根据GMT005更新了10^6数据组检测工具的相关检测参数

Trisia · Oct 28, 2022 · 6736c66 · 6736c66
1 parent a041a54
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diff --git a/README.md b/README.md
@@ -74,23 +74,23 @@ func main() {
 
 各算法检测参数如下：
 
-序号 | 检测项目 | 参数 |
---- | --- | --- |
-1 | 单比特频数检测  | - |
-2 | 块内频数检测   | m = 100 |
-3 | 扑克检测     | m = 8 |
-4 | 重叠子序列检测  | m = 5 |
-5 | 游程总数检测   | - |
-6 | 游程分布检测   | - |
-7 | 块内最大游程检测 | m = 10000 |
-8 | 二元推导检测   | k = 7 |
-9 | 自相关检测    | d = 16 |
-10 |  矩阵秩检测   | M = 32, Q= 32 |
-11 |  累加和检测   | - |
-12 |  近似熵检测   | m = 5 |
-13 |  线型复杂度检测 | m = 500 |
-14 |  Maurer通用统计检测  | - |
-15 |  离散傅里叶检测 | - |
+序号 | 检测项目 | 参数           |
+--- | --- |--------------|
+1 | 单比特频数检测  | -            |
+2 | 块内频数检测   | m = 10000    |
+3 | 扑克检测     | m = 4,8      |
+4 | 重叠子序列检测  | m = 3,5      |
+5 | 游程总数检测   | -            |
+6 | 游程分布检测   | -            |
+7 | 块内最大游程检测 | m = 10000    |
+8 | 二元推导检测   | k = 3,7      |
+9 | 自相关检测    | d = 1,2,8,16 |
+10 |  矩阵秩检测   | -            |
+11 |  累加和检测   | -            |
+12 |  近似熵检测   | m = 2,5      |
+13 |  线型复杂度检测 | m = 500,1000 |
+14 |  Maurer通用统计检测  | L=7,Q=1280   |
+15 |  离散傅里叶检测 | -            |
 
 
 ## 工具

diff --git a/overlapping.go b/overlapping.go
@@ -28,8 +28,9 @@ func OverlappingTemplateMatching(data []byte) *TestResult {
 // OverlappingTemplateMatchingTest 重叠子序列检测方法,m=5
 // bits: 检测序列
 // return:
-//      p1: P-value1
-//      p2: P-value2
+//
+//	p1: P-value1
+//	p2: P-value2
 func OverlappingTemplateMatchingTest(bits []bool) (p1 float64, p2 float64, q1 float64, q2 float64) {
 	return OverlappingTemplateMatchingProto(bits, 5)
 }
@@ -38,18 +39,20 @@ func OverlappingTemplateMatchingTest(bits []bool) (p1 float64, p2 float64, q1 fl
 // data: 检测序列
 // m: m长度,m=2,5
 // return:
-//      p1: P-value1
-//      p2: P-value2
+//
+//	p1: P-value1
+//	p2: P-value2
 func OverlappingTemplateMatchingTestBytes(data []byte, m int) (p1 float64, p2 float64, q1 float64, q2 float64) {
 	return OverlappingTemplateMatchingProto(B2bitArr(data), m)
 }
 
 // OverlappingTemplateMatchingProto 重叠子序列检测方法
 // bits: 检测序列
-// m: m长度,m=2,5
+// m: m长度,m=3,5
 // return:
-//      p1: P-value1
-//      p2: P-value2
+//
+//	p1: P-value1
+//	p2: P-value2
 func OverlappingTemplateMatchingProto(bits []bool, m int) (p1 float64, p2 float64, q1 float64, q2 float64) {
 	n := len(bits)
 	if n < 5 {

