Attacks on the heap are an increasingly severe threat. State-of-the-art secure dynamic memory allocators can offer protection, however their memory consumption is high, making them suboptimal in many situations. We introduce sys, a secure allocator whose design is driven by memory efficiency. Among other features, sys uses an efficient fine-grain size classes indexing mechanism and implements a novel dynamic canary scheme. It offers a low memory overhead due its size classes optimized for canary usage, its on-demand metadata allocation, and the combination of randomized allocations and over-provisioning into a single memory efficient security feature. sys protects against widespread heap-related attacks such as overflows, over-reads, double/invalid free, and use-after-free. Evaluation over a wide range of applications shows that it offers a significant reduction in memory consumption compared to the state-of-the-art secure allocator (up to 2x in macro-benchmarks), while offering similar or better security guarantees and good performance. / Master of Science / Attacks targeting on the runtime memory (heap allocator) are severe threats to software safety. Statistical results shown that the numbers of heap-related attacks has doubled since 2016. A large number of research works are designed to solve the security problems by offering different techniques to prevent some specific attacks. Not only are they very secure but also fast. However, these secure heap allocators sacrifice the memory usage, all of them at least double the memory consumption. Our work is trying to design and implement a heap allocator, in which it can defend against different attacks, as well as fast and memory-efficient. We carefully re-design some security features in our heap allocator while keep memory-efficient in mind. In the end, we evaluated sys and found that it offers significant reduction on different benchmarks suites. Evaluation also showed that sys can detect a lot of vulnerabilities in the software, while offer the same good performance as the state-of-the-art heap allocator.

Dynamic memory allocators are a determining factor of an application's performanceand have the opportunity to improve a major performance bottleneck ontoday's computer hardware: data locality. To approach this problem, a memoryallocator must rst oer strategies that allow the locality problem to be addressed.However, while focusing on locality, an allocator must also not ignore the existing constraintsof allocation speed and fragmentation, which further complicate its design. Inorder for a locality improving technique to be successfully employed in today's largecode applications, its integration needs to be automatic, without user intervention.The alternative, manual integration, is not a tractable solution.In this dissertation we develop three novel memory allocators that explore dierentallocation strategies that enhance an application's locality. We conduct the rststudy that shows that allocation speed, fragmentation and locality improving goalsare antagonistic. We develop an automatic method that supplies allocation hintsfrom C++ STL containers to their allocators. This method allows applications tobenet from locality improving techniques at the cost of a simple re-compilation. Weconduct the rst study that quanties the eect of allocation hints on performance,and show that an allocator with high locality of reference can be as competitive asone using an application's spatial feedback.To further allow dynamic memory allocation to improve an application's performance,new and non-traditional strategies need be explored. We develop a generic software tool that allows users to examine unconventional strategies. The tool allowsusers not only to focus on allocation strategies rather than their implementation, butalso to compare and contrast various approaches.

Dynamic memory allocators are a determining factor of an application's performanceand have the opportunity to improve a major performance bottleneck ontoday's computer hardware: data locality. To approach this problem, a memoryallocator must rst oer strategies that allow the locality problem to be addressed.However, while focusing on locality, an allocator must also not ignore the existing constraintsof allocation speed and fragmentation, which further complicate its design. Inorder for a locality improving technique to be successfully employed in today's largecode applications, its integration needs to be automatic, without user intervention.The alternative, manual integration, is not a tractable solution.In this dissertation we develop three novel memory allocators that explore dierentallocation strategies that enhance an application's locality. We conduct the rststudy that shows that allocation speed, fragmentation and locality improving goalsare antagonistic. We develop an automatic method that supplies allocation hintsfrom C++ STL containers to their allocators. This method allows applications tobenet from locality improving techniques at the cost of a simple re-compilation. Weconduct the rst study that quanties the eect of allocation hints on performance,and show that an allocator with high locality of reference can be as competitive asone using an application's spatial feedback.To further allow dynamic memory allocation to improve an application's performance,new and non-traditional strategies need be explored. We develop a generic software tool that allows users to examine unconventional strategies. The tool allowsusers not only to focus on allocation strategies rather than their implementation, butalso to compare and contrast various approaches.

This diploma thesis presents a tool for dynamic memory allocator analysis, focused on their performance. The work identifies the important memory allocator performance metrics, as well as the environment and program factors influencing these metrics. Using this knowledge, a tool was designed and implemented. This tool allows to gather and analyze these metrics. The tool provides the ability to create memory allocator usage scenarios for the purpose of the allocator behavior analysis under different conditions. The tool was tested on several available memory allocators with free license.