We propose a maximum toroidal distance (MTD) code for lattice-based public-key encryption (PKE). By formulating the encryption encoding problem as the selection of $2^\ell$ points in the discrete $\ell$-dimensional torus $\mathbb{Z}_q^\ell$, the proposed construction maximizes the minimum $L_2$-norm toroidal distance to reduce the decryption failure rate (DFR) in post-quantum schemes such as the NIST ML-KEM (Crystals-Kyber). For $\ell = 2$, we show that the MTD code is essentially a variant of the Minal code recently introduced at IACR CHES 2025. For $\ell = 4$, we present a construction based on the $D_4$ lattice that achieves the largest known toroidal distance, while for $\ell = 8$, the MTD code corresponds to $2E_8$ lattice points in $\mathbb{Z}_4^8$. Numerical evaluations under the Kyber setting show that the proposed codes outperform both Minal and maximum Lee-distance ($L_1$-norm) codes in DFR for $\ell > 2$, while matching Minal code performance for $\ell = 2$.

The use of generative AI (genAI) in higher education is rapidly evolving, provoking both optimism and concern among educators. While some students embrace genAI tools as learning aids, others, including many educators, remain cautious about their implications for critical thinking and academic integrity. Accepting that genAI is readily available and banning its use is not feasible, we explore how it might be integrated meaningfully into pedagogy through the lens of Transformative Learning Theory (TLT). This study investigates how genAI tools influence student learning in an IT Forensics course using diverging assessments, a form of assessment-as-learning where students receive the same authentic tasks but unique data inputs. We examine three research questions addressing genAI's impact on learning strategies, its role in supporting assessment-as-learning tasks, and how it fosters critical reflection and transformation in student learning. Drawing on interviews with 14 students, our findings suggest that, when scaffolded appropriately, genAI use within diverging assessments can catalyze transformative learning by provoking disorienting dilemmas, encouraging reflection, and reshaping problem-solving approaches. Finally, implications for teaching practice and assessment design are discussed.

In 2023, the National Institute of Standards and Technology (NIST) announced its post-quantum cryptography (PQC) standards; CRYSTALS-Dilithium, Falcon and SPHINCS+ as digital signatures and CRYSTALS-Kyber as the key-encapsulation mechanism (KEM) (or put simply, encryption). These PQC standards are to replace today’s quantum-vulnerable cryptography algorithms, currently securing digital systems, to protect against emerging quantum computing threats. One of the main challenges in transitioning into such standards is to educate the current and future IT/Cybersecurity workforce about PQC, particularly around the practical aspects. In particular, the original proposers of the selected algorithms only provided the reference (and optimized) software implementations of them. The final NIST standard specifications will only be equipped with mathematical explanations and test vectors. Hence, there are not many custom-designed educational content, assessment, and practical tools for PQC. In this experience paper, we introduce and discuss our PQC educational program, PQCIP, targeted at industry and governmental IT/Cybersecurity professionals. PQCIP has significantly contributed to its participants’ learning and engagement by providing tailored high-quality content, hands-on assessments, and strategic planning, making them ready to develop evaluated transition plans for their organizations and/or governments. We have also created custom software interfaces for CRYSTALS-Kyber, the NIST PQC standard for KEM. Using the developed interface along with Open Quantum Safe (OQS) software library for OpenSSL, we bridge a gap in available educational tools for PQC training. This tool has been shown to enhance the participants’ understanding of PQC’s practical applications and improve their engagement with highly technical cryptographic contents.

This paper investigates the downlink energy efficiency (EE) optimization for cell-free massive multiple input multiple output (CF-mMIMO) systems subject to ultra-reliable and low-latency communication (URLLC) requirements. To achieve superior performance, we jointly consider the impacts of power allocation, access point (AP)-user association, and AP sleep modes under the finite blocklength (FBL) regime, leading to a challenging mixed-integer (MI) non-convex optimization problem. Utilizing a sequential convex approximation (SCA) framework, we first propose the SCA-Relaxation algorithm to convert the original problem into a series of second-order cone programming (SOCP) sub-problems, which can be efficiently addressed via modern convex programming solvers. Moreover, for further reducing computational complexity, we approximate the original problem as a continuous-variable optimization and tackle it via a combination of the Dinkelbach transformation, penalty functions, as well as an accelerated proximal gradient method with adaptive momentum, resulting in the proposed low complexity EE maximization (LCEE-max) algorithm. Besides, the related convergence and complexity analysis of these two algorithms are also presented in detail. Simulation results demonstrate that compared to the state-of-the-art baseline algorithm, the proposed two algorithms achieve the EE improvements of approximately 40% and 30%, respectively, along with a substantial reduction in complexity, thereby enabling efficient and fast resource allocation in CF-mMIMO-enabled URLLC scenarios.

