A METHOD FOR FRICTIONLESS SIGNATURE-BASED HIGH-RISK PERMISSIONS MANAGEMENT ON COMPUTING DEVICES AND SYSTEM THEREOF

The present disclosure provides a method for frictionless signature-based high-risk permissions management on computing devices. The method includes an onboarding process involving the inclusion of new software vendors by the OS or MDM vendor, a process that verifies vendor legitimacy and the necessity of their access to sensitive resources. During onboarding, the OS or MDM vendor generates an upload key, securely provided to the software vendor, and an app signing key, securely retained within the vendor\u27s Key Management System (KMS). Further, the method includes releasing or publishing applications to a digital distribution service managed by the OS or MDM vendor involves software vendors declaring necessary permissions and signing applications with the upload key before uploading them to distribution services. The OS or MDM vendor validates the application, ensuring vendor correspondence, adherence to platform-specific signature rules, and pre-clearance for resource access. Upon successful verification, the application is signed with permission-specific certificates and the app signing key, preparing it for distribution. Furthermore, the method includes downloading and installation of applications on end-point computing devices encompass the OS verification process. If successful, the application is installed with normal or low-risk permissions without user consent. Moreover, for each requested sensitive resource and feature access, the application is verified with the corresponding permission key, granting dangerous or high-risk permissions seamlessly

When private set intersection meets big data : an efficient and scalable protocol

Large scale data processing brings new challenges to the design of privacy-preserving protocols: how to meet the increasing requirements of speed and throughput of modern applications, and how to scale up smoothly when data being protected is big. Efficiency and scalability become critical criteria for privacy preserving protocols in the age of Big Data. In this paper, we present a new Private Set Intersection (PSI) protocol that is extremely efficient and highly scalable compared with existing protocols. The protocol is based on a novel approach that we call oblivious Bloom intersection. It has linear complexity and relies mostly on efficient symmetric key operations. It has high scalability due to the fact that most operations can be parallelized easily. The protocol has two versions: a basic protocol and an enhanced protocol, the security of the two variants is analyzed and proved in the semi-honest model and the malicious model respectively. A prototype of the basic protocol has been built. We report the result of performance evaluation and compare it against the two previously fastest PSI protocols. Our protocol is orders of magnitude faster than these two protocols. To compute the intersection of two million-element sets, our protocol needs only 41 seconds (80-bit security) and 339 seconds (256-bit security) on moderate hardware in parallel mode

Setup-Free Secure Search on Encrypted Data: Faster and Post-Processing Free

We present a novel $\textit{secure search}$ protocol on data and queries encrypted with Fully Homomorphic Encryption (FHE). Our protocol enables organizations (client) to (1) securely upload an unsorted data array $x=(x[1],\ldots,x[n])$ to an untrusted honest-but-curious sever, where data may be uploaded over time and from multiple data-sources; and (2) securely issue repeated search queries $q$ for retrieving the first element $(i^*,x[i^*])$ satisfying an agreed matching criterion $i^* = \min\ \left\{ \left.i\in[n] \;\right\vert \mathsf{IsMatch}(x[i],q)=1 \right\}$, as well as fetching the next matching elements with further interaction. For security, the client encrypts the data and queries with FHE prior to uploading, and the server processes the ciphertexts to produce the result ciphertext for the client to decrypt. Our secure search protocol improves over the prior state-of-the-art for secure search on FHE encrypted data (Akavia, Feldman, Shaul (AFS), CCS\u272018) in achieving: (1) $\textit{Post-processing free}$ protocol where the server produces a ciphertext for the correct search outcome with overwhelming success probability.This is in contrast to returning a list of candidates for the client to post-process, or suffering from a noticeable error probability, in AFS. Our post-processing freeness enables the server to use secure search as a sub-component in a larger computation without interaction with the client. (2) $\textit{Faster protocol:}$(a) Client time and communication bandwidth are improved by a $\log^2n/\log\log n$ factor. (b) Server evaluates a polynomial of degree linear in $\log n$ (compare to cubic in AFS), and overall number of multiplications improved by up to $\log n$ factor.(c) Employing only $\textrm{GF}(2)$ computations (compare to $\textrm{GF}(p)$ for $p \gg 2$ in AFS) to gain both further speedup and compatibility to all current FHE candidates. (3) $\textit{Order of magnitude speedup exhibited by extensive benchmarks}$ we executed on identical hardware for implementations of ours versus AFS\u27s protocols. Additionally, like other FHE based solutions, out solution is setup-free: to outsource elements from the client to the server, no additional actions are performed on $x$ except for encrypting it element by element (each element bit by bit) and uploading the resulted ciphertexts to the server

