コード例 #1
0
        public void GenerateRandomVector(BigInteger p, double l0)
        {
            long len = (long)Math.Ceiling(3.0 * l0 / 8.0) + 1;

            byte[] rndBytes = new byte[len];

            for (long i = 0; i < rowsCount; i++)
            {
                rnd.NextBytes(rndBytes);
                BigInteger num = new BigInteger(rndBytes);
                Mat[i, i] = MathClass.mod(num, p);
            }
        }
コード例 #2
0
        //---- Gauss Jordan Matrix Mod-Inverse ---
        public BigIntMatrix GaussJordanModInverse(BigInteger p)
        {
            BigIntMatrix workMat = new BigIntMatrix(2 * rowsCount, 2 * colsCount);
            //--- build work matrix ---
            long n = this.rowsCount;

            for (long i = 0; i < n; i++)
            {
                for (long j = 0; j < n; j++)
                {
                    workMat.Mat[i, j] = this.Mat[i, j];
                }
                workMat.Mat[i, i + n] = 1;
            }

            // --- partial pivoting ---
            for (long i = n - 1; i > 0; i--)
            {
                if (workMat.Mat[i - 1, 0] < workMat.Mat[i, 0])
                {
                    for (long j = 0; j < 2 * n; j++)
                    {
                        BigInteger d = workMat.Mat[i, j];
                        workMat.Mat[i, j]     = workMat.Mat[i - 1, j];
                        workMat.Mat[i - 1, j] = d;
                    }
                }
            }

            // --- reducing to diagnoal matrix ---
            for (int i = 0; i < n; i++)
            {
                BigInteger mi = MathClass.EEA(workMat.Mat[i, i], p);
                for (int j = 0; j < 2 * n; j++)
                {
                    if (i != j)
                    {
                        BigInteger d = workMat.Mat[j, i] * mi;
                        for (int k = 0; k < 2 * n; k++)
                        {
                            workMat.Mat[j, k] = MathClass.mod(workMat.Mat[j, k] - workMat.Mat[i, k] * d, p);
                        }
                    }
                }
            }

            BigIntMatrix result = new BigIntMatrix(rowsCount, colsCount);

            //--- reducing to unit matrix ---
            for (int i = 0; i < n; i++)
            {
                BigInteger d = MathClass.EEA(workMat.Mat[i, i], p);
                for (int j = 0; j < 2 * n; j++)
                {
                    workMat.Mat[i, j] = workMat.Mat[i, j] * d;
                }

                for (int j = 0; j < n; j++)
                {
                    //--- check whether matrix is inversible or not ---
                    if (i != j && workMat.Mat[i, j] != 0)
                    {
                        throw new System.ArgumentException("ERROR: Matrix is not inversible...", "Matrix inversion error");
                    }

                    result.Mat[i, j] = MathClass.mod(workMat.Mat[i, j + n], p);
                }
            }

            return(result);
        }
        private void btnSetupRequest_Click(object sender, EventArgs e)
        {
            txtReturnTime.Text     = "0";
            txtResult.Text         = "-";
            btnSendRequest.Enabled = false;

            n       = frmParent.n;
            this.i0 = (int)nud_i0.Value;
            int NI = 1;

            while ((Math.Ceiling(Math.Log(n * NI)) + 1) * NI < frmParent.ll)
            {
                NI++;
            }
            N = NI;

            l0             = (int)Math.Ceiling(Math.Log(n * N)) + 1;
            q              = BigInteger.Pow(2, 2 * l0);
            p              = MathClass.GenerateLargePrime(l0);
            nud_i0.Maximum = n;

            txtN.Text   = N.ToString();
            txt_n.Text  = n.ToString();
            txt_p.Text  = p.ToString();
            txt_q.Text  = q.ToString();
            txt_l0.Text = l0.ToString();

            Stopwatch sw = new Stopwatch();

            sw.Start();

