Algorithm 2 Authentication

Input:   D: The dimension of the vector.   L: The number of core objects.   $\Omega$: The set of core objects $\{{\Omega }^{\left(1\right)},{\Omega }^{\left(2\right)},\dots ,{\Omega }^{\left(L\right)}\}$   $ϵ$: The parameter of One-Class DBSCAN, which means that the distance is $ϵ$.   v: The vector of the new sample. Function: 1:for$j=1,2,\dots ,D$do 2: $v_j=v_j/{\sum }_k^D{v}_k$ 3:end for 4:for$i=1,2,\dots ,L$do 5: $dis=\Vert {\Omega }^{\left(i\right)}-v{\Vert }_2$ 6: if $dis\le ϵ$ then 7:  return True 8: end if 9:end for 10:return False Output:   True or False: Whether the new sample belongs to this class