Return-oriented programming (ROP) is a prevalent code reuse technique that hijacks a program's control flow by modifying its return addresses on the stack. Researchers have proposed some return address verification methods by using the message authentication code (MAC). But these approaches suffer from high performance overhead. In this article, we first propose Dislocated Stack, a new kind of stack layout in which a previous return address would be pushed onto the current stack frame and the current return address would be stored into a hardware buffer on function calls. Based on Dislocated Stack, we design two new verification approaches, Lazy Verification and Batch Verification. Lazy Verification does not verify a return address popped from stack until it is going to be used for return. Batch Verification verifies a couple of return addresses at one time. We implemented these two designs on RISC-V architecture and quantitatively analyzed their effect on QEMU. Our experiments show that Lazy Verification reduces over 99% verifications on function returns and incurs only 1.23% performance overhead; while in Batch Verification, the overhead is merely 0.78%. The result demonstrates that these two approaches are highly efficient for return address verification.

The DNS system is gradually becoming the infrastructure of many services and applications. The availability and security of the domain name resolution process must be guaranteed. We propose a graph-based formal model and a general analysis method for quantifying the name resolution process. We define metrics to quantify the availability and security of resolution process for a domain name. We conducted four measurements of the top 1 million popular domains within a one-year period. Our survey shows that for more than 50% of domains, if the most critical authoritative server of the domain name becomes unavailable or compromised, the probability of resolution failure or insecure answer is over 50%.

We compare the performance of seven methods in computing or approximating service levels for nonstationary M(t)/M/s(t) queueing systems: an exact method (a Runge-Kutta ordinary-differential-equation solver), the randomization method, a closure (or surrogate-distribution) approximation, a direct infinite-server approximation, a modified-offered-load infinite-server approximation, an effective-arrival-rate approximation, and a lagged stationary approximation. We assume an exhaustive service discipline, where service in progress when a server is scheduled to leave is completed before the server leaves. We used all of the methods to solve the same set of 640 test problems. The randomization method was almost as accurate as the exact method and used about half the computational time. The closure approximation was less accurate, and usually slower, than the randomization method. The two infinite-server-based approximations, the effective-arrival-rate approximation, and the lagged stationary approximation were less accurate but had computation times that were far shorter and less problem-dependent than the other three methods.