{"title":"Exploiting DRAM bank mapping and HugePages for effective denial-of-service attacks on shared cache in multicore","authors":"M. Bechtel, H. Yun","doi":"10.1145/3384217.3386394","DOIUrl":"https://doi.org/10.1145/3384217.3386394","url":null,"abstract":"In this paper, we propose memory-aware cache DoS attacks that can induce more effective cache blocking by taking advantage of information of the underlying memory hardware. Like prior cache DoS attacks, our new attacks also generate lots of cache misses to exhaust cache internal shared hardware resources. The difference is that we carefully control those cache misses to target the same DRAM bank to induce bank conflicts. Note that accesses to different DRAM banks can occur in parallel, and are thus faster. However, accesses to the same bank are serialized, and thus slower [5] and as each memory access request takes longer to finish, it would prolong the time it takes for the cache to become unblocked. We further extend these attacks to exploit HugePage support in Linux in order to directly control physical address bits and to avoid TLB contention, while mounting the attacks from the userspace.","PeriodicalId":205173,"journal":{"name":"Proceedings of the 7th Symposium on Hot Topics in the Science of Security","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129077978","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
E. Vugrin, Jerry Cruz, Christian Reedy, T. Tarman, Ali Pinar
{"title":"Cyber threat modeling and validation: port scanning and detection","authors":"E. Vugrin, Jerry Cruz, Christian Reedy, T. Tarman, Ali Pinar","doi":"10.1145/3384217.3385626","DOIUrl":"https://doi.org/10.1145/3384217.3385626","url":null,"abstract":"Port scanning is a commonly applied technique in the discovery phase of cyber attacks. As such, defending against them has long been the subject of many research and modeling efforts. Though modeling efforts can search large parameter spaces to find effective defensive parameter settings, confidence in modeling results can be hampered by limited or omitted validation efforts. In this paper, we introduce a novel, mathematical model that describes port scanning progress by an attacker and intrusion detection by a defender. The paper further describes a set of emulation experiments that we conducted with a virtual testbed and used to validate the model. Results are presented for two scanning strategies: a slow, stealthy approach and a fast, loud approach. Estimates from the model fall within 95% confidence intervals on the means estimated from the experiments. Consequently, the model's predictive capability provides confidence in its use for evaluation and development of defensive strategies against port scanning.","PeriodicalId":205173,"journal":{"name":"Proceedings of the 7th Symposium on Hot Topics in the Science of Security","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116726722","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}