Diverging assessment maintains a common question set for all students but varies the input data so that each student has a unique problem to solve. It is an approach in student assessment that offers a unique and authentic learning experience. Although such assessments have been implemented in computing courses, their effectiveness and students' perceptions in different contexts remain unexplored. In this paper, we investigate student perspectives on diverging assessment. We surveyed students in four courses across three different universities. Each surveyed student was enrolled in one of the four courses on networking, operation systems, digital forensics or ethical hacking. Each course featured at least one diverging assessment. The students' overall perceptions about diverging assessments and three different aspects of diverging assessment, namely authenticity, assessment-as-learning, and academic integrity, are surveyed, reported, and analyzed.

Traditional explicit and implicit watermarking methods have long been employed to protect multimedia content. However, while implicit watermarks offer robustness, integrating them into real-time streaming environments introduces technical challenges, such as increased latency and high computational overhead. As a result, major platforms like YouTube and broadcast channels continue to rely on visible, image-based watermarks, reasoning that removing such marks in real-time is non-trivial. In image processing, deep learning-based inpainting techniques have been used to remove visible watermarks. Yet, traditional supervised convolutional neural networks (CNNs) often depend on paired training data, which may not be available in practice. Chunwei Tian et al. proposed the Self-Supervised CNN (SWCNN) [8], which circumvents this dependency by generating its own reference images. Through a lightweight heterogeneous U-Net architecture, SWCNN effectively adapts to various watermark distributions, maintaining precision while reducing computational costs. Despite these advances, the original SWCNN implementation still struggles to meet the speed and latency demands of real-time video watermark removal, particularly for live streaming. To address this limitation, we introduce half-precision (FP16) computation, preprocessing strategies, and multi-threaded optimizations to SWCNN. Our enhanced approach achieves real-time performance not only for locally streamed video via VLC media player but also for live internet sources, such as Twitch streams. Experimental results confirm that our optimized SWCNN improves both watermark removal quality and frame rates across different resolutions, making it practical for real-time deployment. To support ongoing research and ensure reproducibility, we have created a new dataset of watermarked video frames. This work not only advances the field of video watermark removal but also exposes potential vulnerabilities in current watermarking strategies, reinforcing the need for stronger copyright protection measures. The code and all video demonstrations are available in the Supplemental material.

This article formalises watchtower and its different properties includingagility,privacyagainst both watchtower and third parties,fairnesswith respect to both watchtower and its client andcoverage. We also evaluate the existing schemes regarding these properties and show they cannot achieve all properties altogether. Furthermore, we prove that there is a trade-off between the level of fairness that a watchtower provides to its clients and the coverage it can achieve. We also introduce FPPW, the first Fair and Privacy-Preserving Watchtower for Bitcoin. This new scheme provides fairness with respect to all channel participants including both channel parties and the watchtower. It means the funds of any honest channel participants are safe even assuming that the other two participants are corrupted and/or collude with each other. Furthermore, the watchtower in FPPW learns no information about the off-chain transactions and hence FPPW provides privacy against the watchtower. We also show that FPPW coverage, i.e., the total capacity of channels that an FPPW watchtower can cover, is higher than that of PISA and Cerberus and FPPW can be implemented without any update in the Bitcoin script.

We introduce the first candidate Lattice-based designated verifier (DV) zero knowledge sUccinct Non-interactive Argument (ZK-SNARG) protocol, named LUNA, with quasi-optimal proof length (quasi-linear in the security/privacy parameter). By simply relying on mildly stronger security assumptions, LUNA is also a candidate ZK-SNARK (i.e. argument of knowledge). LUNA achieves significant improvements in concrete proof sizes, reaching below 6 KB (compared to >32 KB in prior work) for 128-bit security/privacy level. To achieve our quasi-optimal succinct LUNA, we give a new regularity result for 'private' re-randomization of Module LWE (MLWE) samples using discrete Gaussian randomization vectors, also known as a lattice-based leftover hash lemma with leakage, which applies with a discrete Gaussian re-randomization parameter that is polynomial in the statistical privacy parameter (avoiding exponential smudging), and hides the coset of the re-randomization vector support set. Along the way, we derive bounds on the smoothing parameter of the intersection of short integer solution (SIS), gadget, and Gaussian perp module lattices over the power of 2 cyclotomic rings. We then introduce a new candidate linear-only homomorphic encryption scheme called Module Half-GSW (HGSW), and apply our regularity theorem to provide smudging-free circuit-private homomorphic linear operations for Module HGSW. Our implementation and experimental performance evaluation show that, for typical instance sizes, Module HGSW provides favourable performance for ZK-SNARG applications involving lightweight verifiers. It enables significantly (around 5x) shorter proof lengths while speeding up CRS generation and encryption time by 4-16x and speeding up decryption time by 4.3x, while incurring just 1.2-2x time overhead in linear homomorphic proof generation operations, compared to a Regev encryption used in prior work in the ZK-SNARG context. We believe our techniques are of independent interest and will find application in other privacy-preserving lattice-based protocols.

