This document summarizes a research paper that proposes an authenticated multiple key distribution algorithm using simple continued fractions. The algorithm represents two large prime numbers as a simple continued fraction that is then used to construct a non-homogeneous equation with two variables. The secret key is divided into shares distributed to participants in a way that any fewer than a threshold number of shares provides no information about the secret. The full secret can only be reconstructed by combining a sufficient number of shares.
THE KEY EXCHANGE CRYPTOSYSTEM USED WITH HIGHER ORDER DIOPHANTINE EQUATIONSIJNSA Journal
One-way functions are widely used for encrypting the secret in public key cryptography, although they are regarded as plausibly one-way but have not been proven so. Here we discuss the public key cryptosystem based on the system of higher order Diophantine equations. In this system those Diophantine equations are used as public keys for sender and recipient, and both sender and recipient can obtain the shared secret through a trapdoor, while attackers must solve those Diophantine equations without trapdoor. Thus the scheme of this cryptosystem might be considered to represent a possible one-way function. We also discuss the problem on implementation, which is caused from additional complexity necessary for constructing Diophantine equations in order to prevent from attacking by tamperers.
Identity-based threshold group signature scheme based on multiple hard number...IJECEIAES
We introduce in this paper a new identity-based threshold signature (IBTHS) technique, which is based on a pair of intractable problems, residuosity and discrete logarithm. This technique relies on two difficult problems and offers an improved level of security relative to an on two difficult hard problems. The majority of the denoted IBTHS techniques are established on an individual difficult problem. Despite the fact that these methods are secure, however, a prospective solution of this sole problem by an adversary will enable him/her to recover the entire private data together with secret keys and configuration values of the associated scheme. Our technique is immune to the four most familiar attack types in relation to the signature schemes. Enhanced performance of our proposed technique is verified in terms of minimum cost of computations required by both of the signing algorithm and the verifying algorithm in addition to immunity to attacks.
Betrayal, Distrust, and Rationality: Smart Counter-Collusion Contracts for Ve...Changyu Dong
Cloud computing has become an irreversible trend. Together comes the pressing need for verifiability, to assure the client the correctness of computation outsourced to the cloud. Existing verifiable computation techniques all have a high overhead, thus if being deployed in the clouds, would render cloud computing more expensive than the on-premises counterpart. To achieve verifiability at a reasonable cost, we leverage game theory and propose a smart contract based solution. In a nutshell, a client lets two clouds compute the same task, and uses smart contracts to stimulate tension, betrayal and distrust between the clouds, so that rational clouds will not collude and cheat. In the absence of collusion, verification of correctness can be done easily by crosschecking the results from the two clouds. We provide a formal analysis of the games induced by the contracts, and prove that the contracts will be effective under certain reasonable assumptions. By resorting to game theory and smart contracts, we are able to avoid heavy cryptographic protocols. The client only needs to pay two clouds to compute in the clear, and a small transaction fee to use the smart contracts. We also conducted a feasibility study that involves implementing the contracts in Solidity and running them on the official Ethereum network.
THE KEY EXCHANGE CRYPTOSYSTEM USED WITH HIGHER ORDER DIOPHANTINE EQUATIONSIJNSA Journal
One-way functions are widely used for encrypting the secret in public key cryptography, although they are regarded as plausibly one-way but have not been proven so. Here we discuss the public key cryptosystem based on the system of higher order Diophantine equations. In this system those Diophantine equations are used as public keys for sender and recipient, and both sender and recipient can obtain the shared secret through a trapdoor, while attackers must solve those Diophantine equations without trapdoor. Thus the scheme of this cryptosystem might be considered to represent a possible one-way function. We also discuss the problem on implementation, which is caused from additional complexity necessary for constructing Diophantine equations in order to prevent from attacking by tamperers.
Identity-based threshold group signature scheme based on multiple hard number...IJECEIAES
We introduce in this paper a new identity-based threshold signature (IBTHS) technique, which is based on a pair of intractable problems, residuosity and discrete logarithm. This technique relies on two difficult problems and offers an improved level of security relative to an on two difficult hard problems. The majority of the denoted IBTHS techniques are established on an individual difficult problem. Despite the fact that these methods are secure, however, a prospective solution of this sole problem by an adversary will enable him/her to recover the entire private data together with secret keys and configuration values of the associated scheme. Our technique is immune to the four most familiar attack types in relation to the signature schemes. Enhanced performance of our proposed technique is verified in terms of minimum cost of computations required by both of the signing algorithm and the verifying algorithm in addition to immunity to attacks.
