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This paper details Implementation of the Encryption algorithm AES under VHDL
language In FPGA by using different architecture of mixcolumn. We then review
this research investigates the AES algorithm in FPGA and the Very High Speed
Integrated Circuit Hardware Description language (VHDL). Altera Quartus II
software is used for simulation and optimiz...
Context in source publication
Context 1
... cryptographic algorithms became the main proceeding for protection of very important data, the security objective called confidentiality [1-3] being the one taken into account by their hardware implementation and by their integration into the present-day communication systems. A number of the encryption/decryption algorithm the cryptographie has been developed [2-4]. Keeping pace with maturity of the security technology the hackers, the electronic eavesdroppers, electronic frauds and the virus have been coming into the field with new improved techniques for to attack the security mechanism [17], [19]. So to protect any attack to the valuable information source and their transmission, the algorithm Advanced Encryption Standard (AES or Rijndael), a Federal Information Processing Standard is approved by National Institute of Standards and Technology (NIST) [4], [7], [8], [11].But AES has 10 round of complex algebraic and matrix operation which involve high processing power and introduce delay in encryption and decryption process. For this reason at the beginning of this work the speed is treated as a major issue and concentration is provided on hardware based implementation. Field Programmable Gate Array based implementation is chosen in this operates as FPGA offers lower cost, flexibility and reasonable performance than ASIC (Application Specific Integrated Circuit) implementation. Beforehand researcher proposed application of AES processor on FPGA hardware place a few security features since earlier version of the FPGA available in the market was low capacity. Newly the development of a AES CPU using VHDL and its implementation on FPGA Xillinx without sacrificing any security feature of the algorithm is reported [22]. It offers many FPGA high capacities in various families. Literatures [10], [12], [13], [18], [20-21] describe design and implementation of AES processor in the FPGA platform. This paper presents a hardware implementation for the AES (Advanced Encryption Standard) symmetric cryptographic algorithm, under VHDL programming language by using different architecture of Mixcolumn and a hardware simulation of the resulted ciphering & deciphering module. AES algorithm is a FIPS standard and is a symmetric key [5], [9], in which the sender and recipient use only key for encryption and decryption. The data block length is fixed to be 128 bits (Nb = 4 words), while the length of the cipher key can be 128, 192 or 256 bits, and be represented by Nk = 4, 6, or 8 words respectively. Moreover, the AES algorithm is an iterative algorithm. The iterations are called rounds, and the total number of rounds, Nr is 10, 12, or 14, when the key length is 128, 192, or 256 bits, respectively. The 128 bit plaintext block is divided into 16 bytes. These bytes are mapped to a 4 x 4 array called the State, and all the internal operations of the AES algorithm are performed on the State. Each byte in the State is denoted by Si;j , (0 < i, j < 5) and is considered as an element of Galois Fields, GF(28). The irreducible polynomial used in the AES algorithm to construct, GF(28) field is In (Figure 1) AES encryption processes are presented. In the encryption of the AES algorithm, each round except for the final round consists of four transformations: the Sub__Bytes(), the Shift__Rows(), the Mix__Columns(), and the Add__RoundKey(), while the final round does not have the MixColumns() transformation. The algorithm AES It can be cut in three blocks: Initial Round: It is the first and simplest of the stages. it only counts one operation: Add Round Key. Remark: The inverse of this operation bloc it is herself. N Rounds: N being the number of iterations. This number varies according to the size of the key used. (128 bits need N=9, 192 bits need N=11 need 256 bits. N =13. This second stage is constituted of N iterations including each the four following operations: Sub Bytes, Shift Rows, Mix Columns, Add Round Key. Final Round: This stage is nearly identical to one of the N iterations of the second stage. The only difference is that it doesn't include the operation Mix Columns In this transformation, a round key is added to the State by a simple bit wise XOR operation (that is a sum in Galois Fields). Each tower key consists of four words from the key schedule ...
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This paper details Implementation of the Encryption algorithm AES under VHDL language In FPGA by using different architecture of mixcolumn. We then review this research investigates the AES algorithm in FPGA and the Very High Speed Integrated Circuit Hardware Description language (VHDL). Altera Quartus II software is used for simulation and optimiz...
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Citations
... transformation, as this transformation was redesigned by eliminating the excessive logical functions for the efficient and speed implementation of the AES algorithm on FBGA chipsets. In [13] several structures were applied to MixColumns() using finite filed techniques and selecting the best structure after applying certain tests on the different structures. In [14] [15] MixColumns() transformation was eliminated and replaced by a new technique based on chaotic system by applying a random map of type (Henon chaotic map), which provided a good diffusion and a reduced execution time. ...
... ShiftRow(i,1)=(ki [8]Xorki [9])mod4 ShiftRow(i,2)=(ki [10]Xorki [11])mod4 ShiftRow(i,3)=(ki [12]Xorki [13])mod4 ShiftRow(i,4)=(ki [14]Xorki [15])mod4 Figure 8: shows the distribution of the row and column shift constants in the encryption process over the AES rounds: ...