Module Learning with Errors (M-LWE) based key reconciliation mechanisms (KRM) can be viewed as quantizing an M-LWE sample according to a lattice codebook. This paper describes a generic M-LWE-based KRM framework, valid for any dimensional lattices and any modulus$q$without a dither. Our main result is an explicit upper bound on the decryption failure rate (DFR) of M-LWE-based KRM. This bound allows us to construct optimal lattice quantizers to reduce the DFR and communication cost simultaneously. Moreover, we present a KRM scheme using the same security parameters$(q, k, \eta_{1}, \eta_{2})$as in Kyber. Compared with Kyber, the communication cost is reduced by up to 36.47% and the DFR is reduced by a factor of up to 299. The security arguments remain the same as Kyber.

In this experience paper, we present ALAN, a framework to automate the generation of authentic assessment tasks in networking courses (NC). Using ALAN, all students in a cohort complete a set of assessment tasks generated from the same skeleton, with each student having their own parameters as input. The way we run ALAN assessments fosters students' self-regulation and peer learning and activates students' engagement in learning through assessment. We present three different ALAN assessments. We finally report on student perceptions and satisfaction and reflect on our experience.

In this experience paper, we introduce the concept of 'diverging assessments', process-based assessments designed so that they become unique for each student while all students see a common skeleton. We present experiences with diverging assessments in the contexts of computer networks, operating systems, ethical hacking, and software development. All the given examples allow the use of generative-AI-based tools, are authentic, and are designed to generate learning opportunities that foster students' meta-cognition. Finally, we reflect upon these experiences in five different courses across four universities, showing how diverging assessments enhance students' learning while respecting academic integrity.

The United Kingdom (UK) government is considering advanced primitives such as identity-based encryption (IBE) for adoption as they transition their public-safety communications network from TETRA to an LTE-based service. However, the current LTE standard relies on elliptic-curve-based IBE, which will be vulnerable to quantum computing attacks, expected within the next 20–30 years. Lattices can provide quantum-safe alternatives for IBE. These schemes have shown promising results in terms of practicality. To date, several IBE schemes over lattices have been proposed, but there has been little in the way of practical evaluation. This paper provides the first complete optimised practical implementation and benchmarking of Latte, a promising Hierarchical IBE (HIBE) scheme proposed by the UK National Cyber Security Centre (NCSC) in 2017 and endorsed by European Telecommunications Standards Institute (ETSI). We propose optimisations for the KeyGen, Delegate, Extract and Gaussian sampling components of Latte, to increase attack costs, reduce decryption key lengths by 2x–3x, ciphertext sizes by up to 33%, and improve speed. In addition, we conduct a precision analysis, bounding the Rényi divergence of the distribution of the real Gaussian sampling procedures from the ideal distribution in corroboration of our claimed security levels. Our resulting implementation of the Delegate function takes 0.4 seconds at 80-bit security level on a desktop machine at 4.2GHz, significantly faster than the order of minutes estimated in the ETSI technical report. Furthermore, our optimised Latte Encrypt/Decrypt implementation reaches speeds up to 9.7x faster than the ETSI implementation.

The US National Institute of Standards and Technology initiated a standardization process for post-quantum cryptography in 2017, with the aim of selecting key encapsulation mechanisms and signature schemes that can withstand the threat from emerging quantum computers. In 2022, Falcon was selected as one of the standard signature schemes, eventually attracting effort to optimize the implementation of Falcon on various hardware architectures for practical applications. Recently, Mitaka was proposed as an alternative to Falcon, allowing parallel execution of most of its operations. These recent advancements motivate us to develop high throughput implementations of Falcon and Mitaka signature schemes on Graphics Processing Units (GPUs), a massively parallel architecture widely available on cloud service platforms. In this paper, we propose the first parallel implementation of Falcon on various GPUs. An iterative version of the sampling process in Falcon, which is also the most time-consuming Falcon operation, was developed. This allows us to implement Falcon signature generation without relying on expensive recursive function calls on GPUs. In addition, we propose a parallel random samples generation approach to accelerate the performance of Mitaka on GPUs. We evaluate our implementation techniques on state-of-the-art GPU architectures (RTX 3080, A100, T4 and V100). Experimental results show that our Falcon-512 implementation achieves 58,595 signatures/second and 2,721,562 verifications/second on an A100 GPU, which is$20.03\times$and$29.51\times$faster than the highly optimized AVX2 implementation on CPU. Our Mitaka implementation achieves 161,985 signatures/second and 1,421,046 verifications/second on the same GPU. Due to the adoption of a parallelizable sampling process, Mitaka signature generation enjoys$\approx 2$–$20 \times$higher throughput than Falcon on various GPUs. The high throughput signature generation and verification achieved by this work can be very useful in various emerging applications, including the Internet of Things.