Instantaneous Decentralized Poker

We present efficient protocols for amortized secure multiparty computation with penalties and secure cash distribution, of which poker is a prime example. Our protocols have an initial phase where the parties interact with a cryptocurrency network, that then enables them to interact only among themselves over the course of playing many poker games in which money changes hands. The high efficiency of our protocols is achieved by harnessing the power of stateful contracts. Compared to the limited expressive power of Bitcoin scripts, stateful contracts enable richer forms of interaction between standard secure computation and a cryptocurrency. We formalize the stateful contract model and the security notions that our protocols accomplish, and provide proofs using the simulation paradigm. Moreover, we provide a reference implementation in Ethereum/Solidity for the stateful contracts that our protocols are based on. We also adopt our off-chain cash distribution protocols to the special case of stateful duplex micropayment channels, which are of independent interest. In comparison to Bitcoin based payment channels, our duplex channel implementation is more efficient and has additional features

Programmeerimiskeeled turvalise ühisarvutuse rakenduste arendamiseks

Turvaline ühisarvutus on tehnoloogia, mis lubab mitmel sõltumatul osapoolel oma andmeid koos töödelda neis olevaid saladusi avalikustamata. Kui andmed on esitatud krüpteeritud kujul, tähendab see, et neid ei dekrüpteerita arvutuse käigus kordagi. Turvalise ühisarvutuse teoreetilised konstruktsioonid on teada olnud juba alates kaheksakümnendatest, kuid esimesed praktilised teostused ja rakendused, mis päris andmeid töötlesid, ilmusid alles natuke enam kui kümme aastat tagasi. Nüüdseks on turvalist ühisarvutust kasutatud mitmes praktilises rakenduses ning sellest on kujunenud oluline andmekaitsetehnoloogia. Turvalise ühisarvutuse rakenduste arendamine on keerukas. Vahendid, mis aitavad kaasa arendusprotsessile, on veel väga uued, ning raamistikud on sageli liiga aeglased praktiliste rakenduste jaoks. Rakendusi on endiselt võimelised arendama ainult krüptograafiaeksperdid. Käesoleva töö eesmärk on teha turvalise ühisarvutuse raamistikke paremaks ning muuta ühisarvutusrakenduste arendamist kergemaks. Väidame, et valdkon- naspetsiifiliste programmeerimiskeelte kasutamine võimaldab turvalise ühisarvu- tuse rakenduste ja raamistike ehitamist, mis on samaaegselt lihtsasti kasutatavad, hea jõudlusega, hooldatavad, usaldusväärsed ja võimelised suuri andmemahtusid töötlema. Peamise tulemusena esitleme kahte uut programmeerimiskeelt, mis on mõeldud turvalise ühisarvutuse jaoks. SecreC 2 on mõeldud turvalise ühisarvutuse rakendus- te arendamise lihtsustamiseks ja aitab kaasa sellele, et rakendused oleks turvalised ja efektiivsed. Teine keel on loodud turvalise ühisarvutuse protokollide arenda- miseks ning selle eesmärk on turvalise ühisarvutuse raamistikke paremaks muuta. Protokollide keel teeb raamistikke kiiremaks ja usaldusväärsemaks ning lihtsustab protokollide arendamist ja haldamist. Kirjeldame mõlemad keeled nii formaalselt kui mitteformaalselt. Näitame, kuidas mitmed rakendused ja prototüübid saavad neist keeltest kasu.Secure multi-party computation is a technology that allows several independent parties to cooperatively process their private data without revealing any secrets. If private inputs are given in encrypted form then the results will also be encrypted, and at no stage during processing are values ever decrypted. As a theoretical concept, the technology has been around since the 1980s, but the first practical implementations arose a bit more than a decade ago. Since then, secure multi-party computation has been used in practical applications, and has been established as an important method of data protection. Developing applications that use secure multi-party computation is challenging. The tools that help with development are still very young and the frameworks are often too slow for practical applications. Currently only experts in cryptography are able to develop secure multi-party applications. In this thesis we look how to improve secure multy-party computation frame- works and make the applications easier to develop. We claim that domain-specific programming languages enable to build secure multi-party applications and frame- works that are at the same time usable, efficient, maintainable, trustworthy, and practically scalable. The contribution of this thesis is the introduction of two new programming languages for secure multi-party computation. The SecreC 2 language makes secure multi-party computation application development easier, ensuring that the applications are secure and enabling them to be efficient. The second language is for developing low-level secure computation protocols. This language was created for improving secure multi-party computation frameworks. It makes the frameworks faster and more trustworthy, and protocols easier to develop and maintain. We give give both a formal and an informal overview of the two languages and see how they benefit multi-party applications and prototypes