Abstract Metaheuristic is one of the techniques to improve the security of image encryption. However, existing metaheuristic image cryptosystems based on metaheuristic may have convergence difficulties during the optimization process, which cause insecurity and slow convergence. Besides, the time cost of the parallel execution model applied to metaheuristic image cryptosystems is not low enough. Therefore, a parallel many‐objective optimized key generation framework is proposed. Firstly, if four or more security indicators of cryptosystem, which are the results of security test, need to be optimized, the many‐objective optimization algorithm is employed to the proposed framework. With method adjusts the chaotic system parameters as the optimization key, which effectively avoid the convergence difficulty of the encryption key. Secondly, a master‐slave parallel model is improved to metaheuristic encryption. The model allocates the most time‐consuming fitness calculation work to slave nodes, which makes the modified model more reasonable and thus reduces the encryption time. To evaluate the performance of the proposed framework, a specific encryption scheme is constructed, that utilizes a 2D quadric map and many‐objective optimization algorithm based on dominance and decomposition (MOEA/DD) to optimize five security indicators. Experimental results reveal that this scheme has good security performances and less parallel encryption time.

Rumor spreaders are increasingly utilizing multimedia content to attract the attention and trust of news consumers. Though quite a few rumor detection models have exploited the multi-modal data, they seldom consider the inconsistent semantics between images and texts, and rarely spot the inconsistency among the post contents and background knowledge. In addition, they commonly assume the completeness of multiple modalities and thus are incapable of handling handle missing modalities in real-life scenarios. Motivated by the intuition that rumors in social media are more likely to have inconsistent semantics, a novelKnowledge-guided Dual-consistency Networkis proposed to detect rumors with multimedia contents. It uses two consistency detection subnetworks to capture the inconsistency at the cross-modal level and the content-knowledge level simultaneously. It also enables robust multi-modal representation learning under different missing visual modality conditions, using a special token to discriminate between posts with visual modality and posts without visual modality. Extensive experiments on three public real-world multimedia datasets demonstrate that our framework can outperform the state-of-the-art baselines under both complete and incomplete modality conditions.

Recently, pre-trained language models such as BERT have shown state-of-the-art accuracies in text matching.When being applied to IR (or QA), the BERT-based matching models need to online calculate the representations and interactions for all query-candidate pairs.The high inference cost has prohibited the deployments of BERT-based matching models in many practical applications.To address this issue, we propose a novel BERT-based text matching model, in which the representations and the interactions are decoupled.Then, the representations of the candidates can be calculated and stored offline, and directly retrieved during the online matching phase.To conduct the interactions and generate final matching scores, a lightweight attention network is designed.Experiments based on several large scale text matching datasets show that the proposed model, called FASTMATCH, can achieve up to 100X speed-up to BERT and RoBERTa at the online matching phase, while keeping more up to 98.7% of the performance.

Text-to-SQL systems offers natural language interfaces to databases, which can automatically generates SQL queries given natural language questions.On the WikiSQL benchmark, state-ofthe-art text-to-SQL systems typically take a slot-filling approach by building several specialized models for each type of slot.Despite being effective, such modularized systems are complex and also fall short in jointly learning for different slots.To solve these problems, this paper proposes a novel approach that formulates the task as a question answering problem, where different slots are predicted by a unified machine reading comprehension (MRC) model.For this purpose, we use a BERT-based MRC model, which can also benefit from intermediate training on other MRC datasets.The proposed method can achieve competitive results on WikiSQL, suggesting it being a promising direction for text-to-SQL.

On the WikiSQL benchmark, state-of-the-art text-to-SQL systems typically take a slotfilling approach by building several dedicated models for each type of slots.Such modularized systems are not only complex but also of limited capacity for capturing interdependencies among SQL clauses.To solve these problems, this paper proposes a novel extraction-linking approach, where a unified extractor recognizes all types of slot mentions appearing in the question sentence before a linker maps the recognized columns to the table schema to generate executable SQL queries.Trained with automatically generated annotations, the proposed method achieves the first place on the WikiSQL benchmark.

Jianqiang Ma, Erhard Hinrichs. