acm transactions on privacy and security

8. Fig. Often it is not possible to pack messages, before they are encrypted, e.g., when the messages are generated over time and not available at the moment of encryption. Dr. Yao is an IEEE Fellow for her contributions to enterprise data security and high-precision vulnerability screening. The 2021 Symposium will mark the 42 nd annual meeting of this flagship conference. SGX offers hardware encrypted and integrity-protected physical memory, which allows data and code to reside in the untrusted cloud. Topics of interest include: New ACM Policy on AuthorshipACM has a new Policy on Authorship, covering a range of key topics, including the use of generative AI tools. The effectiveness of the model can be evaluated by looking at how well the model converts the deployment profile for the plaintext streams to the deployment profile for the encrypted streams in C3PO. PAGE LIMIT. We use the popular Linear Road Benchmark (LRB) that models variable toll calculation for a city or county to assess C3POs deployment heuristic. Storm is an online, distributed computation system. k-anonymity based models and knowledge hiding models), and methods of secure communication with various properties (e.g. A straightforward application of PHE and PPE to existing stream processing solutions to support computations over encrypted data is unlikely to be practical: Complexity of cryptosystems. The tuples in the stream are processed in a distributed fashion. SIGN IN Furthermore, using FNR to keep ciphertext size smaller is particularly useful when also employing the caching and speculative encryption optimization described above. Unfortunately, there are no standards on how to best interpret the scan Data-oriented attacks manipulate non-control data to alter a programs benign behavior without violating its control-flow integrity. Threat 1: Cloud compromises. C3PO makes computations over encrypted data practical for stream processing by using a novel API, encryption inference, automatic re-encryption, and a set of other original optimizations. In addition, IoT devices can vary significantly in terms of their computing power and memory capacity. C3PO leverages the idea that oftentimes users have some limited (but trusted) computing resources available. To ensure the secure delivery of keys, C3PO first establishes a secure TLS-based connection between the key manager and IoT devices and transmits keys over TLS. Application variables & constants. Table 4. IoT devices are vulnerable to physical attacks that can compromise secret keys (for asymmetric encryption schemes only the public key is made available to the IoT devices). Since C3PO supports devices with as little as 64 KB of memory, having ciphertexts of smaller size allows IoT devices to retain a larger number of cached ciphertexts in memory. Adoption of PHE and even FHE for generic application development will depend on the ease with which a programmer can incorporate the properties offered by the cryptosystem into their regular programming tasks. Submission to TOPS implies exclusive consideration by TOPS 'till such time as official decision by the Editor-in-Chief has been made. This article presents C3PO (Cloud-based Confidentiality-preserving Continuous Query Processing),3 a novel managed runtime system that leverages PHE and PPE to provide confidentiality for IoT applications delegating online streaming jobs to the public cloud. Please download or close your previous search result export first before starting a new bulk export. AUTHORSHIP INTEGRITY. The intuition here is that for vertices that come under heavy load, the programmer will allocate a higher number of instances in the deployment profile to accommodate the load. Paillier and ElGamal require arbitrary precision arithmetic computations as part of their encryption, decryption, and homomorphic operations. Leading IAM providers include AWS Identity and Access Management, CrowdStrike, Delinea, Ericom, ForgeRock, Ivanti, Google Cloud Identity, IBM, Microsoft Azure Active Directory, Palo Alto Networks . Tutorial or survey papers will not be considered for publication. We observe that if SSL is available, then AES and FNR encryption is very fast, taking only 19 us for AES and 36 us for FNR, on the most computationally constrained device, M3. University of Auckland, Auckland, New Zealand, University of Auckland, Auckland, New Zealand and Carleton University, Ottawa, Canada, Universitt Stuttgart, Stuttgart, Germany. Dozens of PHE and PPE schemes exist, varying by operations supported, efficiency, ciphertext size, and so on; IoT application developers do not necessarily possess sufficient knowledge of cryptosystems to judiciously select among these. To identify unused fields, C3PO relies on the stream annotations described in Section 4.1. The primary responsibility of the C3PO scheduler is to decide on which host machine(s) each vertex of the graph will be executed. The Editor-in-Chief is copied on all correspondence. Note that every multiplication generates an additional term in the ciphertext. AHE packing. The Editor-in-Chief forwards the paper to an Editor for processing. Your search export query has expired. SecureScala [28] is a domain-specific