In this work, we study the blockchain leader election problem. The purpose of such protocols is to elect a leader who decides on the next block to be appended to the blockchain, for each block proposal round. Solutions to this problem are vital for the security of blockchain systems. We introduce an efficient blockchain leader election method with security based solely on standard assumptions for cryptographic hash functions (rather than public-key cryptographic assumptions) and that does not involve a racing condition as in Proof-of-Work based approaches. Thanks to the former feature, our solution provides the highest confidence in security, even in the post-quantum era. A particularly scalable application of our solution is in the Proof-of-Stake setting, and we investigate our solution in the Algorand blockchain system. We believe our leader election approach can be easily adapted to a range of other blockchain settings.

Post-Quantum cryptography (PQC), in the past few years, constitutes the main driving force of the quantum resistance transition for security primitives, protocols and tools. TLS is one of the widely used security protocols that needs to be made quantum safe. However, PQC algorithms integration into TLS introduce various implementation overheads compared to traditional TLS that in battery powered embedded devices with constrained resources, cannot be overlooked. While there exist several works, evaluating the PQ TLS execution time overhead in embedded systems there are only a few that explore the PQ TLS energy consumption cost. In this paper, a thorough power/energy consumption evaluation and analysis of PQ TLS 1.3 on embedded systems has been made. A WolfSSL PQ TLS 1.3 custom implementation is used that integrates all the NIST PQC algorithms selected for standardisation as well as 2 out of 3 of those evaluated in NIST Round 4. Also 1 out of 2 of the BSI recommendations have been included. The PQ TLS 1.3 with the various PQC algorithms is deployed in a STM Nucleo evaluation board under a mutual and a unilateral client-server authentication scenario. The power and energy consumption collected results are analyzed in detail. The performed comparisons and overall analysis provide very interesting results indicating that the choice of the PQC algorithms in TLS 1.3 to be deployed on an embedded system may be very different depending on the device use as an authenticated or not authenticated, client or server. Also, the results indicate that in some cases, PQ TLS 1.3 implementations can be equally or more energy consumption efficient compared to traditional TLS 1.3.

In this experience paper, we present an automated assessment and marking generation framework to create capture-the-flag (CTF) questions in the context of Information Technology (IT) Forensics. This allows educators to generate many randomised Virtual Hard Disk (VHD) and packet capture (PCAP) files with different forensic artefacts for each student suitable for assessment tasks in disk-based and network-based forensic courses, respectively. These files are then inscribed inside quizzes, which are constructively aligned to what students have learned in their lecture and tutorial classes. We replaced our invigilated closed-book end-of-semester exams with these open-book multiple-attempt non-invigilated in-semester quizzes. We also conducted a survey asking students about, how the designed quizzes (1) were aligned with (and covering) the promised course learning outcomes, (2) were run to address academic integrity concerns, and (3) helped students manage their stress once their final exams are replaced by the presented quizzes.

Payment Channel Hub (PCH) is a promising solution to the scalability issue of first-generation blockchains or cryptocurrencies such as Bitcoin. It supports off-chain payments between a sender and a receiver through an intermediary (called the tumbler). Relationship anonymity and value privacy are desirable features of privacy-preserving PCHs, which prevent the tumbler from identifying the sender and receiver pairs as well as the payment amounts. To our knowledge, all existing Bitcoin-compatible PCH constructions that guarantee relationship anonymity allow only a (predefined) fixed payment amount. Thus, to achieve payments with different amounts, they would require either multiple PCH systems or running one PCH system multiple times. Neither of these solutions would be deemed practical.In this paper, we propose the first Bitcoin-compatible PCH that achieves relationship anonymity and supports variable amounts for payment. To achieve this, we have several layers of technical constructions, each of which could be of independent interest to the community. First, we propose BlindChannel, a novel bi-directional payment channel protocol for privacy-preserving payments, where one of the channel parties is unable to see the channel balances. Then, we further propose BlindHub, a three-party (sender, tumbler, receiver) protocol for private conditional payments, where the tumbler pays to the receiver only if the sender pays to the tumbler. The appealing additional feature of BlindHub is that the tumbler cannot link the sender and the receiver while supporting a variable payment amount. To construct BlindHub, we also introduce two new cryptographic primitives as building blocks, namely Blind Adaptor Signature (BAS), and Flexible Blind Conditional Signature (FBCS). BAS is an adaptor signature protocol built on top of a blind signature scheme. FBCS is a new cryptographic notion enabling us to provide an atomic and privacy-preserving PCH. Lastly, we instantiate both BlindChannel and BlindHub protocols and present implementation results to show their practicality.