Betrayal, Distrust, and Rationality: Smart Counter-Collusion Contracts for Ve...Changyu Dong
Cloud computing has become an irreversible trend. Together comes the pressing need for verifiability, to assure the client the correctness of computation outsourced to the cloud. Existing verifiable computation techniques all have a high overhead, thus if being deployed in the clouds, would render cloud computing more expensive than the on-premises counterpart. To achieve verifiability at a reasonable cost, we leverage game theory and propose a smart contract based solution. In a nutshell, a client lets two clouds compute the same task, and uses smart contracts to stimulate tension, betrayal and distrust between the clouds, so that rational clouds will not collude and cheat. In the absence of collusion, verification of correctness can be done easily by crosschecking the results from the two clouds. We provide a formal analysis of the games induced by the contracts, and prove that the contracts will be effective under certain reasonable assumptions. By resorting to game theory and smart contracts, we are able to avoid heavy cryptographic protocols. The client only needs to pay two clouds to compute in the clear, and a small transaction fee to use the smart contracts. We also conducted a feasibility study that involves implementing the contracts in Solidity and running them on the official Ethereum network.
Digital Differential Analyzer (DDA) algorithm is the simple line generation algorithm which is explained step by step here.
Step 1 − Get the input of two end points (X0,Y0) and (X1,Y1).
Step 2 − Calculate the difference between two end points.
dx = X1 - X0
dy = Y1 - Y0
Step 3 − Based on the calculated difference in step-2, you need to identify the number of steps to put pixel. If dx > dy, then you need more steps in x coordinate; otherwise in y coordinate.
Step 4 − Calculate the increment in x coordinate and y coordinate.
Step 5 − Put the pixel by successfully incrementing x and y coordinates accordingly and complete the drawing of the line.
HOW TO FIND A FIXED POINT IN SHUFFLE EFFICIENTLYIJNSA Journal
In electronic voting or whistle blowing, anonymity is necessary. Shuffling is a network security technique
that makes the information sender anonymous. We use the concept of shuffling in internet-based lotteries,
mental poker, E-commerce systems, and Mix-Net. However, if the shuffling is unjust, the anonymity,
privacy, or fairness may be compromised. In this paper, we propose the method for confirming fair
mixing by finding a fixed point in the mix system and we can keep the details on ‘how to shuffle’ secret.
This method requires only two steps and is efficient.
Class Mean Classifier is used to classify unclassified
sample vectors where the vectors are classified in more
than one class. For example, in our dataset we have some
sample vectors. Some given sample vectors are already
classified into different classes and some are not
classified. We can classify the unclassified sample
vectors by the help of Minimum Distance to Class Mean
Classifier.
Pattern Recognition - Designing a minimum distance class mean classifierNayem Nayem
“Minimum Distance to Class Mean Classifier” is used to classify unclassified sample vectors where the vectors clustered in more than one classes are given. We can classify the unclassified sample vectors with Class Mean Classifier.
“Minimum Distance to Class Mean Classifier” is used to classify unclassified sample vectors where the vectors clustered in more than one classes are given. For example, in a dataset containing n sample vectors of dimension d some given sample vectors are already clustered into classes and some are not. We can classify the unclassified sample vectors with Class Mean Classifier.
the use of digital data has been increase over the past decade which has led to the evolution of digital world. With this evolution the use of data such as text, images and other multimedia for communication purpose over network needs to be secured during transmission. Images been the most extensively used digital data throughout the world, there is a need for the security of images, so that the confidentiality, integrity and availability of the data is maintained. There is various cryptography techniques used for image security of which the asymmetric cryptography is most extensively used for securing data transmission. This paper discusses about Elliptic Curve Cryptography an asymmetric public key cryptography method for image transmission. With security it is also crucial to address the computational aspects of the cryptography methods used for securing images. The paper proposes an Image encryption and decryption method using ECC. Integrity of image transmission is achieved by using Elliptic Curve Digital Signature Algorithm (ECDSA) and also considering computational aspects at each stage.
