We study the problem of maintaining the vertex connectivity $κ$ of a graph under edge insertions. For undirected graphs, our algorithm uses $O(κ^4 \log^2 n)$ amortized time per edge insertion. After each edge insertion, the algorithm outputs the current value of $κ$, plus a set of $κ$ vertices whose removal disconnects the graph. Our algorithm is Monte-Carlo randomized and works with a randomness-adaptive adversary. The algorithm also works on directed graphs against an oblivious adversary, which is equivalent to an output-adaptive adversary if we only have to output the current value of $κ$. Previously, algorithms for maintaining the vertex connectivity with $o(n)$ time per edge insertion were only known for $κ\le 2$, and need $\tilde{O}(\log^2 n)$ and $O(\sqrt{n})$ time per edge insertion for $κ= 1,2$, respectively. Moreover, for $κ> 4$, no algorithm faster than recomputation from scratch was known. We complement our algorithm with a conditional lower bound: Under the OMv conjecture, any insertions-only algorithm that outputs the current value of $κ$ after every insertion needs $Ω(n^{1-\varepsilon})$ amortized time per edge insertion for $κ= Θ(n)$. Previous conditional lower bounds for this problem only apply to worst case running time, or algorithms that support both edge insertions and edge deletions.

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