Secure Untrusted Data Repository (SUNDR)

By Jinyuan Li, Maxwell N. Krohn, David Mazières, Dennis E. Shasha. USENIX Symposium on Operating Systems Design and Implementation, 2004

506 citations recorded by the source corpus.

Subfields: Computer Networks and Communications

View Paper: https://www.semanticscholar.org/paper/e4fc3adca44206ecb5dc2c4960e578fe2d0994fe

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In Computer Networks and Communications

Citations in the corpus

Verifying computations with state (2013, methodology): “To do so, we apply the technique of embedding in data blocks the names (or references or hashes—these concepts are equivalent here) of other blocks [17, 29, 47, 49, 53] (see also §9).”
Efficient RAM and control flow in verifiable outsourced computation (2015, methodology): “When RAM is built this way [25, 39, 54], each configuration of memory has its own digest.”
Making Geo-Replicated Systems Fast as Possible, Consistent when Necessary (2012, unknown): “Fork SUNDR [24] all ops no yes yes yes N/A”
Provable data possession at untrusted stores (2007, background): “It arises in peerto-peer storage systems [29, 35], network file systems [30, 26], long-term archives [32], web-service object stores [48], and database systems [31].”
zkLedger: Privacy-Preserving Auditing for Distributed Ledgers (2018, background): “There are many systems which compute on encrypted data to protect user confidentiality in the event of a server compromise [25, 31, 32, 40, 43, 44, 50].”
Vanish: Increasing Data Privacy with Self-Destructing Data (2009, background): “One could also use a different exit node for each share to counter potentially malicious Tor exit nodes [36, 66], or use Tor for only a subset of the shares.”
VC3: Trustworthy Data Analytics in the Cloud Using SGX (2015, background): “This is a cost-effective and flexible arrangement, but it requires users to trust the cloud provider with their code and data: while data at rest can easily be protected using bulk encryption [35], at some point, cloud computers typically need access to the users’ code and data in plaintext in order”
DJoin: Differentially Private Join Queries over Distributed Databases (2012, unknown): “In SUNDR [19], SPORC [13], and Depot [22], the server provides storage ; in CryptDB [30], it implements a database and SQL-style queries.”
Depot: Cloud Storage with Minimal Trust (2010, methodology): “As in prior work [Cachin et al. 2007, 2009; Li and Mazières 2007; Li et al. 2004], the protocol requires that an update be signed and that it name both its antecedents and the system state seen by the updater.”
DupLESS: Server-Aided Encryption for Deduplicated Storage (2013, background): “Prior works [42,53,54,58,75] which build a secure file system on top of a flat outsourced storage server break deduplication mechanisms and are unfit for use in our setting.”
Overshadow: a virtualization-based approach to retrofitting protection in commodity operating systems (2008, background): “More sophisticated approaches have been explored by others [11, 9, 17].”
On Omitting Commits and Committing Omissions: Preventing Git Metadata Tampering That (Re)introduces Software Vulnerabilities (2016, background): “SUNDR [26] provides fork consistency for a network file system that stores data on untrusted servers.”
Accountable Virtual Machines (2010, background): “If only a subset cooperates, she can still detect all the faults that are observable by that subset [21].”
CryptDB: protecting confidentiality with encrypted query processing (2011, methodology): “One approach to reduce the damage caused by server compromises is to encrypt sensitive data, as in SUNDR [28], SPORC [16], and Depot [30], and run all computations (application logic) on clients.”
T-SGX: Eradicating Controlled-Channel Attacks Against Enclave Programs (2017, background): “More critically, sensitive operations are often executed on potentially malicious clients [13] [36] [41], which significantly weakens the overall, end-to-end security of the system.”
An Efficient and Secure Dynamic Auditing Protocol for Data Storage in Cloud Computing (2013, background): “This is because data loss could happen in any infrastructure, no matter what high degree of reliable measures cloud service providers would take [4], [5], [6], [7], [8].”
CONIKS: Bringing Key Transparency to End Users (2015, unknown): “it must maintain fork consistency [42]).”