We rely on secrets such as safe combinations, PIN codes, computer passwords, etc. But so many things happen to lose secretes.
1. Secrets can be lost.
2. Documents get destroyed.
3. Hard disks fail
4. People forget
5. People leave companies,
6. people die...
One way to avoid such problems :-
Divide secret data (D) in to pieces (n)
* Knowledge of some pieces (k) enables to derive secret data (D)
* Knowledge of any pieces (k-1) makes secret data (D) completely undetermined.
Such a scheme is called a (k, n) threshold scheme.
This presentation provides a in depth view of Shamir's Secret Sharing Scheme.
Public-Key Cryptography.pdfWrite the result of the following operation with t...FahmiOlayah
Write the result of the following operation with the correct number of significant figure of 0.248?Write the result of the following operation with the correct number of signi
Digital Differential Analyzer (DDA) algorithm is the simple line generation algorithm which is explained step by step here.
Step 1 − Get the input of two end points (X0,Y0) and (X1,Y1).
Step 2 − Calculate the difference between two end points.
dx = X1 - X0
dy = Y1 - Y0
Step 3 − Based on the calculated difference in step-2, you need to identify the number of steps to put pixel. If dx > dy, then you need more steps in x coordinate; otherwise in y coordinate.
Step 4 − Calculate the increment in x coordinate and y coordinate.
Step 5 − Put the pixel by successfully incrementing x and y coordinates accordingly and complete the drawing of the line.
HOW TO FIND A FIXED POINT IN SHUFFLE EFFICIENTLYIJNSA Journal
In electronic voting or whistle blowing, anonymity is necessary. Shuffling is a network security technique
that makes the information sender anonymous. We use the concept of shuffling in internet-based lotteries,
mental poker, E-commerce systems, and Mix-Net. However, if the shuffling is unjust, the anonymity,
privacy, or fairness may be compromised. In this paper, we propose the method for confirming fair
mixing by finding a fixed point in the mix system and we can keep the details on ‘how to shuffle’ secret.
This method requires only two steps and is efficient.
Class Mean Classifier is used to classify unclassified
sample vectors where the vectors are classified in more
than one class. For example, in our dataset we have some
sample vectors. Some given sample vectors are already
classified into different classes and some are not
classified. We can classify the unclassified sample
vectors by the help of Minimum Distance to Class Mean
Classifier.
Pattern Recognition - Designing a minimum distance class mean classifierNayem Nayem
“Minimum Distance to Class Mean Classifier” is used to classify unclassified sample vectors where the vectors clustered in more than one classes are given. We can classify the unclassified sample vectors with Class Mean Classifier.
“Minimum Distance to Class Mean Classifier” is used to classify unclassified sample vectors where the vectors clustered in more than one classes are given. For example, in a dataset containing n sample vectors of dimension d some given sample vectors are already clustered into classes and some are not. We can classify the unclassified sample vectors with Class Mean Classifier.
the use of digital data has been increase over the past decade which has led to the evolution of digital world. With this evolution the use of data such as text, images and other multimedia for communication purpose over network needs to be secured during transmission. Images been the most extensively used digital data throughout the world, there is a need for the security of images, so that the confidentiality, integrity and availability of the data is maintained. There is various cryptography techniques used for image security of which the asymmetric cryptography is most extensively used for securing data transmission. This paper discusses about Elliptic Curve Cryptography an asymmetric public key cryptography method for image transmission. With security it is also crucial to address the computational aspects of the cryptography methods used for securing images. The paper proposes an Image encryption and decryption method using ECC. Integrity of image transmission is achieved by using Elliptic Curve Digital Signature Algorithm (ECDSA) and also considering computational aspects at each stage.
We rely on secrets such as safe combinations, PIN codes, computer passwords, etc. But so many things happen to lose secretes.
1. Secrets can be lost.
2. Documents get destroyed.
3. Hard disks fail
4. People forget
5. People leave companies,
6. people die...
One way to avoid such problems :-
Divide secret data (D) in to pieces (n)
* Knowledge of some pieces (k) enables to derive secret data (D)
* Knowledge of any pieces (k-1) makes secret data (D) completely undetermined.
Such a scheme is called a (k, n) threshold scheme.
This presentation provides a in depth view of Shamir's Secret Sharing Scheme.
