Reuse signature, or reuse distance pattern, is an accurate model for program memory accessing behaviors. It has been studied and shown to be effective in program analysis and optimizations by many recent works. However, the high overhead associated with reuse distance measurement restricts the scope of its application. This paper explores applying sampling in reuse signature collection to reduce the time overhead. We compare different sampling strategies and show that an enhanced systematic sampling with a uniform coverage of all distance ranges can be used to extrapolate the reuse distance distribution. Based on that analysis, we present a novel sampling method with a measurement accuracy of more than 99%. Our average speedup of reuse signature collection is 7.5 while the best improvement observed is 34. This is the first attempt to utilize sampling in measuring reuse signatures. Experiments with varied programs and instrumentation tools show that sampling has great potential in promoting the practical uses of reuse signatures and enabling more optimization opportunities.
Today, botnets are still responsible for most large scale attacks on the Internet. Botnets are versatile, they remain the most powerful attack platform by constantly and continuously adopting new techniques and strategies in the arms race against various detection schemes, . Thus, it is essential to understand the latest of the botnets in a timely manner so that the insights can be utilized in developing more efficient defenses. In this work, we conduct a measurement study on some of the most active botnets on the Internet based on a public dataset collected over a period of seven months by a monitoring entity. We first examine and compare the attacking capabilities of different families of today's active botnets. Our analysis clearly shows that different botnets start to collaborate when launching DDoS attacks.
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