HomeAlone: Co-residency Detection in the Cloud via Side-Channel Analysis
By Yinqian Zhang, Ari Juels, Alina Oprea, Michael K. Reiter. IEEE Symposium on Security and Privacy, 2011
358 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Hardware and Architecture, Information Systems
View Paper: https://www.semanticscholar.org/paper/4d4a218d873a34c6c1e80cd14f3cca67532146c0
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Daniel Gruss
- Stefan Mangard
- Yuval Yarom
- Marcus Peinado
- Thomas Eisenbarth
- Gorka Irazoqui Apecechea
- Clémentine Maurice
- Yinqian Zhang
In Hardware and Architecture
- Thomas Eisenbarth
- Gorka Irazoqui Apecechea
- Marcus Peinado
- Taesoo Kim
- Ming-Wei Shih
- Sangho Lee
- Ahmad Moghimi
- Ari Juels
In Information Systems
- Daniel Gruss
- Stefan Mangard
- Marcus Peinado
- Thomas Eisenbarth
- Gorka Irazoqui Apecechea
- Clémentine Maurice
- Thomas Ristenpart
- Yuval Yarom
Citations in the corpus
- Cache Template Attacks: Automating Attacks on Inclusive Last-Level Caches (2015, background): “Instrumenting cache attacks to detect co-residency [58] with another virtual machine on the same physical machine, or even to detect cache attacks [59] and cachebased side channels in general [11] has already been pro-”
- S$A: A Shared Cache Attack That Works across Cores and Defies VM Sandboxing -- and Its Application to AES (2015, methodology): “This is the main reason why techniques such as Prime+Probe have only targeted the L1 cache, since it is the only one permitting the attacker to have full control of the bits resolving the set.”
- Raccoon: Closing Digital Side-Channels through Obfuscated Execution (2015, background): “Defenses against such attacks either partition resources [40, 14, 43, 37], add noise [39, 38, 23, 45], or”
- CATalyst: Defeating last-level cache side channel attacks in cloud computing (2016, background): “Recent research has demonstrated that this sharing may allow a malicious VM to extract sensitive information from co-resident VMs, a serious security concern for cloud adoption [22, 29, 34, 45, 46].”
- Inferring Fine-grained Control Flow Inside SGX Enclaves with Branch Shadowing (2016, background): “This attack is further extended to be conducted in the public cloud setting to recognize co-residency of virtual machines [45, 64].”
- Cross-VM side channels and their use to extract private keys (2012, background): “Subsequent work [48, 49] showed how to build various covert channels in cross-VM SMP settings, but these require cooperating VMs and so cannot be used as a side-channel attacks.”
- CacheZoom: How SGX Amplifies The Power of Cache Attacks (2017, background): “The attacker can identify where a particular VM is located on the cloud infrastructure such as Amazon EC2, create VMs until a co-located one is found [44, 55] and perform cross-VM Prime+Probe attacks [30].”
- Flush+Flush: A Fast and Stealthy Cache Attack (2015, background): “Zhang et al. [47] proposed HomeAlone, a system-level solution that uses a Prime+Probe covert channel to detect the presence of a foe co-resident virtual machine.”
- Last-Level Cache Side-Channel Attacks are Practical (2015, methodology): “[46] use an L2 side channel to detect non-cooperating co-resident VMs.”
- Whispers in the Hyper-space: High-speed Covert Channel Attacks in the Cloud (2012, background): “We first study existing cache covert channel techniques and their applications in a virtualized environment.”
- Cross-Tenant Side-Channel Attacks in PaaS Clouds (2014, methodology): “However, it might be possible to employ the same type of side-channel analysis to detect Flush-Reload attacks, similar to the ideas of HomeAlone [39].”