Driven by the cloud-first initiative taken by various governments and companies, it has become a common practice to outsource spatial data to cloud servers for a wide range of applications such as location-based services and geographic information systems. Searchable encryption is a common practice for outsourcing spatial data which enables search over encrypted data by sacrificing the full security via leaking some information about the queries to the server. However, these inherent leakages could equip the server to learn beyond what is considered in the scheme, in the worst-case allowing it to reconstruct of the database. Recently, a novel form of database reconstruction attack against such kind of outsourced spatial data was introduced (Markatou and Tamassia, IACR ePrint 2020/284), which is performed using common leakages of searchable encryption schemes, i.e., access and search pattern leakages. An access pattern leakage is utilized to achieve an order reconstruction attack, whereas both access and search pattern leakages are exploited for the full database reconstruction attack. In this paper, we propose two novel schemes for outsourcing encrypted spatial data supporting dynamic range search. Our proposed schemes leverage R+tree to partition the dataset and binary secret sharing to support secure range search. They further provide backward and content privacy and do not leak the access pattern, therefore being resilient against the above mentioned database reconstruction attacks. The evaluations and results on the real-world dataset demonstrate the practicality of our schemes, due to (a) the minimal round-trip between the client and server, and (b) the low computation and storage overhead on the client side.

Network Function Virtualisation (NFV) advances the adoption of composable software middleboxes. Accordingly, cloud data centres become major NFV vendors for enterprise traffic processing. Due to the privacy concern of traffic redirection to the cloud, secure middlebox systems (e.g., BlindBox) draw much attention; they can process encrypted packets against encrypted rules directly. However, most of the existing systems supporting pattern matching based network functions require the enterprise gateway to tokenise packet payloads via sliding windows. Such tokenisation induces a considerable communication overhead, which can be over 100× to the packet size. To overcome this bottleneck, in this article, we propose the first bandwidth-efficient encrypted pattern matching protocol for secure middleboxes. We resort to a primitive called symmetric hidden vector encryption (SHVE), and propose a variant of it, aka SHVE+, to achieve constant and moderate communication cost. To speed up, we devise encrypted filters to reduce the number of accesses to SHVE+ during matching highly. We formalise the security of our proposed protocol and conduct comprehensive evaluations over real-world rulesets and traffic dumps. The results show that our design can inspect a packet over 20 k rules within 100$\mu$s. Compared to prior work, it brings a saving of 94 percent in bandwidth consumption.

In this article, we introduce a new mechanism for constructing multi-client searchable encryption (SE). By tactfully leveraging the RSA-function, we propose the first multi-client SE protocol that successfully avoids per-query interaction between data owner and client. Therefore, our approach significantly reduces the communication cost by eliminating the need for data owner to authorize client queries at all times. To be compatible with the RSA-based approach, we also present a deterministic and memory-efficient ‘keyword to prime’ hash function, which may be of independent interest. Further, to improve efficiency, we put forward a more generic construction from set-constrained PRFs. The construction not only inherits the merits of our first protocol, but also achieves an enhanced security (against untrusted clients), where colluding attack among clients is also taken into account. Both protocols are instantiated via the recent representative SE protocol by Cashet al.with the support of boolean queries. At last, we implement our proposed protocols and comprehensively evaluate their performance to demonstrate their practicability and scalability.

In this paper, we consider the problem of information theoretic security for a single-input single-output (SISO) relay-aided network in the presence of an adaptive eavesdropper. We assess the impact of deceptive friendly jammers on the secrecy of communication in this network when countering adaptive eavesdroppers. Specifically, we derive the secrecy capacity and secrecy outage probability of the network and compare the results in the absence and presence of a deceptive friendly jammer. Our results show that the secrecy capacity of the network increases while the achievable secrecy outage probability decreases significantly in the presence of friendly jammer to nullify the effect of the adversary. Numerical results, obtained through computer simulations, under different scenarios of varying jamming power and average main channel gain to average eavesdropper channel gain ratio demonstrate the effectiveness of friendly jammer in providing physical layer security.

Outlier detection is widely used in practice to track the anomaly on incremental data sets, such as network traffic and system logs. However, these data sets often involve sensitive information, and sharing the data to third parties for anomaly detection raises privacy concerns. In this article, we present a privacy-preserving outlier detection (PPOD) protocol for incremental data sets. The protocol decomposes the outlier detection algorithm into several phases and recognizes the necessary cryptographic operations in each phase. It realizes several cryptographic modules via efficient and interchangeable protocols to support the above cryptographic operations and composes them in the overall protocol to enable outlier detection over encrypted data sets. To support efficient updates, it integrates the sliding window model to periodically evict the expired data in order to maintain a constant update time. We build a prototype of PPOD and systematically evaluates the cryptographic modules and the overall protocols under various parameter settings. Our results show that PPOD can handle encrypted incremental data sets with a moderate computation and communication cost.

