Secure computation is becoming a key feature of future information systems. Distributed network applications and cloud architectures are at danger because lots of personal consumer data is aggregated in all kinds of formats and for various purposes. Industry and consumer electronics companies are facing massive threats like theft of intellectual property and industrial espionage. Public infrastructure has to be secured against sabotage and manipulation. A possible solution is encrypted computing: Data can be processed on remote, possibly insecure resources, while program code and data is encrypted all the time. This allows to outsource the computation of confidential information independently from the trustworthiness or the security level of the remote system. The technologies and techniques discussed in this workshop are a key to extend the range of applications that can be securely outsourced.

The 11th Workshop on Encrypted Computing and Applied Homomorphic Cryptography is held in Copenhagen, Denmark on Novem- ber 26, 2023, co-located with the ACM Conference on Computer and Communications Security (CCS). The workshop aims to bring together professionals, researchers and practitioners from academia, industry and government in the area of computer security and applied cryptography with an interest in practical applications of homomorphic encryption, encrypted computing, functional encryption and secure function evaluation, private information retrieval and searchable encryption. The workshop will feature 9 exciting accepted talks on different aspects of secure computation and a forum to discuss current and future challenges. Additionally, the workshop will feature one keynote presentation, as well as one invited talk.

Private Information Retrieval (PIR) protocols enables fetching an arbitrary data from a server without revealing any information to the server about the data. In this paper, we construct three computational PIR (cPIR) protocols which we call P-cPIR and Recursive P-cPIR version I and II. We construct our cPIR protocols on a well known Fully Homomorphic Encryption scheme (FHE), BFVrns. For n = 220, 240, P-cPIR and Recursive P-cPIR version I provide at least ∼ 214 × computational improvement over other prominent cPIR protocols. Recursive P-cPIR version II proposes the same query and half response cost as OnionPIR (lower communication cost in total) and less than other protocols such as SealPIR, SHECS-PIR, XPIR. It also proposes at least ∼ 23 × less computational cost than other proposed protocols by stating the best performance in these protocols for both cases. We also provide a parameter selection method for the proposed cPIR protocols that takes the burden of parameter selection from the users and makes it more usable for real-life applications.

The 10th Workshop on Encrypted Computing and Applied Homomorphic Cryptography is held in Los Angeles, CA, USA on November 7, 2022, co-located with the ACM Conference on Computer and Communications Security (CCS). The workshop aims to bring together professionals, researchers and practitioners from academia, industry and government in the area of computer security and applied cryptography with an interest in practical applications of homomorphic encryption, encrypted computing, functional encryption and secure function evaluation, private information retrieval and searchable encryption. The workshop will feature 6 exciting accepted talks on different aspects of secure computation and a forum to discuss current and future challenges. Additionally, the workshop will feature one keynote presentation, as well as a working session. The complete WAHC'22 workshop proceedings are available at: https://dl.acm.org/doi/proceedings/10.1145/3560827.

One of the first major breakthroughs of computer science in the 21stcentury has been the discovery and practical demonstration of encrypted computing technologies such as Fully Homomorphic Encryption (FHE). Encrypted computing technologies allow sensitive data to be encrypted such that arbitrary programs can be securely run over the encrypted data where the output, when decrypted, is equivalent to the result of running the original algorithm on the unencrypted data. In this talk we focus on the use of and potential for computer arithmetic research to enable more practical encrypted computing, such as to accelerate advanced encryption implementations on custom hardware. These technologies are ground-breaking in their ability for privacy-preserving data science on sensitive data sets with minimal costs in terms of engineering effort, power, compute resources, etc... We discuss theory, design, algorithmic, hardware, software engineering and systems research that is enabling applications of encrypted computing in regulated data industries, such as in medical and financial domains. We use our work using accelerating the PALISADE open-source homomorphic encryption software library for practical applications in case studies.