language in Scala that allows expressing secure programs without requiring any cryptographic knowledge from the programmer. This shows that multi-group mode is an effective way of rotating encryption keys. Packing is even more effective for Paillier, since we can pack up to 33 int items in a single Paillier ciphertext. Linear road: A stream data management benchmark, IoTAbench: An internet of things analytics benchmark, Retrieved from https://developer.arm.com/ip-products/security-ip/trustzone, Smart*: An open data set and tools for enabling research in sustainable homes, BigDigits Multiple Precision Arithmetic Library, TimeCrypt: Encrypted data stream processing at scale with cryptographic access control, Self-organized public-key management for mobile ad hoc networks, Benchmarking streaming computation engines: Storm, Flink and Spark streaming, Contact tracing mobile apps for COVID-19: Privacy considerations and related trade-offs, A generalisation, a simplification and some applications of Pailliers probabilistic public-key system, FNR: Arbitrary length small domain block cipher proposal, Ensuring confidentiality in the cloud of things, A public key cryptosystem and a signature scheme based on discrete logarithms, Answering aggregation queries in a secure system model, Fully homomorphic encryption using ideal lattices, Homomorphic evaluation of the AES circuit, Practical passive leakage-abuse attacks against symmetric searchable encryption, Leakage-abuse attacks against order-revealing encryption, Bolt: Data management for connected homes, Searchable encryption with secure and efficient updates, SecureScala: Scala embedding of secure computations, SecureStreams: A reactive middleware framework for secure data stream processing, Identity Verification and End-to-End Encryption, SecureCloud: Secure big data processing in untrusted clouds, Frequency-hiding order-preserving encryption, An efficiently searchable encrypted data structure for range queries, Twitter heron: Stream processing at scale, JEDI: Many-to-many end-to-end encryption and key delegation for IoT, Efficient and scalable IoT service delivery on cloud, A survey on fully homomorphic encryption: An engineering perspective, The design and implementation of datagram TLS, Inference attacks on property-preserving encrypted databases, Samza: Stateful scalable stream processing at LinkedIn, HealthGear: A real-time wearable system for monitoring and analyzing physiological signals, OpenSSL Multiple Precision Arithmetic Library, Public-key cryptosystems based on composite degree residuosity classes, Big data analytics over encrypted datasets with Seabed, Arx: An encrypted database using semantically secure encryption, An ideal-security protocol for order-preserving encoding, CryptDB: Protecting confidentiality with encrypted query processing, Retrieved from https://www.helpnetsecurity.com/2020/07/09/public-cloud-security-incident/, Practical Confidentiality-Preserving Data Analytics in Untrusted Clouds, Efficient confidentiality-preserving data analytics over symmetrically encrypted datasets, Secure data types: A simple abstraction for confidentiality-preserving data analytics, Droplet: Decentralized authorization and access control for encrypted data streams, Secure sharing of partially homomorphic encrypted IoT data, Talos: Encrypted query processing for the internet of things, Practical techniques for searches on encrypted data, Practical confidentiality preserving big data analysis, Program analysis for secure big data processing, STYX: Stream processing with trustworthy cloud-based execution, The GNU Multiple Precision Arithmetic Library, An IoT-cloud based wearable ECG monitoring system for smart healthcare, A key management scheme using deployment knowledge for wireless sensor networks, Discretized streams: An efficient and fault-tolerant model for stream processing on large clusters, Skip 5PHE and PPE for IOT Devices Section, Skip 7C3PO Deployment and Security Analysis Section, https://www.rfc-editor.org/rfc/rfc7228.txt, http://www.rfc-editor.org/rfc/rfc5246.txt, http://chriswhong.com/open-data/foil_nyc_taxi, All Holdings within the ACM Digital Library. Authors should submit such work to TOPS only after the paper has been presented at the conference so that any questions or comments from the presentation can be taken into account. Fig. Theoretical papers must make convincing argument for the practical significance of the results. C3PO leverages this fact by having IoT devices store a small number of encrypted values that are likely to be re-used. Source vertices act as entry points for data into the graph. We compute the total number of bits, \(T\), allocated for each packed item as 2:1-2:31. Following this intuition, we derive two invariants that need to hold for all keys to minimize data leaks while preserving program correctness. MHE schemes include the ElGamal [18] and unpadded RSA [50] cryptosystems. Figure 4(a) shows the effect of a nave key change in an encrypted data stream. The upper limit within which the system needs to report tolls and accidents is 5 s. The benchmark rates the system by the highest number of expressways (L) the system can support while maintaining these invariants. Finally, \(v_4\) has