1 Telematics/Networkengineering Confidential Transmission of Lossless Visual Data: Experimental Modelling and Optimization.

Slides:



Advertisements
Similar presentations
CoMPI: Enhancing MPI based applications performance and scalability using run-time compression. Rosa Filgueira, David E.Singh, Alejandro Calderón and Jesús.
Advertisements

Bandwidth-Efficient, Energy-Constrained Short Range Wireless Communications.
UDgateway WAN Optimization. 1. Why UDgateway? All-in-one solution Value added services – Networking project requirements Optimize IP traffic on constrained.
Pervasive Web Content Delivery with Efficient Data Reuse Chi-Hung Chi and Cao Yang School of Computing National University of Singapore
Software Architecture of High Efficiency Video Coding for Many-Core Systems with Power- Efficient Workload Balancing Muhammad Usman Karim Khan, Muhammad.
Security Overview Hofstra University University College for Continuing Education - Advanced Java Programming Lecturer: Engin Yalt May 24, 2006.
SCHOOL OF COMPUTING SCIENCE SIMON FRASER UNIVERSITY CMPT 820 : Error Mitigation Schaar and Chou, Multimedia over IP and Wireless Networks: Compression,
Exploring timing based side channel attacks against i CCMP Suman Jana, Sneha K. Kasera University of Utah Introduction
Dr Alejandra Flores-Mosri Message Authentication Internet Management & Security 06 Learning outcomes At the end of this session, you should be able to:
Peering in Infrastructure Ad hoc Networks Mentor : Linhai He Group : Matulya Bansal Sanjeev Kohli EE 228a Course Project.
1 CS 577 “TinySec: A Link Layer Security Architecture for Wireless Sensor Networks” Chris Karlof, Naveen Sastry, David Wagner UC Berkeley Summary presented.
Networking Theory (Part 1). Introduction Overview of the basic concepts of networking Also discusses essential topics of networking theory.
Security Internet Management & Security 06 Learning outcomes At the end of this session, you should be able to: –Describe the reasons for having system.
Security Internet Management & Security 06 Learning outcomes At the end of this session, you should be able to: –Describe the reasons for having system.
Introduction to Signcryption November 22, /11/2004 Signcryption Public Key (PK) Cryptography Discovering Public Key (PK) cryptography has made.
Performance Evaluation of Peer-to-Peer Video Streaming Systems Wilson, W.F. Poon The Chinese University of Hong Kong.
Compressibility of WML and WMLScript byte code:Initial results Eetu Ojanen and Jari Veijalainen Department of Computer Science and Information Systems.
11/11/05ELEC CISC (Complex Instruction Set Computer) Veeraraghavan Ramamurthy ELEC 6200 Computer Architecture and Design Fall 2005.
Apr 4, 2003Mårten Trolin1 Previous lecture TLS details –Phases Handshake Securing messages –What the messages contain –Authentication.
August 6, 2003 Security Systems for Distributed Models in Ptolemy II Rakesh Reddy Carnegie Mellon University Motivation.
Overview of Cryptography and Its Applications Dr. Monther Aldwairi New York Institute of Technology- Amman Campus INCS741: Cryptography.
Statistical Multiplexer of VBR video streams By Ofer Hadar Statistical Multiplexer of VBR video streams By Ofer Hadar.
Chapter 13: Electronic Commerce and Information Security Invitation to Computer Science, C++ Version, Fourth Edition SP09: Contains security section (13.4)
Variable Bit Rate Video Coding April 18, 2002 (Compressed Video over Networks: Chapter 9)
Chapter 8.  Cryptography is the science of keeping information secure in terms of confidentiality and integrity.  Cryptography is also referred to as.
Security Considerations for Wireless Sensor Networks Prabal Dutta (614) Security Considerations for Wireless Sensor Networks.
1 Public-Key Cryptography and Message Authentication Ola Flygt Växjö University, Sweden
Electronic Mail Security
UDgateway WAN Optimization. 1. Why UDgateway? All-in-one solution Value added services – Networking project requirements Optimize IP traffic on constrained.
KAIS T A lightweight secure protocol for wireless sensor networks 윤주범 ELSEVIER Mar
SSL and https for Secure Web Communication CSCI 5857: Encoding and Encryption.
E0262 MIS - Multimedia Playback Systems Anandi Giridharan Electrical Communication Engineering, Indian Institute of Science, Bangalore – , India.