The discrete Gaussian sampler is one of the fundamental tools in implementing lattice-based cryptosystems. However, a naive discrete Gaussian sampling implementation suffers from side-channel vulnerabilities, and the existing countermeasures usually introduce significant overhead in either the running speed or the memory consumption. In this paper, we propose a fast, compact, and constant-time implementation of the binary sampling algorithm, originally introduced in the BLISS signature scheme. Our implementation adapts the Rényi divergence and the transcendental function polynomial approximation techniques. The efficiency of our scheme is independent of the standard deviation, and we show evidence that our implementations are either faster or more compact than several existing constant-time samplers. In addition, we show the performance of our implementation techniques applied to and integrated with two existing signature schemes: qTesla and Falcon. On the other hand, the convolution theorems are typically adapted to sample from larger standard deviations, by combining samples with much smaller standard deviations. As an additional contribution, we show better parameters for the convolution theorems.

In this paper, we develop an orthogonal precoding scheme for integer-forcing (IF) linear receivers using the steepest gradient algorithm. Although this scheme can be viewed as a special case of the unitary precoded integer-forcing (UPIF), it has two major advantages. First, the orthogonal precoding outperforms its unitary counterpart in terms of achievable rate, outage probability, and error rate. We verify this advantage via theoretical and numerical analyses. Second, it exhibits lower complexity as the dimension of orthogonal matrices is half that of unitary matrices in the real-valued domain. For finding “good” orthogonal precoder matrices, we propose an efficient algorithm based on the steepest gradient algorithm that exploits the geometrical properties of orthogonal matrices as a Lie group. The proposed algorithm has low complexity and can be easily applied to an arbitrary MIMO configuration. We also confirm numerically that the proposed orthogonal precoding outperforms UPIF type II in some scenarios and the X-precoder in high-order QAM schemes, e.g., 64- and 256-QAM.

This paper focuses on orthogonal precoding for integer-forcing linear receiver and shows it has two advantages over unitary precoding. Orthogonal precoding exhibits lower complexity than unitary precoding because the dimension of orthogonal matrices is half that of unitary matrices for a fixed number of antennas. Moreover, orthogonal precoding outperforms unitary precoding in terms of achievable rate and error-rate. Despite its promising advantages, it is not easy to find the optimal precoding matrices because it involves an orthogonality constraint and the shortest lattice vector problem. To solve this, we separate the optimization problem into two sub-problems and propose methods based on the steepest gradient with Lie groups and a random search algorithm. The proposed methods have low complexity and are applicable to any MIMO dimension. For high-order QAM, the proposed orthogonal precoder outperforms X-precoders which are designed specifically for QAM.

The recently proposed Oblivious Cross-Tags (OXT) protocol (CRYPTO 2013) has broken new ground in designing efficient searchable symmetric encryption (SSE) protocol with support for conjunctive keyword search in a single-writer single-reader framework. While the OXT protocol offers high performance by adopting a number of specialised data-structures, it also trades-off security by leaking 'partial' database information to the server. Recent attacks have exploited similar partial information leakage to breach database confidentiality. Consequently, it is an open problem to design SSE protocols that plug such leakages while retaining similar efficiency. In this paper, we propose a new SSE protocol, called Hidden Cross-Tags (HXT), that removes 'Keyword Pair Result Pattern' (KPRP) leakage for conjunctive keyword search. We avoid this leakage by adopting two additional cryptographic primitives - Hidden Vector Encryption (HVE) and probabilistic (Bloom filter) indexing into the HXT protocol. We propose a 'lightweight' HVE scheme that only uses efficient symmetric-key building blocks, and entirely avoids elliptic curve-based operations. At the same time, it affords selective simulation-security against an unbounded number of secret-key queries. Adopting this efficient HVE scheme, the overall practical storage and computational overheads of HXT over OXT are relatively small (no more than 10% for two keywords query, and 21% for six keywords query), while providing a higher level of security.

Symmetric Searchable Encryption (SSE) has received wide attention due to its practical application in searching on encrypted data. Beyond search, data addition and deletion are also supported in dynamic SSE schemes. Unfortunately, these update operations leak some information of updated data. To address this issue, forward-secure SSE is actively explored to protect the relations of newly updated data and previously searched keywords. On the contrary, little work has been done in backward security, which enforces that search should not reveal information of deleted data. In this paper, we propose the first practical and non-interactive backward-secure SSE scheme. In particular, we introduce a new form of symmetric encryption, named symmetric puncturable encryption (SPE), and construct a generic primitive from simple cryptographic tools. Based on this primitive, we then present a backward-secure SSE scheme that can revoke a server's searching ability on deleted data. We instantiate our scheme with a practical puncturable pseudorandom function and implement it on a large dataset. The experimental results demonstrate its efficiency and scalability. Compared to the state-of-the-art, our scheme achieves a speedup of almost 50x in search latency, and a saving of 62% in server storage consumption.