In this paper, a novel approach will be introduced to remove some weakness points in AES and increase its security. Unlike most previous researches, this research will improve the most important and powerful part of AES algorithm which is the MixColumns() transformation. In the original AES, there only one function is used, which it creates a fixed array that is used in MixColumns() transformation, and this fixed array is known by attackers. Alternatively, the expanded secret key will be used to generate a different function at each round of AES. These functions will create a variable dynamic arrays at each round based on expanded secret key. The variable dynamic arrays will increase confusion amongst bits of the encrypted text. After that, the ShiftRow() transformation will be complicated from ShiftRow() with fixed pattern to ShiftRowColumn() with variable dynamic pattern according to expanded secret key. The modified ShiftRowColumn() will increase the diffusion amongst bytes of encrypted text.
... Round function mengalami transformasi yang berulang, namun pada round terakhir state tidak mengalami transformasi dengan fungsi MixColumns, proses perulangan ini dapat diformulasikan sebagai proses Nr-1. Proses enkripsi dan dekripsi AES ditunjukkan pada Gambar 3 [12]. ...
Pada modul IoT yang memerlukan enkripsi data tetapi tidak dilengkapi dengan hardware accelerator khusus untuk enkripsi, perlu menggantikan hardware tersebut dalam bentuk program. Akan tetapi penambahan program enkripsi diketahui dapat menimbulkan permasalahan pada modul IoT berbasis embedded system yang memiliki sumber daya terbatas. Dalam kajian ini dibahas algoritma enkripsi AES-128 yang diimplementasikan pada modul IoT Particle Photon yang belum memiliki hardware accelarator. Tujuan yang hendak dicapai adalah untuk mengetahui pengaruh dari penerapan AES-128 pada modul IoT. Hasil pengujian menunjukkan AES-128 yang diterapkan dapat berjalan baik dengan waktu enkripsi paling lama 398 mikrodetik dan throughput terkecil 301507,538 bit/detik. Hasil pengukuran beban terhadap penerapan enkripsi berupa penggunaan memori flash oleh program sebesar 16.024 Byte dengan penggunaan RAM sebesar 3.020 Byte.
... The logistic map bifurcation diagram is shown in Fig. 5. The horizontal axis of the plot shows the (λ) parameter, and the vertical axis shows Fig. 4 An illustration of the AES encryption and decryption schemes [3] the logistic function at long-term values. It follows from Fig. 5 that the long-term behavior of the logistic map strongly depends on the value of the control parameter λ, namely, small changes in the control parameter translate into completely different end states, which is typical of a chaotic system. ...
Image encryption is a mainstream aspect in multimedia applications and as such it is a highly active research domain. Based on the increasing need for reliable image encryption this paper presents a new method which combines the Haar wavelet transform with the Advanced Encryption Standard (AES) and pixel shuffling based on a chaotic logistic map. In the proposed method the Haar wavelet transform is calculated from the original image to obtain the different frequency domains of the image, namely, the approximation coefficient (LL) and detail confidents (LH, HL and HH). The approximation part (LL) is then encrypted by using the AES algorithm to create the image diffusion and the inverse of the Haar wavelet transform is applied. To further enhance the encryption strength a chaotic logistic map is used to shuffle the resulting image thereby making a malicious reconstruction attempt very challenging. The proposed method was evaluated in an extensive set of tests and compared to several representative methods from the literature. Test results show that it performed well across a variety of images and achieved a better level of image encryption and a lower level of image degradation.
... A novel FPGA implementation of AES was proposed by [25] by using high performance Mix-Column and inv-Mix-Column methods, which uses properties of binary calculation. Their result shows 12% reduction in area and 20% increase in speed compared to the original AES design. ...
This paper surveys Lightweight Cryptographic solutions for Internet of Things (IoT). This survey covers comprehensively a flow of security measures from Lightweight Cryptographic solutions to comparison among different types of block ciphers. It also includes comparison between Hardware vs Software solutions and different recent approaches of the most trusted and researched block cipher, Advanced Encryption Standard (AES) in terms of architecture, Mix-Column/S-box modify strategy and attacks for IoT security. According to the study, lightweight AES has proved to be a good security solution for constrained IoT devices.
... Fig. 1. AES Encryption and Decryption [24] In the case of AES decryption in round 9 output of add round key goes to the input of inverse shift rows and from round 8 -1 output of inverse mix column goes to the input of byte substitution, output of inverse shift-rows becomes the input of inverse byte substitution operation, after substituting bytes from inverse S-Box the output is xored with the key and after adding the output goes to the inverse mix column operation output goes to the add round Key and the same process followed till round 9. Round 0 also follows the same steps except the inverse mix column step. ...
... Fig. 1. AES Encryption and Decryption [24] In the case of AES decryption in round 9 output of add round key goes to the input of inverse shift rows and from round 8 -1 output of inverse mix column goes to the input of byte substitution, output of inverse shift-rows becomes the input of inverse byte substitution operation, after substituting bytes from inverse S-Box the output is xored with the key and after adding the output goes to the inverse mix column operation output goes to the add round Key and the same process followed till round 9. Round 0 also follows the same steps except the inverse mix column step. ...