            MPrime = new BigIntMatrix[n];
            A      = new BigIntMatrix(N, N);
            B      = new BigIntMatrix(N, N);
            Delta  = new BigIntMatrix(N, N);
            invA   = A.GenerateRandomInvertibleMatrix(p, l0, false);
            B.GenerateRandomMatrix(p, l0);

            M        = A.Append(B, BigIntMatrix.AppendMode.Beside);
            invDelta = Delta.GenerateRandomInvertibleMatrix(p, l0, true);

            txtLog.AppendText(A.Print("A"));
            txtLog.AppendText(B.Print("B"));
            txtLog.AppendText(M.Print("M"));
            txtLog.AppendText(Delta.Print("Delta"));

            BigIntMatrix P, Ai, Bi, D;

            P  = new BigIntMatrix(N, N);
            D  = new BigIntMatrix(N, N);
            Ai = new BigIntMatrix(N, N);
            Bi = new BigIntMatrix(N, N);
            txtLog.AppendText("\r\n>>> N: " + N.ToString());
            txtLog.AppendText("\r\n---------------------------- Matrix Operations Started --------------------------");
            Stopwatch swMat = new Stopwatch();

            swMat.Start();
            for (long i = 0; i < n; i++)
            {
                // --- M Jegon ---
                //---P.GenerateRandomInvertibleMatrix(p, l0, false);
                P.GenerateRandomMatrix(p, l0);
                // --- Soft Noise Matrix D ---
                D.GenerateSoftNoiseMatrix();
                // --- hard noise ---
                if (i == i0)
                {
                    D.GenerateHardNoiseMatrix(q);
                }
                else
                {
                    D.GenerateSoftNoiseMatrix();
                }

                Ai        = P * A;
                Bi        = (P * B) + (D * Delta);
                MPrime[i] = Ai.Append(Bi, BigIntMatrix.AppendMode.Beside) % p;
            }
            swMat.Stop();
            MatrixProcessTime = swMat.ElapsedMilliseconds;
            txtLog.AppendText("\r\n>>> Matrix Process Duration: " + MatrixProcessTime.ToString());
            txtLog.AppendText("\r\n---------------------------- Matrix Operations Finished --------------------------");

            // --- make permutation & depermiutation vector ---
            Random     rnd        = new Random(DateTime.Now.Millisecond);
            List <int> tmpList    = new List <int>();
            List <int> permutList = new List <int>();

            dePermutList.Clear();
            for (int i = 0; i < 2 * N; i++)
            {
                tmpList.Add(i);
                dePermutList.Add(0);
            }

            int j = 0;

            while (tmpList.Count > 0)
            {
                int i = rnd.Next(tmpList.Count);
                permutList.Add(tmpList[i]);
                dePermutList[tmpList[i]] = j++;
                tmpList.RemoveAt(i);
            }

            Ms = permute(MPrime, n, permutList, N);

            sw.Stop();
            Protocol1Time          = sw.ElapsedMilliseconds;
            btnSendRequest.Enabled = true;
            txtLog.AppendText("\r\n---------------------------- Request has been sent to the server --------------------------");
        }
        private void btnSendRequest_Click(object sender, EventArgs e)
        {
            BigIntMatrix V = frmParent.getAndProcessRequest(Ms, l0, N, p);

            //MessageBox.Show("Your request has been sent to the server...", "request is on going", MessageBoxButtons.OK, MessageBoxIcon.Information);
            txtLog.AppendText("\r\n---------------------------- Server Respond to the query ------------------------------------");
            txtLog.AppendText(V.Print("Result Vector from server"));

            //--- DePermute V ---
            Stopwatch sw = new Stopwatch();

            sw.Start();

            BigIntMatrix VPrime = Depermute(V, dePermutList, N);

            BigIntMatrix undisturbedHalf = VPrime.GetSubMatrix(0, 1, 0, N);
            //BigIntMatrix invA = A.ModInverse(p);
            //***---- BigIntMatrix invA = A.GaussJordanModInverse(p);