The 7th Workshop on Encrypted Computing & Applied Homomorphic Cryptography (WAHC) will be held in London, United Kingdom, on November 11th, 2019, co-located with the ACM Conference on Computer and Communications Security (CCS). The purpose of the WAHC 2019 workshop is to bring together professionals, researchers and practitioners from academia, industry and government, to present, discuss and share the latest progress in the field of encrypted computing. Encrypted computing is a particular subfield of the area of computer security and applied cryptography, with an interest in practical applications of homomorphic encryption, multiparty computation, functional encryption, secure function evaluation, private information retrieval and searchable encryption. The workshop features an invited talk, that discusses how advanced cryptography is on its way to practice, a demonstration of an homomorphic encryption evaluation platform, and 6 exciting talks on different encrypting computing topics: homomorphic encryption standardization, multiparty computation, and applications.

Genome sequence search is useful, for example, in clinical applications where a care provider needs to select a treatment option for a patient based on the exact kind of cancer the patient might have. Homomorphic encryption is a desirable technology to be used for this application because it is non-interactive. However, privacy-preserving genome sequence search using homomorphic encryption has been a practical challenge because of scalability issues driven by the depth of computations that need to be supported for privacy-preserving genome sequence search. In this paper, we build off of earlier privacy-preserving genome sequence search results to design, implement and compare two approaches to a client-server style system for privacy-preserving genome sequence search. There is a myriad of options and design trade-offs associated with the application of homomorphic encryption in this domain driven, for example, by choices in data encoding, scheme selection, and even encryption software library. We particularly focus on the use of the BGV and BFV homomorphic encryption schemes provided by the HElib and PALISADE open-source homomorphic encryption software libraries. Our results show that using the BFV-based approach in PALISADE provides optimal results for this application over our sample data.

Lattice trapdoors are an important primitive used in a wide range of cryptographic protocols, such as identity-based encryption (IBE), attribute-based encryption, functional encryption, and program obfuscation. In this paper, we present software implementations of the Gentry-Peikert-Vaikuntanathan (GPV) digital signature, IBE and ciphertext-policy attribute-based encryption (CP-ABE) schemes based on an efficient Gaussian sampling algorithm for trapdoor lattices, and demonstrate that these three important cryptographic protocols are practical. One important aspect of our implementation is that it supports prime moduli, which are required in many cryptographic schemes. Also, our implementation uses bases larger than two for the gadget matrix whereas most previous implementations use the binary base. We show that the use of higher bases significantly decreases execution times and storage requirements. We adapt IBE and CP-ABE schemes originally based on learning with errors (LWE) hardness assumptions to a more efficient Ring LWE (RLWE) construction. To the best of our knowledge, ours are the first implementations employing the Gaussian sampling for non-binary bases of the gadget matrix. The experimental results demonstrate that our lattice-based signature, IBE and CP-ABE implementations, which are based on standard assumptions with post-quantum security, provide a performance comparable to the recent state-of-the-art implementation works based on stronger/non-post-quantum assumptions.

The 6th Workshop on Encrypted Computing and Applied Homomorphic Cryptography is held in Toronto, ON, Canada on October 19th, 2018, co-located with the ACM Conference on Computer and Communications Security (CCS). The workshop aims to bring together professionals, researchers and practitioners from academia, industry and government in the area of computer security and applied cryptography with an interest in practical applications of homomorphic encryption, encrypted computing, functional encryption and secure function evaluation, private information retrieval and searchable encryption. The workshop will feature 6 exciting talks on different aspects of secure computation and a forum to discuss current and future challenges.

We address the practicality challenges of secure program obfuscation by implementing, optimizing, and experimentally assessing an approach to securely obfuscate conjunction programs proposed in [1]. Conjunction programs evaluate functionsf(x1,...,xL) = Λi∈Iyi, whereyiis eitherxior ¬xiandI⊆ [L], and can be used as classifiers. Our obfuscation approach satisfies distributional Virtual Black Box (VBB) security based on reasonable hardness assumptions, namely an entropic variant of the Ring Learning with Errors (Ring-LWE) assumption. Prior implementations of secure program obfuscation techniques support either trivial programs like point functions, or support the obfuscation of more general but less efficient branching programs to satisfy Indistinguishability Obfuscation (IO), a weaker security model. Further, the more general implemented techniques, rather than relying on standard assumptions, base their security on conjectures that have been shown to be theoretically vulnerable. Our work is the first implementation of non-trivial program obfuscation based on polynomial rings. Our contributions include multiple design and implementation advances resulting in reduced program size, obfuscation runtime, and evaluation runtime by many orders of magnitude. We implement our design in software and experimentally assess performance in a commercially available multi-core computing environment. Our implementation achieves runtimes of 6.7 hours to securely obfuscate a 64-bit conjunction program and 2.5 seconds to evaluate this program over an arbitrary input. We are also able to obfuscate a 32-bit conjunction program with 53 bits of security in 7 minutes and evaluate the obfuscated program in 43 milliseconds on a commodity desktop computer, which implies that 32-bit conjunction obfuscation is already practical. Our graph-induced (directed) encoding implementation runs up to 25 levels, which is higher than previously reported in the literature for this encoding. Our design and implementation advances are applicable to obfuscating more general compute-and-compare programs and can also be used for many cryptographic schemes based on lattice trapdoors.

