There are many IoT devices use by peoples to make their life easy, but there are some devices that are very important like healthcare devices which are very small in size and having very less memory and power backup. It is important to transfer data to the server with privacy, so we use encryption for that. To encrypt data in such small IoT devices we use lightweight cryptography. There are many healthcare IoT devices that uses SIMON algorithm and there is a need to optimise that algorithm to improve the execution time and memory consumption. In this paper we are introducing the new approach to optimise lightweight cryptography algorithm that is SIMON.
1.1. SIMON Algorithm m-word m must be 2, 3 or 4 n is equal to word size
National Security Agency (NSA) proposed the SIMON algorithm. It provides security to highly constrained devices. It is a Feistel block cipher. The existing cryptographic algorithm is designed keeping in mind hardware devices. This type of algorithm is designed to work under pervasive computing systems. Unlike all algorithms its main objective is to protect data. It uses round functions of left circular shift, bitwise OR and bitwise AND. It was developed to get best performance on hardware but fortunately it is giving best performance in hardware as well software.
Encryption: To encrypt 64bit plaintext P, it uses 44 round functions with 44 round keys generated using key schedule. The key expansion function and round are designed in such a way that they can be used in parallel if needed. Encryption and decryption are symmetric. Decryption: To decrypt a 64 bit ciphertext c, first we swap 32 bit rightmost bits to 32 bits leftmost bits, then applying 44 round function and after completion of all 44 round function ifnally we swap 32 bit leftmost with rightmost and vice versa.
In Fig 1 Norah et al.[
Author utilised the MSP-cycle-watcher, which was designed as a quality-control tool, this
can calculate the clock cycle of encryption algorithm. The number of cycles in the encryption
part’s code is calculated by subtracting it from the total number of cycles in the entire code,
which includes setup and post-processing overhead. To get result in a fair power consumption
comparison research It is important to comparing exact encryption clock cycles. In addition,
this phase (counting encryption cycles) was done exactly by including a determination of check
point for the conclusion and start of the counting process. They use a Bsize command in the
MSP430 GCC compiler to estimate ROM usage in this study. The memory usage of this Bsize
A measure is calculated automatically from the file which is of compiled code. The program’s
consumption of ROM is the total number of data and text bytes utilised and the consumption
of ROM is determined for the specialised encryption portion only.RAM usage comprises both
stack and data use. The consumption of data is calculated using the implementation information
ifle and the command. To examine the stack usage, they used the MSP stack watcher during
execution.[
In December 2015, a paper published by Dhruti Sharma[
Now let’s see about Attribute based encryption technique, it is also a modified version of public key cryptography, in these various attributes are used to form a public key. This encryption technique help sender to define access policies for receiver and also provide fine access control to sender and that lead to control accessibility of data. In this methodology, we are just sending encrypted data over server which stores these data for further encrypted processing such as statistical computations, charts and report generation, forecasting etc. Using this technique, we are also providing data privacy as central system stored each data in encrypted form and can only be accessible by authorized person.
The authors of [
The authors of paper [
Authors of [
While studying above papers got some research gap that execution time is high of SIMON(64/96). While improving execution time of SIMON(64/96), SIMON(96/96), SIMON(128/128) ROM usage also increased. There are few works related to optimised SIMON(48/96), SIMON(64/128), SIMON(96/144), SIMON(128/192), SIMON(128/256). 3. Our Contribution • To develop a modified approach to decrease the execution time. As the reduction of execution time helps in the faster communication between healthcare IoT device and main system or Doctor. • To design modified approach to decrease the ROM usage. • To deploy the approach on diferent multiple data key combination to verify check the performance. As some data key pair combination of SIMON algorithm using more RAM in optimized SIMON algorithm as compare to original algorithm as shown in fig 1, to overcome this problem we have introduced some solutions in Proposed Work. With all this changes lifetime of devices also will increased. This will very useful for devices which are implant in body of human with surgery like pacemaker.
We are going to modify multiple parameters of algorithm in a such a way that the privacy will not compromise while doing this we will reduce the rounds of the algorithm so ROM usage will
Dhruti Sharma and Devesh Jin- Secure E-Health IOT syswala tem idea is given Power Consumption of algorithms is not considered
Asmaa Sabet Anwar et al.
Athmika Aravind et al.
Security of image transmission
ROM usage is more Working and implementa- SIMON’s power consumption tion of IDEA and SIMON is less than IDEA but time delay algorithms using Xilinx is greater because of rounds.
