementation;73
12.5;Conclusion;74
12.6;References;74
13;Grayscale Image Classification Using Supervised Chromosome Clustering;76
13.1;Introduction;76
13.2;Previous Works;78
13.3;Our Work;79
13.4;Result;80
13.5;Conclusion;82
13.6;References;82
14;Towards the Integration of Security Aspects into System Development Using Collaboration-Oriented Models;84
14.1;Introduction;84
14.2;The Basic Development Method;85
14.3;The Security-Enhanced Method;87
14.4;Security Analysis of the e-Sale System;88
14.5;Security Specific Building Blocks;90
14.6;Secure e-Sale System;92
14.7;Related Work;94
14.8;Concluding Remarks and Future Work;94
14.9;References;96
15;Impact of Malicious Node on Broadcast Schemes;98
15.1;Introduction;98
15.2;Related Work;99
15.2.1;Characteristics of Relevance Based Approach;99
15.2.2;Cross Layer Implementation;100
15.2.3;802.11e Implementation;100
15.2.4;802.11e Implementation with Virtual Queue;101
15.3;Proposed Study and Results;101
15.3.1;Study 1;101
15.3.2;Study 2;102
15.3.3;Study 3;102
15.4;Conclusion;104
15.5;References;104
16;Hierarchical Identity-Based Identification Schemes;105
16.1;Introduction;105
16.1.1;Background;105
16.1.2;Our Contribution;106
16.1.3;Why HIBI?;106
16.2;Preliminaries;107
16.2.1;Bilinear Pairings;107
16.2.2;Computational Diffie-Hellman Problem (CDHP);107
16.2.3;One-More Computational Diffie-Hellman Problem (OMCDHP);107
16.3;Hierarchical Identity-Based Identification;107
16.3.1;Definition;108
16.3.2;Security Model;108
16.4;Construction;109
16.5;Security Analysis;109
16.5.1;Security against Passive Attacks;109
16.5.2;Security against Active and Concurrent Attacks;110
16.5.3;Efficiency Analysis;110
16.6;Conclusion;110
16.7;References;110
17;The Trend of the Security Research for the Insider Cyber Threat;112
17.1;Introduction;112
17.2;The Insider Security;113
17.3;The Previous Researches for the Insider Threat;114
17.3.1;Prediction Model;114
17.3.2;Intent-Driven Insider Threat Detection;115
17.3.3;Sensitive Information Dissemination Detection;116
17.3.4;Honeypot;117
17.4;Problems of the Current Insider Security System;117
17.5;Conclusions;118
17.6;References;118
18;MIMO Wiretap Channel: A Scalar Approach;120
18.1;Introduction;120
18.2;MIMO Gaussian Wiretap Channel;121
18.3;Capacity Analysis;123
18.3.1;Secrecy Capacity;123
18.3.2;Existence of Secrecy Capacity;124
18.3.3;Outage Probability under Slow Fading;125
18.4;Conclusion;126
18.5;References;126
19;Security Testing for Operating System and Its System Calls;128
19.1;Introduction;128
19.2;Theoretical Foundation;129
19.2.1;Conception and Extension of Security Testing;129
19.2.2;Security Testing Automation for an Operating System;130
19.2.3;Security Testing of System Calls;130
19.3;Prototype Design and Implementation;131
19.3.1;Basic Framework;131
19.3.2;Prototype Implementation;132
19.4;Security Testing Execution and Results Analysis;133
19.4.1;Test Cases Design;133
19.4.2;Test Results Analysis;134
19.5;Summary;135
19.6;References;135
20;Efficient Group Signature with Forward Secure Revocation;136
20.1;Introduction;136
20.2;Definitions;137
20.3;Signature of Knowledge;138
20.4;Our Scheme and Security Analysis;138
20.4.1;Security Analysis;141
20.5;References;142
21;Detecting Distributed Denial of Service Attack Based on Multi-feature Fusion;144
