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.

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.

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.

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.

Efficient homomorphic encryption enables the construction of an encrypted computer system. Previous work has shown how this can be achieved using only arithmetic representations of simple demultiplexer circuits. This poster extends the results by introducing a caching mechanism for oblivious memory access, by far the most time-consuming building block of a recently proposed sample machine architecture. The construction allows to significantly accelerate homomorphically encrypted machine operation while still preserving obliviousness of memory access, control unit operation and functional components.

Currently location privacy settings of mobile operating systems are limited to the option of enabling or disabling the use of location completely or on a per-app basis. When location use is allowed, users always reveal their location in full precision even to apps that do not need it. For instance, weather forecast apps and navigation apps both get the most exact location a device can determine. Up to now, mobile privacy research was focused on the recognition and prevention of disclosure of private data. This includes location data, but does not extend to privacy in use cases where users do want to disclose their location - but not in full detail. However, the increasing adoption of smartphones entails the increasing use of location-based services as well. Users want to use these services, but have privacy concerns. As many location-based services do not require exact locations, user privacy can be increased by only disclosing location in such detail as required for the respective service to function. To enable users to restrict the accuracy of location data that is revealed to apps, we created a location privacy framework that allows per-app location obfuscation. The framework allows easy integration of different obfuscation algorithms into the Android system. We present both on-device obfuscation and service-based obfuscation and evaluate our framework.

Data protection is a challenge when outsourcing medical analysis, especially if one is dealing with patient related data. While securing transfer channels is possible using encryption mechanisms, protecting the data during analyses is difficult as it usually involves processing steps on the plain data. A common use case in bioinformatics is when a scientist searches for a biological sequence of amino acids or DNA nucleotides in a library or database of sequences to identify similarities. Most such search algorithms are optimized for speed with less or no consideration for data protection. Fast algorithms are especially necessary because of the immense search space represented for instance by the genome or proteome of complex organisms. We propose a new secure exact term search algorithm based on Bloom filters. Our algorithm retains data privacy by using Obfuscated Bloom filters while maintaining the performance needed for real-life applications. The results can then be further aggregated using Homomorphic Cryptography to allow exact-match searching. The proposed system facilitates outsourcing exact term search of sensitive data to on-demand resources in a way which conforms to best practice of data protection.

The growing adoption of cloud technology in sensitive application domains, such as medicine, gives rise to new problems in maintaining the privacy of the involved parties during authorisation. In such domains, an honest but curious service provider can derive sensitive information purely from the authorisation process. In this paper, we present a detailed discussion of this rising problem including a concrete example and argue the need for the combination of hidden credentials, hidden policies and hidden decisions. We then show that mechanisms explored in previous work only cover individual aspects of this problem, but do not achieve a comprehensive solution without making restrictive assumptions on the resources, policies or subjects to be protected. As a first step towards solving this problem, we introduce an abstract foundation for using homomorphic cryptography to provide the required combination of privacy as a wrapper for other access control (AC) mechanisms. We achieve hidden policies, hidden credentials and even hidden access control decisions, so that the subject of an AC request only learns whether or not access was granted. Meanwhile, the provider of a resource learns nothing at the policy decision point and only access frequencies for individual resources at the policy enforcement point. We postulate that this is the maximum achievable level of protection in the authorisation process, without making restrictive assumptions on the resources, policies or subjects to be protected. Once homomorphic cryptography achieves satisfactory performance, our model can be used to transparently add this protection to other access control models.

Homomorphic cryptography has received a lot of attention due to potentially ground breaking advances in cryptography. However it is also surrounded by a lot of hyperbole such as "ground breaking advances", "this will solve all Cloud computing problems" to "it is completely impractical" and "it will never work for real world problems". In previous work we showed how homomorphic encryption can be used to execute arbitrary programs in encrypted space, showing that at least in theory real world problems can be computed protected by homomorphic cryptography without losing generality. In this paper we expand our work to evaluate how practical current homomorphic cryptography based on the Smart-Vercauteren system is for executing arbitrary programs on untrusted resources. For this we present the implementation of a method to compute non-linear secret programs on an untrusted resource using encrypted circuits embedded in an encrypted virtual machine. We successively show how a processor architecture using encrypted circuits can be implemented so it can support read and write memory access, dynamic parameters and non-linear programs that render branch-decisions at runtime. The system comprises the runtime environment for program execution and an assembler to generate the encrypted machine code. We present performance evaluation of the sub-components as well as the complete system. The system represents a flexible prototype for homomorphic program execution in software and system architecture.

In today's distributed computing environments, like Grids and Clouds, authentication and authorization decisions take place in the middleware or on the compute and storage resources themselves. Thus, in both cases the decision is felled within the local network of the hosting organization. This is due to several drawbacks in common firewalls. For one, most firewalls only utilize the tupel of IP addresses, port numbers and protocol parameters to decide which connection are legitimate and which are not. This offers minimal configurability, which in complex environments like the Grid or the Cloud is not sufficient for optimal fine grained decisions. Also, the inability of application level firewalls to deal with dynamically opened server ports for encrypted connections like they are in use by GridFTP require very lax firewall rules to be set, if the Grid or Cloud is to operate unhindered.