diff --git a/tools/rddetector/README.md b/tools/rddetector/README.md
@@ -32,23 +32,22 @@ rddetector -i 待检测数据目录 [-o 生成报告位置]
 
 ```
 
-15中检测方法的监测参数如下：
-
-序号 | 检测项目 | 参数 |
- --- | --- | --- |
-1 | 单比特频数检测     | - |
-2 | 块内频数检测      | m = 100 |
-3 | 扑克检测        | m = 8 |
-4 | 重叠子序列检测     | m = 5 |
-5 | 游程总数检测      | - |
-6 | 游程分布检测      | - |
-7 | 块内最大游程检测 | m = 10000 |
-8 | 二元推导检测      | k = 7 |
-9 | 自相关检测       | d = 16 |
-10 |  矩阵秩检测      | M = 32, Q= 32 |
-11 |  累加和检测      | - |
-12 |  近似熵检测      | m = 5 |
-13 |  线型复杂度检测    | m = 500 |
-14 |  通用统计检测     | - |
-15 |  离散傅里叶检测    | - |
-
+15种检测方法的检测参数如下：
+
+序号 | 检测项目 | 参数           |
+--- | --- |--------------|
+1 | 单比特频数检测  | -            |
+2 | 块内频数检测   | m = 10000    |
+3 | 扑克检测     | m = 4,8      |
+4 | 重叠子序列检测  | m = 3,5      |
+5 | 游程总数检测   | -            |
+6 | 游程分布检测   | -            |
+7 | 块内最大游程检测 | m = 10000    |
+8 | 二元推导检测   | k = 3,7      |
+9 | 自相关检测    | d = 1,2,8,16 |
+10 |  矩阵秩检测   | -            |
+11 |  累加和检测   | -            |
+12 |  近似熵检测   | m = 2,5      |
+13 |  线型复杂度检测 | m = 500,1000 |
+14 |  Maurer通用统计检测  | L=7,Q=1280   |
+15 |  离散傅里叶检测 | -            |
diff --git a/tools/rddetector/main.go b/tools/rddetector/main.go
@@ -37,7 +37,7 @@ func worker(jobs <-chan string, out chan<- *R) {
 		p, _ = randomness.PokerProto(bits, 8)
 		arr = append(arr, p)
 
-		p1, p2, _, _ := randomness.OverlappingTemplateMatchingProto(bits, 2)
+		p1, p2, _, _ := randomness.OverlappingTemplateMatchingProto(bits, 3)
 		arr = append(arr, p1, p2)
 		p1, p2, _, _ = randomness.OverlappingTemplateMatchingProto(bits, 5)
 		arr = append(arr, p1, p2)
@@ -71,7 +71,9 @@ func worker(jobs <-chan string, out chan<- *R) {
 		arr = append(arr, p)
 		p, _ = randomness.ApproximateEntropyProto(bits, 5)
 		arr = append(arr, p)
-		p, _ = randomness.LinearComplexityTest(bits)
+		p, _ = randomness.LinearComplexityProto(bits, 500)
+		arr = append(arr, p)
+		p, _ = randomness.LinearComplexityProto(bits, 1000)
 		arr = append(arr, p)
 		p, _ = randomness.MaurerUniversalTest(bits)
 		arr = append(arr, p)
@@ -144,26 +146,27 @@ func main() {
 	_, _ = w.WriteString(
 		"源数据," +
 			"单比特频数检测," +
-			"块内频数检测," +
-			"扑克检测m=4," +
-			"扑克检测m=8," +
-			"重叠子序列检测m=2 P1,重叠子序列检测m=2 P2," +
-			"重叠子序列检测m=5 P1,重叠子序列检测m=5 P2," +
+			"块内频数检测 m=10000," +
+			"扑克检测 m=4," +
+			"扑克检测 m=8," +
+			"重叠子序列检测 m=3 P1,重叠子序列检测 m=2 P2," +
+			"重叠子序列检测 m=5 P1,重叠子序列检测 m=5 P2," +
 			"游程总数检测," +
 			"游程分布检测," +
-			"块内最大”1“游程检测," +
-			"二元推导检测k=3," +
-			"二元推导检测k=7," +
-			"自相关检测d=1," +
-			"自相关检测d=2," +
-			"自相关检测d=8," +
-			"自相关检测d=16," +
+			"块内最大游程检测 m=10000," +
+			"二元推导检测 k=3," +
+			"二元推导检测 k=7," +
+			"自相关检测 d=1," +
+			"自相关检测 d=2," +
+			"自相关检测 d=8," +
+			"自相关检测 d=16," +
 			"矩阵秩检测," +
 			"累加和检测," +
-			"近似熵检测m=2," +
-			"近似熵检测m=5," +
-			"线性复杂度检测," +
-			"Maurer通用统计检测," +
+			"近似熵检测 m=2," +
+			"近似熵检测 m=5," +
+			"线性复杂度检测 m=500," +
+			"线性复杂度检测 m=1000," +
+			"Maurer通用统计检测 L=7 Q=1280," +
 			"离散傅里叶检测\n")
 	var wg sync.WaitGroup
 	var cnt = make([]int32, 25)