Neural network decoding algorithms are recently introduced by Nachmani et al. to decode high-density parity-check (HDPC) codes. In contrast with iterative decoding algorithms such as sum-product or min-sum algorithms in which the weight of each edge is set to 1, in the neural network decoding algorithms, the weight of every edge depends on its impact in the transmitted codeword. In this paper, we provide a novel feed-forward neural network lattice decoding algorithm suitable to decode lattices constructed based on Construction A, whose underlying codes have HDPC matrices. We first establish the concept of feed-forward neural network for HDPC codes and improve their decoding algorithms compared to Nachmani et al. We then apply our proposed decoder for a Construction A lattice with HDPC underlying code, for which the well-known iterative decoding algorithms show poor performances. The main advantage of our proposed algorithm is that instead of assigning and training weights for all edges, which turns out to be time-consuming especially for high-density parity-check matrices, we concentrate on edges which are present in most of 4-cycles and removing them gives a girth -6 Tanner graph. This approach, by slight modifications using updated LLRs instead of initial ones, simultaneously accelerates the training process and improves the error performance of our proposed decoding algorithm.

In multiple-input multiple-output (MIMO) fading channels, the design criterion for full-diversity space-time block codes (STBCs) is primarily determined by the decoding method at the receiver. Although constructions of STBCs have predominantly matched the maximum-likelihood (ML) decoder, design criteria and constructions of full- diversity STBCs have also been reported for low- complexity linear receivers. A new receiver architecture called Integer-Forcing (IF) linear receiver has been proposed to MIMO channels by Zhan et al. which showed promising results for the high-rate V-BLAST encoding scheme. In this work we address the design of full-diversity STBCs for IF linear receivers. We derive an upper bound on the probability of decoding error, and show that STBCs that satisfy the non-vanishing singular value (NVS) property provide full-diversity for the IF receiver. We also present simulation results to demonstrate that linear designs with NVS property provide full diversity for IF receiver. As a special case of our analysis on STBCs, we present an upper bound on the error probability for the V- BLAST architecture presented by Zhan et al., and demonstrate that the IF linear receivers provide full receive diversity. Our results supplement the existing outage probability based results for the IF receiver.

Low density parity check (LDPC) lattices were the first family of lattices equipped with iterative decoding algorithms. We introduce quasi-cyclic LDPC (QC LDPC) lattices as a special case of LDPC lattices with one binary QC-LDPC code as their underlying code. These lattices are obtained from the Construction A of lattices providing us to encode them efficiently using shift registers. To benefit from an encoder with linear complexity in the lattice dimension, we obtain the generator matrix of these lattices in quasi-cyclic form. We generalize the proposed quasi-cyclic form of the generator matrix for other Construction A lattices, namely the LDA lattices, with a non-binary QC-LDPC code as their underlying code. We provide a low-complexity decoding algorithm of QC LDPC-lattices based on the sum product algorithm. To design lattice codes, QC LDPC-lattices are combined with the nested lattice shaping that uses the Voronoi region of a sublattice for shaping. The shaping gain and the shaping loss of our lattice codes with dimensions 40, 50, and 60 using an optimal quantizer, are presented. The guidelines for applying efficient shaping methods, like hypercube shaping, for QC LDPC-lattices are also given. Consequently, we establish a family of lattice codes that perform practically close to the sphere bound.

We introduce cross-packing lattices for Rician fading channels, motivated by a geometric interpretation stemming from the pairwise error probability analysis. We approximate the star bodies arising from the pairwise error probability analysis with n-dimensional crosses of radius t, consisting of 2nt + 1 unit cubes, for some positive integer t. We give a construction for a family of cross-packing lattices for all dimensions and any minimum cross distance 2t + 1. We show by simulations how our new cross-packing lattices perform compared to other known lattices over the Rician fading channel, for different values of the Rician K-factor.

We consider a point-to-point flat-fading MIMO channel with channel state information known both at transmitter and receiver. At the transmitter side, a lattice coding scheme is employed at each antenna to map information symbols to independent lattice codewords drawn from the same codebook. Each lattice codeword is then multiplied by a unitary precoding matrix P and sent through the channel. At the receiver side, an integer-forcing (IF) linear receiver is employed. We denote this scheme as unitary precoded integer-forcing (UPIF). We show that UPIF can achieve full-diversity under a constraint based on the shortest vector of a lattice generated by the precoding matrix P. This constraint and a simpler version of that provide design criteria for two types of full-diversity UPIF. Type I uses a unitary precoder that adapts at each channel realization. Type II uses a unitary precoder, which remains fixed for all channel realizations. We then verify our results by computer simulations in 2×2, and 4×4 MIMO using different QAM constellations. We finally show that the proposed Type II UPIF outperform the MIMO precoding X-codes at high data rates.

