Erin cracks the code to the dreaming spires of Oxford
When it comes to computer passwords, Erin Chapman doesn’t take chances.
That means complicated, regularly-rotated combinations, not using the same one for any two websites, and steering well clear of password-storing software.
It might be that she’s slightly paranoid about hackers.
Or it might be that she’s a cryptography whiz who’s just landed a coveted spot in a worldrenowned cyber security programme at Oxford University.
The 25-year-old Aucklander, who has just completed a Masters in Computing and Information Sciences at AUT University, has a rare mind hard-wired to navigate complex algorithms in a way that even the most mathematically savvy of us would struggle to.
In the past few years, she’s turned it toward cryptology — the art of writing and breaking codes, the kind of algorithms that protect us when we log into our online bank accounts.
A voracious reader, she’d first studied English literature and ancient history before switching to a Bachelor of Science and Computer Science at the University of Auckland. Later, at AUT, she took a cryptography course which taught her about early codes and ciphers. Sudoku puzzles and UK science writer Simon Singh’s The Code Book.
When she asked her AUT lecturer, Dr Brian Cusack, about where to study next, Chapman was stunned to hear him suggest Oxford, the second oldest and regularly topranked university in the world.
“They’ve got a really great cyber security programme there . . . but I thought it was [an] insane idea.”
Still, she became one of 16 out of 100 applicants picked for the course.
“When they told me I’d got in, I was really stoked,” she said.
Ultimately, she’d love to become an academic specialising in cryptography, rather than a private sector code-maker.
While major ransomware attacks like the WannaCry cryptoworm which this month infected more than 230,000 computers in 150 countries had increasingly put cyber security in the spotlight, Chapman said it was the global explosion in “big data” that would pose the big challenge to people like herself.
“The sheer scale of the data we are generating today means that we’ve got to look at the efficiency of the algorithms that protect it, and not just the strengths.
“Because the stronger you make the algorithm, the longer it’s going to take, and you have to ask — how do we make this realistic and what are we willing to sacrifice.”