            BigIntMatrix resultHalf        = undisturbedHalf * invA * B % p;
            BigIntMatrix undisturbedVector = undisturbedHalf.Append(resultHalf, BigIntMatrix.AppendMode.Beside);
            BigIntMatrix ScrambledNoise    = (VPrime - undisturbedVector) % p;

            //BigIntMatrix invDelta = Delta.ModInverse(p);
            //***---- invDelta = Delta.GaussJordanModInverse(p);

            BigIntMatrix halfScrambledNoise = ScrambledNoise.GetSubMatrix(0, 1, N, N);
            BigIntMatrix unScrambledNoise   = halfScrambledNoise * invDelta % p;

            //BigInteger[] eea = MyClass.Extended_GCD(q, p);
            //---BigInteger qInv = MathClass.NumberModInverse(q, p);
            BigInteger qInv = MathClass.EEA(q, p);

            //long qInv = (long)eea[1];

            BigInteger[,] eJegon = new BigInteger[1, N];
            for (int i = 0; i < N; i++)
            {
                BigInteger epsilon = MathClass.mod(unScrambledNoise.GetElement(0, i), q);
                if (epsilon >= q / 2)
                {
                    epsilon -= q;
                }
                eJegon[0, i]  = MathClass.mod(unScrambledNoise.GetElement(0, i) - epsilon, p);
                eJegon[0, i] *= qInv;// % p;//MyClass.mod((long)eJegon[0, i] * qInv, p);
            }

            //Matrix<double> ResultVector = Matrix<double>.Build.DenseOfArray(eJegon).Multiply(qInv).Modulus(p);
            BigIntMatrix ResultVector = new BigIntMatrix(eJegon).Modulus(p);

            BigInteger[] resVect = new BigInteger[N];
            for (int i = 0; i < N; i++)
            {
                resVect[i] = ResultVector.GetElement(0, i);
            }

            BigInteger result = 0;

            for (int i = 0; i < N; i++)
            {
                result <<= l0;
                result  += resVect[i];
            }

            sw.Stop();
            Protocol3Time = sw.ElapsedMilliseconds;
            txtLog.AppendText(ResultVector.Print("Obtained Result Vector"));
            txtLog.AppendText(invA.Print("Inv A"));
            txtLog.AppendText(invDelta.Print("Inv Delta"));
            txtLog.AppendText("\r\n>>>>>>>>>> Inv q = " + qInv.ToString());
            txtLog.AppendText("\r\n>>>>>>>>>> Obtained Result for index(" + i0.ToString() + "): " + result.ToString());
            txtLog.AppendText("\r\n--------------------------------------------- Timing ----------------------------------------------------");
            long totalDuration = Protocol1Time + Protocol3Time + frmParent.Protocol2Time;

            txtLog.AppendText("\r\n>>> Protocol 1 Duration: " + Protocol1Time.ToString());
            txtLog.AppendText("\r\n>>> Protocol 2 Duration: " + frmParent.Protocol2Time.ToString());
            txtLog.AppendText("\r\n>>> Protocol 3 Duration: " + Protocol3Time.ToString());
            txtLog.AppendText("\r\n>>> Total Duration: " + totalDuration.ToString());
            txtLog.AppendText("\r\n>>> Matrix Process Duration: " + MatrixProcessTime.ToString());
            txtLog.AppendText("\r\n>>> Deference check: " + (frmParent.getValueByIndex(i0) - result).ToString());
            txtLog.AppendText("\r\n--------------------------------------------- Timing ----------------------------------------------------");

            txtResult.Text     = result.ToString();
            txtReturnTime.Text = totalDuration.ToString();
            MessageBox.Show("Query process has been finished successfully...", "Query Operation", MessageBoxButtons.OK, MessageBoxIcon.Information);
        }