As software continues to eat the world, there is an increasing pressure to
automate every aspect of society, from self-driving cars, to algorithmic trading
on the stock market. As this pressure manifests into software implementations
of everything, there are security concerns to be addressed across many areas.
But are there some domains and fields that are distinctly susceptible to attacks,
making them difficult to secure?
My dissertation argues that one domain in particular—public policy and law—
is inherently difficult to automate securely using computers. This is in large part
because law and policy are written in a manner that expects them to be flexibly
interpreted to be fair or just. Traditionally, this interpreting is done by judges
and regulators who are capable of understanding the intent of the laws they are
enforcing. However, when these laws are instead written in code, and interpreted
by a machine, this capability to understand goes away. Because they blindly fol-
low written rules, computers can be tricked to perform actions counter to their
intended behavior.
This dissertation covers three case studies of law and policy being implemented
in code and security vulnerabilities that they introduce in practice. The first study
analyzes the security of a previously deployed Internet voting system, showing
how attackers could change the outcome of elections carried out online. The second study looks at airport security, investigating how full-body scanners can be
defeated in practice, allowing attackers to conceal contraband such as weapons or
high explosives past airport checkpoints. Finally, this dissertation also studies how
an Internet censorship system such as China’s Great Firewall can be circumvented
by techniques that exploit the methods employed by the censors themselves.
To address these concerns of securing software implementations of law, a hybrid human-computer approach can be used. In addition, systems should be designed to allow for attacks or mistakes to be retroactively undone or inspected by
human auditors. By combining the strengths of computers (speed and cost) and
humans (ability to interpret and understand), systems can be made more secure
and more efficient than a method employing either alone.PhDComputer Science and EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/120795/1/ewust_1.pd