Public-Key Cryptography.pdfWrite the result of the following operation with t...FahmiOlayah
Write the result of the following operation with the correct number of significant figure of 0.248?Write the result of the following operation with the correct number of signi
BREAKING MIGNOTTE’S SEQUENCE BASED SECRET SHARING SCHEME USING SMT SOLVERijcsit
The secret sharing schemes are the important tools in cryptography that are used as building blocks in
many secured protocols. It is a method used for distributing a secret among the participants in a manner
that only the threshold number of participants together can recover the secret and the remaining set of
participants cannot get any information about the secret. Secret sharing schemes are absolute for storing
highly sensitive and important information. In a secret sharing scheme, a secret is divided into several
shares. These shares are then distributed to the participants’ one each and thus only the threshold (t)
number of participants can recover the secret. In this paper we have used Mignotte’s Sequence based
Secret Sharing for distribution of shares to the participants. A (k, m) Mignotte's sequence is a sequence of
pair wise co-prime positive integers. We have proposed a new method for reconstruction of secret even
with t-1 shares using the SMT solver.
The secret sharing schemes are the important tools in cryptography that are used as building blocks in many secured protocols. It is a method used for distributing a secret among the participants in a manner that only the threshold number of participants together can recover the secret and the remaining set of participants cannot get any information about the secret. Secret sharing schemes are absolute for storing highly sensitive and important information. In a secret sharing scheme, a secret is divided into several shares. These shares are then distributed to the participants’ one each and thus only the threshold (t) number of participants can recover the secret. In this paper we have used Mignotte’s Sequence based Secret Sharing for distribution of shares to the participants. A (k, m) Mignotte's sequence is a sequence of pair wise co-prime positive integers. We have proposed a new method for reconstruction of secret even with t-1 shares using the SMT solver.
The secret sharing schemes are the important tools in cryptography that are used as building blocks in many secured protocols. It is a method used for distributing a secret among the participants in a manner that only the threshold number of participants together can recover the secret and the remaining set of participants cannot get any information about the secret. Secret sharing schemes are absolute for storing highly sensitive and important information. In a secret sharing scheme, a secret is divided into several shares. These shares are then distributed to the participants’ one each and thus only the threshold (t) number of participants can recover the secret. In this paper we have used Mignotte’s Sequence based Secret Sharing for distribution of shares to the participants. A (k, m) Mignotte's sequence is a sequence of pair wise co-prime positive integers. We have proposed a new method for reconstruction of secret even with t-1 shares using the SMT solver.
DYNAMIC SESSION KEY EXCHANGE METHOD USING TWO S-BOXESIJCSEA Journal
This paper presents modifications of the Diffie-Hellman (DH) key exchange method. The presented modifications provide better security than other key exchange methods. We are going to present a dynamic security that simultaneously realizes all the three functions with a high efficiency and then give a security analysis. It also presents secure and dynamic key exchange method. Signature, encryption and key exchange are some of the most important and foundational Crypto-graphical tools. In most cases, they are all needed to provide different secure functions. On the other hand, there are also some proposals on the efficient combination of key exchange. In this paper, we present a dynamic, reliable and secure method for the exchange of session key. Moreover, the proposed modification method could achieve better performance efficiency.
Implementation of RSA Algorithm with Chinese Remainder Theorem for Modulus N ...CSCJournals
Cryptography has several important aspects in supporting the security of the data, which
guarantees confidentiality, integrity and the guarantee of validity (authenticity) data. One of the
public-key cryptography is the RSA cryptography. The greater the size of the modulus n, it will be
increasingly difficult to factor the value of n. But the flaws in the RSA algorithm is the time
required in the decryption process is very long. Theorem used in this research is the Chinese
Remainder Theorem (CRT). The goal is to find out how much time it takes RSA-CRT on the size
of modulus n 1024 bits and 4096 bits to perform encryption and decryption process and its
implementation in Java programming. This implementation is intended as a means of proof of
tests performed and generate a cryptographic system with the name "RSA and RSA-CRT Text
Security". The results of the testing algorithm is RSA-CRT 1024 bits has a speed of
approximately 3 times faster in performing the decryption. In testing the algorithm RSA-CRT 4096
bits, the conclusion that the decryption process is also effective undertaken more rapidly.
