Studying the Effects of Most Common Encryption Algorithms

Wireless networks play critical roles in present wor k, home, and public places, so the needs of protecting of such networks are increased. Encryption algorithms play vital roles in information systems sec urity. Those algorithms consume a significant amount of computing resources such as CPU time, memory, an d battery power. CPU and memory usability are increasing with a suitable rates, but battery technology is increasing at slower rate. The problem of the slower increasing battery technology forms "battery gap". The design of efficient secure protocols for wireless devices from the view of battery consumption needs to understand how encryption techniques affect the consumption of battery power with and without data transmission. This paper studies the effects of six of the most common symmetric encryption alg orithms on power consumption for wireless devices. at different settings for each algorithm. These setting include different sizes of data blocks, different data types (text, images, and audio file), battery power consumption, different key size, different cases of transmission of the data , effect of varying signal to noise ratio and finally encryption/decryption speed.The experimental results show the superiority of two encryption algorithm over other algorithms in terms of the power consumption, proc essing time, and throughput .These results can aid in new design of security protocol where energy efficiency is the main focus. Some suggestions for design of secure communications systems to handle the varying wireless environment have been provided to r educe the energy

[1]  Sagar Naik,et al.  Software implementation strategies for power-conscious systems , 1999, Mobile Networks and Computing.

[2]  A T Karygiannis,et al.  Wireless Network Security: 802.11, Bluetooth and Handheld Devices , 2002 .

[3]  James Kempf Wireless Internet Security - Architecture and Protocols , 2008 .

[4]  M.Y. Javed,et al.  A Performance Comparison of Data Encryption Algorithms , 2005, 2005 International Conference on Information and Communication Technologies.

[5]  Thomas Hardjono,et al.  Security in Wireless LANs and MANs , 2005 .

[6]  R. N. Uma,et al.  Battery power-aware encryption , 2006, TSEC.

[7]  Vincent Rijmen,et al.  Rijndael, the advanced encryption standard , 2001 .

[8]  Joseph Y. Halpern,et al.  Minimum-energy mobile wireless networks revisited , 2001, ICC 2001. IEEE International Conference on Communications. Conference Record (Cat. No.01CH37240).

[9]  Nathan Ickes,et al.  Physical layer driven protocol and algorithm design for energy-efficient wireless sensor networks , 2001, MobiCom '01.

[10]  William Stallings,et al.  Cryptography and Network Security (4th Edition) , 2005 .

[11]  P. Krishnamurthy,et al.  Encryption and Power Consumption in Wireless LANs , 2001 .

[12]  Anantha Chandrakasan,et al.  JouleTrack: a web based tool for software energy profiling , 2001, DAC '01.

[13]  R. Badlishah Ahmad,et al.  Performance Analysis of Encryption Algorithms' Text Length Size on Web Browsers , 2008 .

[14]  Osama M. Abu Zaid,et al.  Quality of Encryption Measurement of Bitmap Images with RC6, MRC6, and Rijndael Block Cipher Algorithms , 2007, Int. J. Netw. Secur..

[15]  Prashant Krishnamurthy,et al.  Analysis of energy consumption of RC4 and AES algorithms in wireless LANs , 2003, GLOBECOM '03. IEEE Global Telecommunications Conference (IEEE Cat. No.03CH37489).

[16]  Praphul Chandra BULLETPROOF WIRELESS SECURITY: GSM, UMTS, 802.11, and Ad Hoc Security (Communications Engineering) , 2005 .

[17]  Sujit Dey,et al.  Embedded Tutorial: Battery-Driven System Design: A New Frontier in Low Power Design. , 2002 .

[18]  William A. Arbaugh,et al.  Real 802.11 Security: Wi-Fi Protected Access and 802.11i , 2003 .

[19]  B. Brown 802.11: the security differences between b and i , 2003 .

[20]  Don Coppersmith,et al.  The Data Encryption Standard (DES) and its strength against attacks , 1994, IBM J. Res. Dev..