three tasks running on a trusted node \(n_3\). We therefore fix the number of packed items to 2 and now, arithmetically, we have \((a_1 \circ a_2) \times (b_1 \circ b_2) = (a_1 \times b_1) \circ (a_1 \times b_2 + a2 \times b_1) \circ (a_2 \times b_2),\) which includes the intermediate term \((a_1\,\times \,b_2 + a2 \,\times \, b_1)\). Expectations of reviewers and ACM can be found in the Reviewer section of the Policy on Roles and Responsibilities in ACM Publishing page. Oftentimes, continuous queries include equality comparisons involving values of a fixed format such as dates, timestamps, or phone numbers. In addition, C3PO addresses challenges such as managing keys and allows for different deployments that improve performance. Please also see the "25% new material guideline" atACM Policy on Prior Publication and Simultaneous Submissions. ACM Transactions on Privacy and Security Archive Vol. Each component is then wrapped in Docker containers for isolation and ease of deployment. Information provided by the authors on prior rejection and current submission will be treated as confidential. https://dlnext.acm.org/doi/10.1145/3472717. ACM Transactions on Transactions on Privacy and Security (TOPS) is devoted to the study, analysis, and application of information security and privacy. Response time for LRB on Storm. Secure Systems: secure operating systems, database systems and networks; secure distributed systems including security middleware; secure web browsers, servers, and mobile code; specialized secure systems for specific application areas; interoperability, and composition. For example, conditions that require more than one encryption scheme to be used on the same variable, e.g., \(x + y \gt \alpha\) or for conditions that include a public value such as \(secret\_value \gt public\_const\) where the public value cannot be encrypted as it is already public, C3PO will perform the entire control structure in the trusted tier. (8) \[\begin{equation} D^{\prime }(x) = {\left\lbrace \begin{array}{ll} D(x) - N& \text{if}\ D(x) \ge \lfloor \frac{N}{\delta } \rfloor \\ D(x) & \text{otherwise,} \end{array}\right.} Application logic in Storm is packaged into directed graphs called topologies. Computing methodologies. The ACM LaTeX template on Overleaf platform is available to all ACM authorshttps://www.overleaf.com/gallery/tagged/acm-official#.WOuOk2e1taQ. Deep learning, especially deep neural networks (DNNs), has been widely and successfully adopted in many critical applications for its high effectiveness and efficiency. Once all vertices of the graph are designated, the graph is assembled by defining the input stream of each vertex and specifying the grouping clause of each stream. We observe that in Storm vertices \(v_4\) and \(v_2\) have the highest utilization values until around the 8,000 s mark, and after that vertex \(v_1\) becomes the node with the highest load. Indeed, researchers have stressed a useful technique that can address this barrier. An approach that is gaining popularity now is to use an Intel SGX7 enabled processor, which offers a trusted execution environment (so-called enclaves) in which data computations can be carried out confidentially. Reviewing and editorial chores are all done by volunteers. Deployment optimization technique (Section 7): We propose a deployment heuristic that analyzes resource availability and requirements and generates a deployment profile that optimizes cloud resource usage (7). 7. The client device emits a message every time the client requests to see a specific data point, in response to which, the requested values are retrieved. Providing the proper indexing and retrieval information from the CCS provides the reader with quick content reference, facilitating the search for related literature, as well as searches for your work in ACM's Digital Library and on other online resources. (5) \[\begin{equation} D(E(x_1) \times E(x_2)^{-1} \bmod N^2) = (x_1 - x_2) \bmod N \end{equation}\] Similarly, the ElGamal cryptosystem [18] supports multiplication and division (multiplication with the multiplicative inverse) between two encrypted values and multiplication/exponentiation between an encrypted and a plaintext value. The top part of each stacked column indicates decryption overhead. These can be derived from the graph declaration provided by the application programmer, as explained in Section 4.1. It is still beneficial to pack values after they have been encrypted through post-encryption packing to reduce ciphertext size and decryption times. This means a factor of 128 increase in the operand size. Even in the worst case, ElGamal implemented using the less optimized BigDigits library takes only 1.7 ms on the most resource-constrained device, M3. Fig. Abstracting with credit is permitted. The stream emitted by each vertex is declared explicitly in the vertex itself. ACMauthoring templates are found at:http://www.acm.org/publications/authors/submissions. 