However, the flaws in the key generation process and the RSA 4096 bits RSA-CRT is that the
time needed is longer to generate the keys.
RSA always uses two big prime numbers to deal with the encryption process. The public key is obtained from the multiplication of both figures. However, we can break it by doing factorization to split the public key into two individual numbers. Cryptanalysis can perform the public key crack by knowing its value. The private key will be soon constructed after the two numbers retrieved. The public key is noted as “N”, while "N = P . Q". This technique is unclassified anymore to solve the RSA public and private key. If it is successfully factored into p and q then ɸ (N) = (P - 1) . (Q - 1) can be further calculated. By having the public key e, the private key d will be solved. Factorization method is the best way to do the demolition. This study concerns to numbers factorization. GCD calculation will produce the encryption "E" and decryption "D" keys, but it depends on the computer speed.
traditional private/secret/single key cryptography uses one key
Key is shared by both sender and receiver
if the key is disclosed communications are compromised
also known as symmetric, both parties are equal
hence does not protect sender from receiver forging a message & claiming is sent by sender
1. International Journal of Pure and Applied Mathematics
Volume 87 No. 2 2013, 349-354
ISSN: 1311-8080 (printed version); ISSN: 1314-3395 (on-line version)
url: http://www.ijpam.eu
doi: http://dx.doi.org/10.12732/ijpam.v87i2.15
PAijpam.eu
AUTHENTICATED MULTIPLE KEY
DISTRIBUTION USING SIMPLE CONTINUED FRACTION
S. Srinivasan1, P. Muralikrishna2 §, N. Chandramowliswaran3
1,2School of Advanced Sciences
VIT University
Vellore, 632014, Tamilnadu. INDIA
3Visiting Faculty
Indian Institute of Management Indore
Indore, 453 331, INDIA
Abstract: In resent years the security of operations taking place over a com-
puter network become very important. It is necessary to protect such actions
against bad users who may try to misuse the system (e.g. steal credit card
numbers, read personal mail, or impersonate other users.) Many protocols and
schemes were designed to solve problem of this type. Threshold cryptography
is a novel cryptographic technique sharing secret among members. It divides
a secret key into multiple shares by a cryptographic operation. In this paper,
we proposed a key distribution algorithm based on Simple Continued Fraction.
The goal of our algorithm is to divide a secret S into ℓ pieces s1 + s2 + · · · + sℓ
such that, ℓ pieces are necessary to reconstruct S, but any m < ℓ pieces give
no information about S.
AMS Subject Classification: 94A60, 94A62
Key Words: simple continued fraction, shares, RSA prime
1. Introduction
Secret sharing (also called secret splitting) refers to method for distributing a
Received: June 15, 2013 c 2013 Academic Publications, Ltd.
url: www.acadpubl.eu
§Correspondence author
2. 350 S. Srinivasan, P. Muralikrishna, N. Chandramowliswaran
secret amongst a group of participants, each of whom is allocated a share of
the secret. The secret can be reconstructed only when a sufficient number, of
possibly different types, of shares are combined together; individual shares are
of no use on their own.
Secret sharing was invented independently by Adi Shamir [3] and George
Blakley [1] in 1979. Secret sharing schemes are ideal for storing information
that is highly sensitive and highly important. Examples include: encryption
keys, missile launch codes and numbered bank accounts. Each of these pieces of
information must be kept highly confidential, as their exposure could be disas-
trous, however, it is also critical that they not be lost. Traditional methods for
encryption are ill-suited for simultaneously achieving high levels of confidential-
ity and reliability. This is because when storing the encryption key, one must
choose between keeping a single copy of the key in one location for maximum
secrecy, or keeping multiple copies of the key in different locations for greater
reliability. Increasing reliability of the key by storing multiple copies lowers
confidentiality by creating additional attack vectors; there are more opportu-
nities for a copy to fall into the wrong hands. Secret sharing schemes address
this problem, and allow arbitrarily high levels of confidentiality and reliability
to be achieved.
A secure secret sharing scheme distributes shares so that anyone with fewer
than t shares has no extra information about the secret than someone with 0
shares.
