Fundamental thresholds of realistic quantum error correction circuits from classical spin models

Mapping the decoding of quantum error correcting (QEC) codes to classical disordered statistical mechanics models allows one to determine critical error thresholds of QEC codes under phenomenological noise models. Here, we extend this mapping to admit realistic, multi-parameter noise models of faulty QEC circuits, derive the associated strongly correlated classical spin models, and illustrate this approach for a quantum repetition code with faulty stabilizer readout circuits. We use Monte-Carlo simulations to study the resulting phase diagram and benchmark our results against a minimum-weight perfect matching decoder. The presented method provides an avenue to assess fundamental thresholds of QEC circuits, independent of specific decoding strategies, and can thereby help guiding the development of near-term QEC hardware.

Machine Learning of Physical Unclonable Functions using Helper Data

Physical Unclonable Functions (PUFs) are used in various key-generation schemes and protocols. Such schemes are deemed to be secure even for PUFs with challenge-response behavior, as long as no responses and no reliability information about the PUF are exposed. This work, however, reveals a pitfall in these constructions: When using state-of-the-art helper data algorithms to correct noisy PUF responses, an attacker can exploit the publicly accessible helper data and challenges. We show that with this public information and the knowledge of the underlying error correcting code, an attacker can break the security of the system: The redundancy in the error correcting code reveals machine learnable features and labels. Learning these features and labels results in a predictive model for the dependencies between different challenge-response pairs (CRPs) without direct access to the actual PUF response. We provide results based on simulated data of a k-SUM PUF model and an Arbiter PUF model. We also demonstrate the attack for a k-SUM PUF model generated from real data and discuss the impact on more recent PUF constructions such as the Multiplexer PUF and the Interpose PUF. The analysis reveals that especially the frequently used repetition code is vulnerable: For a SUM-PUF in combination with a repetition code, e.g., already the observation of 800 challenges and helper data bits suffices to reduce the entropy of the key down to one bit. The analysis also shows that even other linear block codes like the BCH, the Reed-Muller, or the Single Parity Check code are affected by the problem. The code-dependent insights we gain from the analysis allow us to suggest mitigation strategies for the identified attack. While the shown vulnerability advances Machine Learning (ML) towards realistic attacks on key-storage systems with PUFs, our analysis also facilitates a better understanding and evaluation of existing approaches and protocols with PUFs. Therefore, it brings the community one step closer to a more complete leakage assessment of PUFs.

TYPES OF COMMUNICATION STRATEGIES USED BY YOUNG LEARNERS IN EFL CLASSROOMS

The learner’s proficiency level in communication using English as a foreign language was indicated by their capability to make use of strategies to communicate both in written as well as spoken forms. This qualitative study focused on finding out (i) the types of communication strategies used by the students in EFL classrooms at SMP Negeri 4 Singaraja, and (ii) the students’ reasons towards the use of their communication strategies. The data were obtained from observation and focus group discussion. All data were analysed descriptively. The results of the study indicated that numerous types of strategies were used by the students when communicating in the classroom. They are the use of fillers, self-repetition, code switching, appeal for help, self-repair, asking for confirmation, massage abandonment, omission, approximation, and literal translation. Various types of reasons were expressed by the students toward the use of communication strategies such as thinking time, anxiety, and proficiency level.

A Novel Compressed Encrypted and Encoded Watermark Embedding Scheme for Digital Images

In this research work a novel idea of compressed, encrypted and encoded watermark embedding scheme for digital images is proposed. Initially watermark is compressed using Huffman encoder. Compressed watermark is encrypted using combined binary key sequence {Ki} derived from sequence of logistic map and Lozi map. The compressed and encrypted binary watermark is encoded using (n,1) repetition code. This compressed, encrypted and encoded binary watermark is embedded in alternate locations of cover image pixels using of Least Significant Bit (LSB) and Second Least Significant Bit (SLSB). To study the watermarked image quality, parameters such as Signal to Noise Ratio (SNR) and Mean Square Error (MSE) are used. Also performance of the proposed system is compared with uncompressed, encrypted, encoded watermark embedding scheme. There is a significant improvement in MSE, SNR of watermarked image, when compressed watermark embedding scheme is compared to uncompressed watermark embedding scheme.

Memes as reasonably hostile laments: A discourse analysis of political dissent in Oman

In this article, I investigate how political dissent is linguistically constructed and mitigated in memes that are circulated nationally on WhatsApp in Oman. I do so by drawing upon insights from relational approaches to face, the theorization of communicative strategies as polysemous and ambiguous, and research pertaining to the Islamic practice of lamenting. The data consist of a representative set of memes collected in the summer and fall of 2015 as part of an ethnographic project on social media and Arab identity. I theorize memes as cultural tools that take the form of ‘reasonably hostile’ lament-narratives, which enable citizens in Oman to engage in democracy while saving face. To create lament-memes that voice dissent while mitigating face-attacks, Omanis draw upon various communicative strategies: They use repetition, code choice, hashtags, and different genres; they juxtapose emojis with text; and they manipulate the production and participation frameworks of texts. Collectively, these strategies, which function via intertextuality, allow the concerns to be aired, but indirectly and playfully. The article demonstrates how political dissent is negotiated and mitigated through memes, the agency of social media users, and the validity of conceptualizing memes as cultural tools.