21.1;Introduction;144
21.2;IFI Algorithm;145
21.3;DDoS Attack Detection Method;147
21.3.1;DDoS Attack Detection Model;147
21.3.2;Adaptive Parameter Estimate Algorithm;147
21.3.3;Alert Evaluation Mechanism;148
21.4;Experiments and Results;148
21.4.1;Feature;148
21.4.2;Performance Comparison;149
21.5;Conclusions;150
21.6;References;151
22;Researching on Cryptographic Algorithm Recognition Based on Static Characteristic-Code;152
22.1;Introduction;152
22.2;Associated Research;153
22.2.1;The Characteristic-Code Checking Technology;153
22.2.2;The Algorithm Recognition Technology;153
22.3;Extracting the Characteristic-Code from Cryptographic Algorithms;154
22.3.1;The Characteristic-Code of Hash Function;155
22.3.2;The Characteristic-Code of Grouping Cryptographic Algorithm;156
22.3.3;The Characteristic-Code of Public Key Cryptographic Algorithm;157
22.4;The Matching Algorithm of Cryptographic Algorithm Recognition;157
22.5;Test and Conclusion;158
22.6;Future Works;159
22.7;References;159
23;Verification of Security-Relevant Behavior Model and Security Policy for Model-Carrying Code;160
23.1;Introduction;160
23.2;Related Work;161
23.3;Security-Relevant Behavior Model: EPDA;161
23.4;Security Policy: EFSA;162
23.5;Formal Verification of EPDA and EFSA;163
23.5.1;Finding an Equivalent EFSA for a EPDA;163
23.5.2;Improvements to REE;165
23.5.3;Algorithms for Verification;165
23.6;Future Work;167
23.7;References;167
24;Feature Level Fusion of Biometrics Cues: Human Identification with Doddington’s Caricature;169
24.1;Introduction;169
24.2;Description of SIFT Features;170
24.3;Feature Extraction and Feature Level Fusion;171
24.3.1;Preprocessing and SIFT Feature Extraction;171
24.3.2;Feature Level Fusion of SIFT Keypoints;172
24.4;Feature Reduction and Matching;173
24.4.1;Feature Reduction;173
24.4.2;Matching;173
24.5;Adaptive Weighting Using Doddington’s Approach;173
24.6;Experimental Results;174
24.7;Conclusion;175
24.8;References;176
25;A Study on the Interworking for SIP-Based Secure VoIP Communication with Security Protocols in the Heterogeneous Network;177
25.1;Introduction;177
25.2;SIP-Based Secure VoIP Communication;178
25.3;OPTIONS Method (RFC3329);179
25.3.1;Overview of Operation;179
25.3.2;Client Initiated;179
25.4;MIKEY (RFC3830);181
25.4.1;System Overview;181
25.4.2;Basic Key Transport and Exchange Methods;181
25.5;Secure Communication Interworking Scenarios;183
25.5.1;Partial Secure Communication I;184
25.5.2;Partial Secure Communication II;184
25.5.3;Partial Secure Communication III;186
25.6;Conclusion;186
25.7;References;186
26;DDoS Attack Detection Using Three-State Partition Based on Flow Interaction;188
26.1;Introduction;188
26.2;Related Work;189
26.3;IP Flow Interaction Feature;189
26.4;Attack Detection Method;190
26.4.1;Attack Detection Model;190
26.4.2;Adaptive Dual Detection Threshold Estimate Algorithm;191
26.4.3;Alarm Evaluation Mechanism;191
26.5;Experiments and Results;192
26.5.1;Experiments and Results about IFF Algorithm;192
26.5.2;Experiments and Results about DASA Method;193
26.6;Conclusions;195
26.7;References;195
27;A Development of Finite State Machine Create Tool for Cryptography Module Validation;197
27.1;Introduction;197
27.2;Cryptographic Module Validation and FSM;198