11. Note that the annotation @encOperations(operations = {{eq}, {{sum}}) in Line 2 indicates to the compiler that the first field of the stream is used in equality comparisons and the second field in summing. Streams are unbounded sequences of tuples. These changes add an additional 1,031 lines of Java code to Storm. Correspondence with the authors regarding revisions is typically done by the Editor. This dataset represents electrical meter readings collected over a 24-hour period at the rate of one reading per minute from 443 unique homes, totaling 637,526 records. As discussed in Section 3.1, C3PO can optionally use encryption schemes that reveal relationships among data items. The key idea is to intelligently utilize partially homomorphic and property-preserving encryption to perform as many computationally intensive operations as possiblewithout revealing plaintextin the untrusted cloud. To keep track of what keys are sent to each device and to be able to identify which devices need to be sent new keys during key rotation, the key manager keeps a map of key IDs per device (key metadata). Copyright 2023 ACM, Inc. ACM Transactions on Privacy and Security (TOPS), SoK: Human-centered Phishing Susceptibility, Performance and Usability Evaluation of Brainwave Authentication Techniques with Consumer Devices, All Holdings within the ACM Digital Library. LRB data profile. The key manager is implemented in 900 lines of Java code and uses DTLS [38] to establish an end-to-end secure channel with IoT devices. Fig. The key manager uses key group information and the encryption strategy generated during the homomorphism analysis step of the compilation to decide how to generate keys, as shown in Figure 5. This example includes several implementation complexities and requires the programmer to. DET schemes reveal the uniqueness of encrypted values, since the same plaintext is encrypted into the same ciphertext, unlike probabilistic schemes that randomize ciphertexts. LRB graph. Fig. Seabed [45] introduces an additively symmetric homomorphic encryption scheme to perform aggregations on large encrypted datasets efficiently. The C3PO programming interface and cryptographic classes that allow computations over encrypted data (but do not include encryption/decryption functions) are packaged as a separate jar library, implemented in 3,633 lines of Java code. Since an unused field may be at any index within a tuple, if we simply drop the field, then program logic that accesses other fields using their indices may fail. C3PO is capable of continuing computation in the trusted tier or re-encrypting (parts of) a data stream to enable further computation in the public cloud if a given sequence of computations cannot be performed due to PHE limitations (4). To further reduce the encryption time overhead, C3PO uses speculative encryption by predicting what values will need to be encrypted next. One way to mitigate these concerns is to encrypt data at the source (i.e., IoT devices) and solely use cloud infrastructure for storage purposes (e.g., Bolt [25]). The object maintaining the sliding window internally contains a map and updates the groups sum every time the updateSum() method is called using C3POs SecOper.add() method (Line 24). Ge et al. List 2 shows just the function updateSum() from List 1 written without using C3PO abstractions. Finally, we implemented ElGamal [18] as the MHE scheme. FNR [15] is used as an alternative DET cryptosystem to preserve the format of small values. As homomorphic operations are performed on ciphertexts, the operations are carried out on the underlying packed values separately. (6) \[\begin{equation} E^{\prime }(x) = {\left\lbrace \begin{array}{ll} E(x \bmod N) & \text{if}\ -\lceil N(1 - \frac{1}{\delta }) \rceil \le x \lt \lfloor \frac{N}{\delta } \rfloor \\ \varnothing & \text{otherwise,} \end{array}\right.} For example, ciphertexts of the ElGamal cryptosystem contain two components and homomorphic multiplication of two ciphertexts is achieved by multiplying the two components of the ciphertexts, respectively, to generate the encrypted result. Furthermore, the increase in completion times and average response times caused by a monthly key change are minimal (about 1%). Cuttlefish shows the benefits of using SGX selectively when hitting the limits of PHE (for re-encryption). If ORCIDs are included in an articles source files, they will also be linked in the published output. The receiver of these tuples (1 tuple per group) can finally compute the total sum by adding the intermediate sums together after decrypting them. We also used the Chinese Remainder Theorem to optimize the decryption function of Paillier. To preserve confidentiality, value \(\alpha\) cannot remain in plaintext and should instead be encrypted under the appropriate cryptosystem during program compilation. Your search export query has expired. SIGN IN By default, we set \(R= 2^{30}\), which means that when packing 32-bit integers into a single 2,048-bit plaintext, we can fit 33 items before encrypting and can perform over 1 billion operations without exceeding the allotted padding bits. WKD-IBE and AES schemes and assembly-level optimizations are incorporated to support embedded IoT devices. An alternative, practical approach is to use less expensive partially homomorphic encryption (PHE) [50] in combination with property-preserving encryption (PPE) [44] to execute specific operations over encrypted data.
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