In this paper, we report on our implementation of a lattice-based key-policy attribute-based encryption (KP-ABE) scheme, which uses short secret keys. The particular KP-ABE scheme can be used directly for attribute-based access control applications, as well as a building block in more involved applications and cryptographic schemes, such as audit log encryption, targeted broadcast encryption, functional encryption, and program obfuscation. We adapt a recently proposed KP-ABE scheme based on the learning with errors (LWE) problem to a more efficient scheme based on the ring learning with errors (RLWE) problem, and demonstrate an implementation that can be used in practical applications. Our state-of-the-art implementation on graphics processing units shows that the homomorphic public key and ciphertext evaluation operations, which dominate the execution time of the KP-ABE scheme, can be performed in a reasonably short amount of time. Our practicality results also hold when scaled to a relatively large number of attributes. To the best of our knowledge, this is the first KP-ABE implementation that supports both ciphertext and public key homomorphism, and the only experimental practicality results reported in this paper.

This workshop addresses the technical challenges arising from our current interconnected society. Multitudes of devices and people can be connected to each other by intelligent algorithms, apps, social networks, and the infrastructure set by Internet of Things (IoT). As more people and their devices are connected without much restriction, the issues of security, privacy, and trust remain a challenge. Multimedia in IoT services should provide a robust and resilient security platforms and solutions against any unauthorized access. Recent literature shows increased concerns about hacking, security breaches, data manipulation, social engineering, and new attack methods. Malware can be hidden within multimedia files and visiting infected websites can trigger its download to victims' machines. There are a multitude of techniques to steal personal information and other sensitive media for unauthorized dissemination; imposters/identity thefts are common in social networks. In order to demonstrate the effectiveness of resilient security and privacy solutions, methods such as new standards, advance cryptography, improved algorithms for intrusion detection, personalized privacy, and isolation of questionable or malicious files can be used independently or all together to minimize the threats.

We present an approach to scalable, secure voice over IP (VoIP) teleconferencing on commodity mobile devices and data networks with end-to-end homomorphic encryption. We assume an honest-but-curious threat model where an adversary, despite observing all communications between participants and having access to teleconferencing servers, is unable to obtain unencrypted data and subsequently listen to the conversation. Prior secure VoIP teleconferencing services have relied on: 1) teleconferencing clients to maintain point-to-point encrypted links with other clients or 2) a teleconferencing server which can access and manipulate VoIP streams unencrypted. Our approach mixes VoIP data streams at a single teleconferencing server only while encrypted. Data streams are never decrypted at the teleconferencing server. Innovation comes from an efficient VoIP encoding to reduce circuit depth for homomorphic mixing of encrypted VoIP data, parameterization for low bandwidth usage and integration into an existing open-source VoIP infrastructure. We experimentally evaluate on commodity iPhones, mixing at the VoIP servers on lowest cost Amazon AWS cloud server instances and communicating on commercial data networks and 802.11n access points.