27.2.1;What Is the CMVP?;198
27.2.2;Relation of between CMVP and FSM;198
27.3;Modeling on the FSM;198
27.3.1;Method of State Diagram Modeling;199
27.3.2;Validation Checklist for State Diagram;201
27.3.3;TTP and CYC Create for Statediagram Validation;201
27.4;Implement of State Diagram Create Tool;203
27.5;Conclusion and Future Work;203
27.6;References;204
28;A Privacy-Aware System Using Threat-Based Evaluation and Feedback Method in Untrusted Ubiquitous Environments;205
28.1;Introduction;205
28.2;Architecture of Proposed System;206
28.3;System Design;208
28.3.1;Evaluating Penalty Value of Single Service;208
28.3.2;Basic Definitions for Hypergraph;210
28.3.3;Services Selection;210
28.4;Conclusion;211
28.5;References;212
29;Fusion of Multiple Matchers Using SVM for Offline Signature Identification;213
29.1;Introduction;213
29.2;Preprocessing of Offline Signatures and Feature Extraction;214
29.2.1;Preprocessing Operations;214
29.2.2;Global and Local Features Extraction;215
29.3;Matching Scores Generation;216
29.3.1;Matching Score Generation Using Euclidean Distance;216
29.3.2;Matching Score Generation Using Mahalanobis Distance;217
29.3.3;Matching Score Generation Using Gaussian Empirical Rule;217
29.4;Fusion of Multiple Matchers Using Support Vector Machines;218
29.5;Experimental Results;218
29.6;Conclusion;219
29.7;References;220
30;A Two-Factor Mutual Authentication Scheme Using Biometrics and Smart Card;221
30.1;Introduction;221
30.2;Background on Error Control Codes and Fuzzy Commitment;222
30.2.1;Error Control Codes;222
30.2.2;Fuzzy Commitment;222
30.3;Assumptions and Attack Model;223
30.4;Proposed Scheme;223
30.4.1;Registration Phase;224
30.4.2;Authentication Phase;224
30.5;Security Analysis;226
30.6;Conclusions;227
30.7;References;228
31;Secure Collection Tree Protocol for Tamper-Resistant Wireless Sensors;229
31.1;Introduction;229
31.2;Wireless Sensors with Tamper-Resistant Module;230
31.3;Collection Tree Protocol;230
31.4;Secure Collection Tree Protocol;231
31.4.1;General Assumptions;231
31.4.2;Protocol Modifications;231
31.4.3;Frame Formats;233
31.4.4;Security;234
31.4.5;Communication Overhead;234
31.4.6;Simulation Results;235
31.5;Conclusion;235
31.6;References;236
32;Accelerometer Based Digital Video Stabilization for Security Surveillance Systems;237
32.1;Introduction;237
32.2;Image Stabilization Algorithms;238
32.2.1;Plain Matching Algorithm;238
32.2.2;Bit Plane Matching Algorithm;240
32.2.3;Enhancement – Our Solution for Image Stabilization;241
32.3;Hardware Design;241
32.3.1;Description of Our Hardware Layout;242
32.3.2;Solution with an Accelerometer;243
32.4;Conclusion;244
32.5;References;244
33;Escrowed Deniable Identification Schemes;246
33.1;Introduction;246
33.2;Preliminaries;247
33.3;Escrowed Deniable Identification;247
33.3.1;Escrowed Deniable Identification Schemes;247
33.3.2;Deniability;248
33.3.3;Impersonation;249
33.3.4;Transferability;249
33.4;Our Construction;250
33.5;Conclusion;253
33.6;References;253
34;Insights into Malware Detection and Prevention on Mobile Phones;254
34.1;Introduction;254
34.2;State-of-the-Art Mobile Malware and Countermeasures;255
34.2.1;State and Trends on Mobile Malware;255
34.2.2;Academic Research against Mobile Malware;256