14.2
Norah Alassaf et al.
ROM usage is not considered
Sohel Rana et al.
Lightweight cryptography to secure medical data Comparison of light weight cryptographic algorithms
Norah Alassaf et al.
Speedup algorithm
Mohamed Elhoseny et al.
Bahram Rashidi
Secure model for patient data transmission SIMON algorithm parameters
NA
Shrikant Taware et al.
Data Security
Power cunsumption is high
Gaëtan Leurent et al.
Attacks and security
Rounds of algorithm takes more time to execute
Anil Gopal Sawant et al.
Power Consumption
Execution speed is low
Bety Hayat Susanti et al.
Security
Power consumption is high
Response time Power Consumption of SIMON is greater then SPECK Cycle for key generation is greater than SPECK ROM usage is increases in SIMON(96/96) SIMON(128/128) Computation power is more reduce and execution speed of algorithm will increase. Our main focus on the that data key combination for which there is very few work.
In Fig 2 we have proposed the modified algorithm for SIMON algorithm. In this algorithm we are using left shift as the original SIMON algorithm for those data key pair combination where the ROM usage is increased by removing left shift by using simple if else condition in the program. Other data key pair combination will not use that left shift as they are performing well without that. Along with this we are going to reduce some rounds of some data key pair combinations of SIMON to increase the speed of algorithm and to decrease the ROM usage.
In Table 3 we have given the tentative reduction of the rounds for each data key combinations of SIMON algorithm. Security of algorithm is also considered while reducing the rounds of the SIMON algorithm. In existing SIMON algorithm there are 32 to 72 rounds. We are going to restrict that round by 0 to 9 cycles. By increasing the execution speed of the the algorithm power consumption will also going to decrease which will lead to increase the lifetime of healthcare devices.
In this paper presented a modified version of SIMON lightweight cryptography algorithm for multi data key pair combinations to improve the execution speed and to decrease the ROM usage. Also focused on data key pair combinations having very few work related to that. This will help to increase the lifetime of the device as the time of execution and ROM usage of algorithm is reduced. In future more modification in SIMON algorithms can done to increase the security without increasing the rounds of algorithm, So the execution speed and security both will not compromised. [9] N. Alassaf, B. Alkazemi, A. Gutub, Applicable light-weight cryptography to secure medical data in iot systems, Arabia (2003). [10] S. Rana, S. Hossain, H. I. Shoun, M. A. Kashem, An efective lightweight cryptographic algorithm to secure resource-constrained devices, International Journal of Advanced Computer Science and Applications 9 (2018). [11] M. Elhoseny, G. Ramírez-González, O. M. Abu-Elnasr, S. A. Shawkat, N. Arunkumar, A. Farouk, Secure medical data transmission model for iot-based healthcare systems, Ieee Access 6 (2018) 20596–20608. [12] S. Taware, R. R. Chakravarthi, C. A. Palagan, K. Chandrasekaran, N. Vadivelan, Preserving mobile commerce iot data using light weight simon block cipher cryptographic paradigm, Journal of Ambient Intelligence and Humanized Computing 12 (2021) 6081–6089. [13] P. Yalla, J.-P. Kaps, Lightweight cryptography for fpgas, in: 2009 international conference on reconfigurable computing and FPGAs, IEEE, 2009, pp. 225–230. [14] B. Susanti, O. Permana, et al., Robustness test of simon-32, speck-32, and simeck-32 algorithms using fixed-point attacks, in: Journal of Physics: Conference Series, volume 1836, IOP Publishing, 2021, p. 012006. [15] A. K. Mandal, C. Parakash, A. Tiwari, Performance evaluation of cryptographic algorithms: Des and aes, in: 2012 IEEE Students’ Conference on Electrical, Electronics and Computer Science, IEEE, 2012, pp. 1–5. [16] J. Gitanjali, N. Jeyanthi, C. Ranichandra, M. Pounambal, Ascii based cryptography using unique id, matrix multiplication and palindrome number, in: The 2014 International Symposium on Networks, Computers and Communications, IEEE, 2014, pp. 1–3. [17] M. Hölbl, M. Kompara, A. Kamišalić, L. Nemec Zlatolas, A systematic review of the use of blockchain in healthcare, Symmetry 10 (2018) 470. [18] A. Shehab, A. Ismail, L. Osman, M. Elhoseny, I. M. El-Henawy, Quantified self using iot wearable devices, in: International conference on advanced intelligent systems and informatics, Springer, 2017, pp. 820–831.