We develop two IND-CPA-secure multihop unidirectional Proxy Re-Encryption (PRE) schemes by applying the Ring-LWE (RLWE) key switching approach from the homomorphic encryption literature. Unidirectional PRE is ideal for secure publish-subscribe operations where a publisher encrypts information using a public key without knowing upfront who the subscriber will be and what private key will be used for decryption. The proposed PRE schemes provide a multihop capability, meaning that when PRE-encrypted information is published onto a PRE-enabled server, the server can either delegate access to specific clients or enable other servers the right to delegate access. Our first scheme (which we call NTRU-ABD-PRE) is based on a variant of the NTRU-RLWE homomorphic encryption scheme. Our second and main PRE scheme (which we call BV-PRE) is built on top of the Brakerski-Vaikuntanathan (BV) homomorphic encryption scheme and relies solely on the RLWE assumption. We present an open-source C++ implementation of both schemes and discuss several algorithmic and software optimizations. We examine parameter selection tradeoffs in the context of security, runtime/latency, throughput, ciphertext expansion, memory usage, and multihop capabilities. Our experimental analysis demonstrates that BV-PRE outperforms NTRU-ABD-PRE in both single-hop and multihop settings. The BV-PRE scheme has a lower time and space complexity than existing IND-CPA-secure lattice-based PRE schemes and requires small concrete parameters, making the scheme computationally efficient for use on low-resource embedded systems while still providing 100 bits of security. We present practical recommendations for applying the PRE schemes to several use cases of ad hoc information sharing for publish-subscribe operations.

Monitoring and encryption are essential to secure today's computer networks. Monitoring network traffic data can be especially useful to protect against data exfiltration by detecting signatures in file metadata to identify especially sensitive files that should not be publicly released. Encryption restricts the visibility of signatures, but this may be needed because some signatures used to protect against data exfiltration may themselves be sensitive, as knowledge of signatures could help adversaries circumvent monitoring. We present results on a prototype exfiltration guard to securely and privately monitor flows of encrypted information for encrypted signatures without requiring the decryption of the data flows or the signatures or the sharing of decryption keys. Our approach is based on using homomorphic encryption to enables secure computing on encrypted data. We show experimental results with a prototype proof-of-concept encrypted data guard running on a commodity computing hardware. These designs point to possible future advances driven by ongoing homomorphic encryption improvements to compute on encrypted data for more advanced and secure filtering and exfiltration protection schemes.

Embedded medical devices, such as wearable devices, are becoming increasingly common, but data from these devices is both very private and highly vulnerable to theft. Data needs to be collected from multiple devices to improve the effectiveness of treatment. The medical devices, data processing sites and intended care givers are often geographically distributed, and operate on different time scales with collected data being aggregated for days or months before analysis and usage. Current approaches to data security do not provide a framework for end-to-end protection, where data can always be encrypted but still used effectively. We present a security architecture with end-to-end encryption that supports 1) secure collection of data from embedded medical devices, 2) protected computing on this data in low-cost commodity cloud environment and 3) restricts the delegation of access to this data to designated recipients. The basis of the architecture comes from recent advances in lattice encryption technologies. This approach leverages recent breakthroughs in Homomorphic Encryption (HE) and Proxy Re-Encryption (PRE) that would practically support specific data aggregation, processing and distribution needs of a secure medical data architecture. This architecture lowers health care data system costs by securely outsourcing computation to cloud computing environments while simultaneously reducing vulnerabilities to some of the most problematic security challenges such as insider attacks and enables additional cost savings with lower-cost embedded medical devices.

We present a scalable, hierarchical control system for the dynamic resource management of a distributed real-time embedded (DRE) system. This DRE is inspired by the DARPA adaptive and reflective middleware systems (ARMS) program. The goal of the control system is to simultaneously manage multiple resources and QoS concerns using a utility-driven approach for decision making and performance evaluation. At each level of the control hierarchy there are multiple local controllers which autonomously make decisions to optimize their local utility. The controllers in the hierarchy can use different, localized resource control algorithms and the system's user can tune the operations of the local controllers. We discuss how the selections of local control algorithms affect the behavior of the overall system. The control system is designed to be easily adaptable to other multi-tiered DRE systems.

This paper discusses modeling and simulation issues associated with the stochastic behavior of a special type of a computer worm called a random constant scanning (RCS) worm. Although these worms propagate by randomly scanning network addresses to find hosts that are susceptible to infection, traditional RCS worm models are fundamentally deterministic. A density-dependent Markov jump process model for RCS worms is presented and analyzed. Conditions are shown for when worm models can safely ignore some stochastic properties of RCS worm propagation. A computationally simple hybrid deterministic/stochastic model for the observed scanning behavior on a local network due to the global propagation of an RCS scanning worm is also presented and discussed.