A New Algorithm for Improving the Remote Sensing Data Transmission over the LEO Satellite Channels Ali Payandeh and Mohammad Reza Aref Applied Science.
TWOFISH ENCRYPTION ALGORITHM CS–627: Cryptology Fall 2004 Horatiu Paul Stancu.
© 2014 Cengage Learning. All rights reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license.
Mobile Relay Configuration in Data-Intensive Wireless Sensor Networks.
Protecting Internet Communications: Encryption  Encryption: Process of transforming plain text or data into cipher text that cannot be read by anyone.
PORTING A NETWORK CRYPTOGRAPHIC SERVICE TO THE RMC2000 : A CASE STUDY IN EMBEDDED SOFTWARE DEVELOPMENT.
LOGO Hardware side of Cryptography Anestis Bechtsoudis Patra 2010.
Processes and OS basics. RHS – SOC 2 OS Basics An Operating System (OS) is essentially an abstraction of a computer As a user or programmer, I do not.
Chapter Ten The Application and Presentation Layers.
RTP Encryption for 3G Networks Rolf Blom, Elisabetta Carrara, Karl Norrman, Mats Näslund Communications Security Lab Ericsson.
The NIProxy: a Flexible Proxy Server Supporting Client Bandwidth Management and Multimedia Service Provision Maarten Wijnants Wim Lamotte.
Chapter Ten The Application and Presentation Layers.
IT job research By Megan McGonigle Sources: - responsibilites-explainedhttp://targetcourses.co.uk/study-areas/computer-science-and-it/it-job-roles-and-
Understanding JPEG MIT-CETI Xi’an ‘99 Lecture 10 Ben Walter, Lan Chen, Wei Hu.
TinySec: A Link Layer Security Architecture for Wireless Sensor Networks Chris Karlof :: Naveen Sastry :: David Wagner Presented by Roh, Yohan October.
April 30, 2002ICC Optimal Linear Interpolation Coding for Server-based Computing Fei Li and Jason Nieh Network Computing Laboratory Columbia University.
TinySec : Link Layer Security Architecture for Wireless Sensor Networks Chris Karlof :: Naveen Sastry :: David Wagner Presented by Anil Karamchandani 10/01/2007.
Novel network coding strategy for TDD Use of feedback (ACK) improves delay/energy/ throughput performance, especially for high latency- high errors scenarios.
Advances in digital image compression techniques Guojun Lu, Computer Communications, Vol. 16, No. 4, Apr, 1993, pp
Computer Science 1 TinySeRSync: Secure and Resilient Time Synchronization in Wireless Sensor Networks Speaker: Sangwon Hyun Acknowledgement: Slides were.
Focus On Bluetooth Security Presented by Kanij Fatema Sharme.
SOCIAL HOUSEKEEPING THROUGH INTERCOMMUNICATING APPLIANCES AND SHARED RECIPES MERGING IN A PERVASIVE WEB-SERVICES INFRASTRUCTURE WP8 – Tests Ghent CREW.
m-Privacy for Collaborative Data Publishing
Copyright 2012, Toshiba Corporation. A Survey on the Algebraic Surface Cryptosystems Koichiro Akiyama ( TOSHIBA Corporation ) Joint work with Prof. Yasuhiro.
Resource Allocation in Hospital Networks Based on Green Cognitive Radios 王冉茵
Harnessing the Cloud for Securely Outsourcing Large- Scale Systems of Linear Equations.
Lx: A Technology Platform for Customizable VLIW Embedded Processing.
Dynamic Control of Coding for Progressive Packet Arrivals in DTNs.
IT 221: Introduction to Information Security Principles Lecture 5: Message Authentications, Hash Functions and Hash/Mac Algorithms For Educational Purposes.
New Efficient Image Encryption Scheme Based on Partial Encryption Karl Martin Multimedia Lab Dept. of Electrical and Computer Eng. University of Toronto.
1 of 14 Lab 2: Formal verification with UPPAAL. 2 of 14 2 The gossiping persons There are n persons. All have one secret to tell, which is not known to.
Energy Efficient Data Management in Sensor Networks Sanjay K Madria Web and Wireless Computing Lab (W2C) Department of Computer Science, Missouri University.
1 of 14 Lab 2: Design-Space Exploration with MPARM.
Cryptographic Hash Function. A hash function H accepts a variable-length block of data as input and produces a fixed-size hash value h = H(M). The principal.
Security Of Wireless Sensor Networks
Security of Wireless Sensor Networks
Outline A. Perrig, R. Szewczyk, V. Wen, D. Culler, and J. D. Tygar. SPINS: Security protocols for sensor networks. In Proceedings of MOBICOM, 2001 Sensor.
Presentation transcript:

1 Telematics/Networkengineering Confidential Transmission of Lossless Visual Data: Experimental Modelling and Optimization

2 Outline 1.Introduction 2.Basic Building Blocks »Lossless Compression »Encryption »Transmission 3. Cost Optimal Configuration of Confidential Visual Data Transmission 4.Conclusion 5.Future work

3 1. Introduction Large amounts of visual content in worldwide distributed database infrastructures  urgent need to provide and protect the confidentiality of sensitive visual data when transmitting it over networks of any kind

4 1. Introduction Focused on computationally efficient schemes in a lossless online scenario »Compression factor for visual data –lossless formats: 2 to 3 –lossy formats: > 100 »Reasons why lossless formats may be preferable –Loss of image data is not acceptable –Low processing power or limited energy ressources –High bandwidth at the communication channel

5 1. Introduction Tried to optimize the interplay of the 3 main steps »Compression »Encryption »Transmission Minimal computational effort and energy consumption

6 1. Introduction Modelled costs based on exemplary experimental data Derived a cost optimal strategy in the target environment Is the compression stage required in any case to result in an overall cost optimal scheme or not? Additionally we considered ‚Selective Encryption‘ »To trade off computational compexity for security

Selective Encryption Application specific data structures are exploited to create more efficient encryption systems Protect the visually most important parts of an image Relying on a secure but slow ‚classical‘ cipher

8 2. Basic Building Blocks The processing chain has always a fixed order Compression has to be performed prior to encryption »statistical properties of encrypted data prevent compression from being applied successfully »reduced amount of data decreases the computational demand Hardware platform: »996 MHz Intel Pentium III »128 MB RAM Network »100 MBit/s Ethernet

Lossless Compression JBIG reference implementation in a selective mode »compression of a different amount of bitplanes of 8 bpp greyscale images »scheme ranges from applying no compression at all to compressing a certain number of bitplanes –started from the MSB bitplane instead of applying JBIG to all bitplanes JPEG 2000 in lossless mode was used »compression results were better as compared to full JBIG coding

Lossless Compression 20 test images in 2 sizes obtained files sizes and compression timings were averaged for »512 x 512 »1280 x 1024 approximate interpolation of the measurement points by a 6 th order polynomial resulted in the following formulas x … resulting data size in 100 KByte after compression t … compression time in seconds

Lossless Compression  decreasing compression time for increasing data size Tradeoff between compression timings and the resulting data amount after compression

Encryption C++ RSA and C++ AES implementation RSA - for reasons of obtaining a rich variety in the overall behaviour of the processing chain »In practice you hardly use public-key systems to encrypt visual data »Time demand of RSA is several orders of magnitude higher as compared to AES »Performance differences among encryption schemes with the exhibited magnitude could result from applying hardware or software based approaches in real-life systems