Consider for example the secret sharing scheme in which the secret phrase
security is divided into the shares se−−−−−−, −−cu−−−−, −−−−ri−−,
and −−−−−−ty. A person with 0 shares knows only that the password consists
of eight letters. He would have to guess the password from 268 = 208 billion
possible combinations. A person with one share, however, would have to guess
only the six letters, from 266 = 308 million combinations, and so on as more
persons collude. Consequently this system is not a secure secret sharing scheme,
because a player with fewer than t secret-shares is able to reduce the problem
of obtaining the inner secret without first needing to obtain all of the necessary
shares.
2. Proposed Algorithms
Construction of the Non-Homogeneous Equation
Definition An expression of the form C0 + 1
C1+
1
C2+
1
C3+ . . . 1
+Cn
. . . where Cj :
3. AUTHENTICATED MULTIPLE KEY... 351
j ≥ 1 are positive integers and C0 is a non-negative integer is called a Simple
Continued Fraction (SCF).
• Define P1
Q1
= C0
1
P2
Q2
= C0 + 1
C1
= C0C1+1
C1
P3
Q3
= C0 + 1
C1+ 1
C2
= C0[C1C2+1]+C2
C1C2+1
• In general, we have
Pn+1
Qn+1
= C0 + 1
C1+
1
C2+
1
C3+ . . . 1
+Cn
(1)
= C0 + 1
C1+ 1
C2+ 1
C3+···+ 1
Cn−1+ 1
Cn
(2)
then, Pn+1
Qn+1
is called (n + 1)th convergent of SCF
• Let us denote C0 + 1
C1+
1
C2+
1
C3+ . . . 1
+Cn
by [C0; C1, C2, C3, . . . , Cn−1, Cn]
i.e., Pn+1
Qn+1
= [C0; C1, C2, C3, . . . , Cn−1, Cn] (3)
• Alternatively, we can represent SCF as the product of special 2 × 2 ma-
trices over non-negative integers
C0 1
1 0
C1 1
1 0 . . . Cn 1
1 0 =
Pn+1 Pn
Qn+1 Qn
(4)
• Taking determinant on both sides of (4), we get
(−1)n+1 = Pn+1Qn − Qn+1Pn for all n ≥ 1 (5)
• Taking transpose of (4), we get
Cn 1
1 0
Cn−1 1
1 0
. . . C0 1
1 0 = Pn+1 Qn+1
Pn Qn
• Let R1, R2 be two given very large odd primes with R1 < R2
• Represent R1
R2
as a SCF
R1
R2
= C0 + 1
C1+
1
C2+
1
C3+ . . . 1
+Cn
= [C0; C1, C2, C3, . . . , Cn−1, Cn] (6)
• Consider the symmetric continue fraction of length 2n + 2
P2n+2
Q2n+2
= [Cn; Cn−1, Cn−2, . . . , C1, C0, C0; C1, C2, C3, . . . , Cn−1, Cn] (7)
where Pi
Qi
be the ith convergent of (7)
• Pn+1
Qn+1
= [Cn; Cn−1, Cn−2, . . . , C1, C0]
Pn
Qn
= [Cn; Cn−1, Cn−2, . . . , C1]
Pn+1
Pn
= [C0; C1, C2, C3, . . . , Cn−1, Cn]
Qn+1
Qn
= [C0; C1, C2, C3, . . . , Cn−1]
4. 352 S. Srinivasan, P. Muralikrishna, N. Chandramowliswaran
• Therefore
Cn 1
1 0
Cn−1 1
1 0
. . . C1 1
1 0
C0 1
1 0
C0 1
1 0
C1 1
1 0 . . . Cn 1
1 0
=
P2n+2 P2n+1
Q2n+2 Q2n+1
=A (8)
• Clearely, det(A) = (−1)2n+2 = 1
• Consider
Cn 1
1 0
Cn−1 1
1 0
. . . C1 1
1 0
C0 1
1 0
C0 1
1 0
C1 1
1 0 . . . Cn 1
1 0
= [Cn; Cn−1, . . . , C1, C0, C0; C1, C2, . . . , Cn−1Cn]
=
Pn+1 Pn
Qn1 Qn
Pn+1 Qn+1
Pn Qn
=
P 2
n+1+P 2
n Pn+1Qn+1+PnQn
Pn+1Qn+1+PnQn Q2
n+1+Q2
n
=
P2n+2 P2n+1
Q2n+2 Q2n+1
• P2n+2Q2n+1 − P2n+1Q2n+2 = 1
(P2
n+1 + P2
n )Q2n+1 = P2
2n+1 + 1
(R2
1 + R2
2)Y = X2 + 1
where Pn+1 = R1, Pn = R2, P2n+1 = X and Q2n+1 = Y
Here, we proposed an algorithm and its actual implementation. Our pri-
mary contribution is that, in our algorithm we discussed the key sharing by
using two prime numbers and a non-homogeneous equation with two variables.