In the generation of worldwide Integrated Circuits (IC), a growing issue for the semiconductor industry is various attacks on VLSI design Intellectual Property. Such attacks are extremely difficult to detect during testing. The solution for these attack issues is to build the Design for Security. There are various approaches which are used in this domain and one such approach is Hardware Obfuscation techniques. This paper discussed about the design and simulation of 128-bit AES algorithm using active hardware obfuscation techniques. 128-bit AES is designed and simulated using Xilinx ISE 14.7. In this paper simulation results of 128-bit AES algorithm are analyzed with and without obfuscation techniques. Results shows that with obfuscation techniques 128 bit AES algorithm offer higher level of security and implementation flexibility with small area overhead which is 0.9% of total area utilized and 2% of power overhead.
... There are many ways how to implement individual encryption operations to FPGA. Article Arrag (2012) is dedicated to efficient design of hardware implementation of various architectures and the results of their tests are presented. Wiebe (2007) is one of the first articles, which describes hardware implementation of AES-128 algorithm to FPGA (Xilinx Virtex-4 XC4VFX12). ...
This article deals with encryption on Field Programmable Gate Array (FPGA). The first part describes current state of symmetric and asymmetric cryptography. The following part focuses on the AES algorithm and its implementation in VHDL language. The last part shows testing results of mentioned implementation on card NFB-40G2 containing FPGA from Xilinx series Virtex-7.
... Since becoming the AES, Rijndael has been the focus of countless analyses and has been implemented both in hardware and software for many different platforms. To accelerate the AES computation time, parallel computing is incorporated [3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19]. ...
... Advanced Encryption Standard (AES) can be deployed in fully hardware [3][4][5][6][7][8][9][10][11], hybrid softwarehardware [12][13][14][15][16], and fully software implementations [17][18][19]. This fact allows parallelization of AES in different ways. ...
... all ten cipher rounds were unrolled.) For more designs for hardware implementation of AES, the reader could refer to [8][9][10][11]. ...
The Advanced Encryption Standard (AES) algorithm is a symmetric block cipher which operates on a
sequence of blocks each consists of 128, 192 or 256 bits. Moreover, the cipher key for the AES algorithm is
a sequence of 128, 192 or 256 bits. AES algorithm has many sources of parallelism. In this paper, a design
of parallel AES on the multiprocessor platform is presented. While most of the previous designs either use
pipelined parallelization or take advantage of the Mix_Column parallelization, our design is based on
combining pipelining of rounds and parallelization of Mix_Column and Add_Round_Key transformations.
This model is divided into two levels: the first is pipelining different rounds, while the second is through
parallelization of both the Add_Round_Key and the Mix_Column transformations. Previous work proposed
for pipelining AES algorithm was based on using nine stages, while, we propose the use of eleven stages in
order to exploit the sources of parallelism in both initial and final round. This enhances the system
performance compared to previous designs. Using two-levels of parallelization benefits from the highly
independency of Add_Round_Key and Mix_Column/ Inv_Mix_Colum transformations. The analysis shows
that the parallel implementation of the AES achieves a better performance. The analysis shows that using
pipeline increases significantly the degree of improvement for both encryption and decryption by
approximately 95%. Moreover, parallelizing Add_Round_Key and Mix_Column/ Inv_Mix_Column
transformations increases the degree of improvement by approximately 98%. This leads to the conclusion
that the proposed design is scalable and is suitable for real-time applications.
Advancement in the internet of things to meet the requirement of human beings and society makes integration of multiple devices into a single system. The integration of hardware and software needs to be provided with security to avoid the stealing of the data. Otherwise, the hacker may gain control over the devices and change the functioning of the system which may lead to malfunction. In order to provide security for the data transfer in IoT, the security algorithm need to be embedded with the IoT. The algorithm should provide high security and at the same time, it should be efficient. In this paper, an attempt is made to design a synthesizable Deoxyribonucleic acid (DNA) based Nano Advanced Encryption Standard (AES) Intellectual Property (IP) Core which can be used as a crypto engine in an IoT system. The crypto engine developed is optimized in terms of power, area and delay. The developed design when compared with the conventional design has given an area advantage of 81.6%, power of 21.17%, gate delay of 88.44% and path delay of 99.64%.
Music is a sound that arises sensations in human mind and body. Music, since the beginning of time, has been present in every culture and life form, in audio and symbolic form, and in physical or digital mode of communication. While availability and scope for advancements increase exponentially, so does the need to search, compare, and organise music. Music industry has been striving towards finding the best possible approach to categorise music whether classification on the basis of emotions, instrumentation, genres, or any other music information will be most efficient as well as useful to listeners and music service providers. With the aim to support the best music experience, the current study statistically shows, with the help of prior research in music information retrieval and implementation of several powerful machine learning-based technologies, that genre classification, that too, ensemble-based, can be as accurate as 73.17%. The study analyses the performances of all models towards genre classification and concludes by proving max-voting ensemble-based models to be more accurate than each component classifier and advanced ensemble models and also optimal for real-world music genre classification as compared to prior experiments on GTZAN database, which is the novel contribution of the study.