Encryption  purely linear behaviour Amount of data encrypted in relation to processing time

Transmission Message passing library PVM 4 different modes »pvm_send - sends a message stored in the active send buffer to the PVM process identified by tid »pvm_psend - takes a pointer to a buffer buf, its length len, and its data type datatype and sends this data directly to the PVM task indentified by tid »ganz - data is sent as a whole block »teil – data is sent in pieces of 1 KByte Again data size is varied and the time required to transmit the data is measured and fitted by a polynomial

Transmission Transmission time related to data size

Transmission AES encryption and transmission operate on a similar level of time demand RSA is much more expensive As expected both processing stages exhibit linear behaviour

17 3. Cost Optimal Configuration of Confidential Visual Data Transmission Processing chain: compression – encryption – transmission has a fixed order but keeps a certain scope in the degree of execution (e.g. SE) Constrictions: »Level of complexity (compression) »Level of security (encryption) »Limited transmission bandwidth (transmission) Goal: Identify the cost optimal way (in terms of processing time) to operate the processing chain

18 3. Cost Optimal Configuration of Confidential Visual Data Transmission First configuration Image: 1280 x 1024 image Cipher: AES (a) AES(256) with PVM mode psend_teil (b) AES(256) with PVM mode send_ganz

19 3. Cost Optimal Configuration of Confidential Visual Data Transmission First configuration Image: 1280 x 1024 image Cipher: AES »Overall behaviour are almost identical to the approximated interpolation of the modeling equation (a) (b) ==> Optimal operation mode: No compression at all

20 3. Cost Optimal Configuration of Confidential Visual Data Transmission Second configuration Image: 1280 x 1024 image Cipher: RSA (a) RSA (512) with PVM mode psend_teil (b) RSA(2048) with PVM mode send_ganz

21 3. Cost Optimal Configuration of Confidential Visual Data Transmission Second configuration Image: 1280 x 1024 image Cipher: RSA »Curves monotonically increasing (unaffected by key size) (a) (b) ==> Optimal operation mode: Maximal compression

22 3. Cost Optimal Configuration of Confidential Visual Data Transmission Third configuration – Selective Encryption Image: 1280 x 1024 image Cipher: RSA (512bit key) (a) 20% encrypted with mode psend_teil (b) 12.5% encrypted with mode send_ganz

23 3. Cost Optimal Configuration of Confidential Visual Data Transmission Third configuration – Selective Encryption Image: 1280 x 1024 image Cipher: RSA (512bit key) »Curve b (12.5% encryption) showing local minimum (b) ==> Optimal operation mode: Compression of 3 out of 8 bitplanes with JBIG In the area of interest [6.6, 13]

24 3. Cost Optimal Configuration of Confidential Visual Data Transmission Fourth configuration – Selective Encryption Image: 512 x 512 image Cipher: RSA (512bit key) (a) 20% encrypted with mode psend_teil (b) 12.5% encrypted with mode send_ganz

25 3. Cost Optimal Configuration of Confidential Visual Data Transmission Third configuration – Selective Encryption Image: 512 x 512 image Cipher: RSA (512bit key) »Curve b (12.5% encryption) showing local minimum (b) ==> Optimal operation mode: Compression of 2 out of 8 bitplanes with JBIG In the area of interest [1.4, 2.6]

26 4. Conclusion Introduced: » Confidential transmission of visual data in lossless format Investigated: »A model of the costs in the 3 main steps compression – encryption – transmission Depending on the type of encryption involved, the optimal configuration of the entire system may be to operate: »Without compression »Full compression »Partial compression

27 5. Future Work Inclusion of constraints alleged by the target environment into the optimization: »Limited bandwidth »Certain level of security in selective encryption Modeling the dependency between selective compression and selective encryption

28 Thanks for your attention