The share holders can verify the validity of their shares only after reconstruc-
tion of the secret and any share holders fewer than ℓ, can not reconstruct the
secret.
Algorithm for Encryption
• Choose two secret very large odd primes R1, R2 with R1 > R2
• Construct x2 + 1 = (R2
1 + R2
2)y
• Select two large RSA secret odd primes p and q
• Define N = pq then φ(N) = (p − 1)(q − 1) where φ(N) is Euler phi
function
• Select a secret exponent e such that (e, φ(N)) = 1 where 1 < e < φ(N)
• For this e, there is a unique d such that ed ≡ 1(mod φ(N))
5. AUTHENTICATED MULTIPLE KEY... 353
• consider a = (R2
1 + R2
2)(y + d) − (x + φ(N))2
a = (R2
1 + R2
2)y − x2 + (R2
1 + R2
2)d − [φ(N)]2 − 2xφ(N)
= 1 + (R2
1 + R2
2)d − [φ(N)]2 − 2xφ(N)
a ≡ (1 + (R2
1 + R2
2)d) (mod φ(N))
ae ≡ (e + (R2
1 + R2
2)) (mod φ(N))
S ≡ e(mod φ(N)) where S = ae − (R2
1 + R2
2)
• Here we define S is the exponent secret
• Represent the secret message m in the interval [0, N − 1]
with gcd(m, N) = 1
Algorithm for Key Sharing
• Consider the ℓ exponent secret partition (share holders)
S = s1 + s2 + · · · + sℓ
Define Yi ≡ msi (mod N) for 1 ≤ i ≤ ℓ
ℓ
1 Yi ≡ mS(mod N)
≡ ms1+s2+···+sℓ (mod N)
≡ ms1 ms2 . . . msℓ (mod N)
• For ℓ secret share holders we can distribute ℓ key’s such as Y1, Y2, . . . , Yℓ
• Sharing scheme follows from the given equations:
ℓ
1 Yi ≡ mS(mod N)
6. 354 S. Srinivasan, P. Muralikrishna, N. Chandramowliswaran
≡ mkφ(N)+e(mod N)
≡ mkφ(N)me(mod N)
≡ [mφ(N)]kme(mod N)
ℓ
1 Yi ≡ me(mod N)
• High Level Authentication Key manager is d
( ℓ
1 Yi)d ≡ (me)d(mod N)
( ℓ
1 Yi)d ≡ m(mod N)
3. Conclusion
This paper dealt with a secret key sharing mechanism on ℓ share holders. Ac-
cording to the algorithm, the secret can be well shared with feasible sense, it
may have some performance impact when the number of share holders is ac-
cordingly increased. Our approach to secret sharing is opened a number of
avenues for future work. These include research into finding schemes that will
remove the restrictions on the size of ℓ. These schemes make it possible to store
secret information in a network.
References
[1] Adi Shamir, How to share a secret, Communications of the ACM, 22, No.
11 (1979), 612-613.
[2] A. Beimel, Secret-sharing schemes: a survey, In: Proceedings of the Third
International Conference on Coding and Cryptology, Berlin, Heidelberg,
2011, Springer-Verlag, IWCC’11, 11-46.
[3] G.R. Blakley, Safeguarding cryptographic keys, Proceedings of the National
Computer Conference, 48 (1979), 313-317.
[4] P. Muralikrishna, S. Srinivasan, N. Chandramowliswaran, Secure schemes
for secret sharing and key distribution using Pell’s equation, Interna-
tional Journal of Pure and Applied Mathematics, 85, No. 5, 33-937, doi:
10.12732/ijpam.v85i5.11.
[5] Ivan Niven, Herbert S. Zuckerman, Hugh L. Montgomery, An Introduction
to the Theory of Numbers, John Wiley.
[6] Tom M. Apostol, Introduction to Analytic Number Theory, Springer.