34.2.3;Industrial Effort against Mobile Malware;257
34.3;Potential Directions for Effective Malware Detection and Prevention on Mobile Phones;258
34.3.1;Monitoring Power Consumption;258
34.3.2;Increasing Platform Diversity;259
34.3.3;Enforcing Hardware Sandbox;259
34.4;Conclusion;261
34.5;References;261
35;Automation of Post-exploitation;262
35.1;Introduction;262
35.2;Limits of Usual Payloads;263
35.3;Metasploit and Meterpreter;263
35.4;Practical Part;264
35.4.1;Metasploit Programming APIs;264
35.4.2;Implementing a Standalone Instance;265
35.4.3;Implementing Post-exploit Scripts;266
35.4.4;Integration of Pivoting;269
35.5;Conclusion;269
35.6;References;269
36;Speaker Dependent Frequency Cepstrum Coefficients;270
36.1;Introduction;270
36.2;Speaker Dependent Features;270
36.2.1;Filter Design;271
36.2.2;Speaker Dependent Frequency Filter Bank;271
36.2.3;Speaker Dependent Frequency Cepstrum Coefficients;272
36.3;Experimental Results;273
36.3.1;Speaker Verification and Identification;273
36.4;Conclusions;275
36.5;References;276
37;Towards the Detection of Encrypted BitTorrent Traffic through Deep Packet Inspection;277
37.1;Introduction;277
37.2;Methodology for P2P Traffic Detection Using Signatures;279
37.3;Experimental Setup;279
37.4;BitTorrent Application;280
37.4.1;Application Details;280
37.4.2;SNORT Rules and Experiments with Encrypted Traffic;281
37.5;Conclusions;283
37.6;References;284
38;A Simple Encryption Scheme for Binary Elliptic Curves;285
38.1;Introduction;285
38.2;Background;286
38.2.1;The Trace Function in $\mathbb{F}_{2^{n}}$;286
38.2.2;Elliptic Curves Defined over $\mathbb{F}_{2^{n}}$;286
38.2.3;Isomorphisms of Binary Elliptic Curves;287
38.2.4;An Application of the Isomorphism;287
38.2.5;Elliptic Curve El Gamal Public-Key Encryption (EC El Gamal);288
38.3;Applying the Isomorphism to Create an Encryption Scheme;288
38.4;Conclusion;292
38.5;References;292
39;Analysis of Text Complexity in a Crypto System – A Case Study on Telugu;293
39.1;Introduction;293
39.2;Review;294
39.3;Security Model;295
39.4;Frequency Distribution of Character Code Points of Telugu Script;296
39.5;Crypto Analysis Using Frequency Distribution;297
39.6;Conclusions;299
39.7;References;299
40;Symmetric-Key Encryption for Wireless Internet SCADA;301
40.1;Introduction;301
40.2;SCADA Defined;301
40.2.1;SCADA Hardware and Software;302
40.2.2;HMI;303
40.3;Installation of SCADA;303
40.3.1;Conventional SCADA;303
40.4;Wireless SCADA;304
40.5;Internet SCADA;305
40.5.1;Internet SCADA Issues;306
40.6;Utilization of Symmetric Key Encryption;306
40.6.1;RC4 Cipher;306
40.7;Symmetric Key Encryption in Wirelss SCADA Environment;308
40.8;Conclusion;308
40.9;References;309
41;An Efficient Pre-filtering Mechanism for Parallel Intrusion Detection Based on Many-Core GPU;310
41.1;Introduction;310
41.2;Use Sub-patterns for Packets Pre-filtering;311
41.2.1;Statistic Analysis;311
41.2.2;Sub-patterns;312
41.3;Use BILP to Optimize the Choice of Filter Sub Patterns;313
41.3.1;Basic Idea;313
41.3.2;BILP Based Optimization;313
41.4;Advantages in Utilizing GPU;314
41.5;Experiments and Results;315
41.5.1;Sub Patterns Extraction and the BILP Optimization;315
41.5.2;Pre-filtering Effects;316
41.6;Conclusions and Future Work;316
41.7;References;317
42;Author Index;318