In this work, we propose phase precoding for the compute-and-forward (CoF) protocol. We derive the phase precoded computation rate and show that it is greater than the original computation rate of CoF protocol without precoder. To maximize the phase precoded computation rate, we need to `jointly' find the optimum phase precoding matrix and the corresponding network equation coefficients. This is a mixed integer programming problem where the optimum precoders should be obtained at the transmitters and the network equation coefficients have to be computed at the relays. To solve this problem, we introduce phase precoded CoF with partial feedback. It is a quantized precoding system where the relay jointly computes both a quasi-optimal precoder from a finite codebook and the corresponding network equations. The index of the obtained phase precoder within the codebook will then be fedback to the transmitters. A “deep hole phase precoder” is presented as an example of such a scheme. We further simulate our scheme with a lattice code carved out of the Gosset lattice and show that significant coding gains can be obtained in terms of equation error performance.

A flat fading point-to-point multiple-antenna channel is considered where the channel state information is known at both transmitter and receiver. At the transmitter side, we use a lattice encoder to map information symbols to lattice codewords. The lattice coded layers are then precoded using unitary matrices satisfying non-vanishing minimum product distance. At the receiver side, an integer-forcing linear receiver is employed. This scheme is called `unitary precoded integer-forcing'. We show that by applying the proposed precoding technique full-diversity can be achieved. We then verify this result by conducting computer simulations in a 2 × 2 and 4 × 4 multiple-input multiple-output (MIMO) channel using full-diversity algebraic rotation precoder matrices.

The concepts of ambiguity and deficiency for a bijection on a finite Abelian group were recently introduced. In this paper, we present some further fundamental results on the ambiguity and deficiency of functions; in particular, we note that they are invariant under the well-known Carlet-Charpin-Zinoviev-equivalence, we obtain upper and lower bounds on the ambiguity and deficiency of differentially k-uniform functions, and we give a lower bound on the nonlinearity of functions that achieve the lower bound of ambiguity and deficiency. In addition, we provide an explicit formula in terms of the ranks of matrices on the ambiguity and deficiency of a Dembowski-Ostrom (DO) polynomial, and using this technique, we find exact values for known cases of DO permutations with few terms. We also derive exact values for the ambiguities and deficiencies of DO permutations obtained from trace functions. The key relationship between the above polynomials is that they all have linearized difference map.

A new architecture called integer-forcing (IF) linear receiver has been recently proposed for multiple-input multiple-output (MIMO) fading channels, wherein an appropriate integer linear combination of the received symbols has to be computed as a part of the decoding process. In this paper, we propose a method based on Hermite-Korkine-Zolotareff (HKZ) and Minkowski lattice basis reduction algorithms to obtain the integer coefficients for the IF receiver. We show that the proposed method provides a lower bound on the ergodic rate, and achieves the full receive diversity. Suitability of complex Lenstra-Lenstra-Lovasz (LLL) lattice reduction algorithm (CLLL) to solve the problem is also investigated. Furthermore, we establish the connection between the proposed IF linear receivers and lattice reduction-aided MIMO detectors (with equivalent complexity), and point out the advantages of the former class of receivers over the latter. For the 2 × 2 and 4× 4 MIMO channels, we compare the coded-block error rate and bit error rate of the proposed approach with that of other linear receivers. Simulation results show that the proposed approach outperforms the zero-forcing (ZF) receiver, minimum mean square error (MMSE) receiver, and the lattice reduction-aided MIMO detectors.

The concepts of ambiguity and deficiency for a given bijection on a finite Abelian group were recently introduced [13]. In this work we investigate the ambiguity and deficiency of some well-known polynomials which satisfy Dn(x+y, xy) = xn+ynfor every x, y ϵ Fqand n ϵ N, as well as linearized polynomials and Dembowski-Ostrom polynomials (DO polynomials). For some specific values of n (related to q) these polynomials generate permutations on Fq. We derive explicitly the ambiguity and deficiency of some of them. Numerical results on the ambiguity and deficiency of the others are also provided. Some of these polynomials are almost perfect nonlinear (APN) functions.

We introduce the concepts of weighted ambiguity and deficiency for a mapping between two finite Abelian groups of the same size. Then, we study the optimum lower bounds of these measures for permutations of an Abelian group. A construction of permutations, by modifying some permutation functions over finite fields, is given. Their ambiguity and deficiency is investigated; most of these functions are APN permutations. We show that, when they are not optimal, the Möbius function in the multiplicative group of \BBFqis closer to being optimal in ambiguity than the inverse function in the additive group of \BBFq. We note that the inverse function over \BBF28is used in AES. Finally, we conclude that a twisted permutation polynomial of a finite field is again closer to being optimal in ambiguity than the APN function employed in the SAFER cryptosystem.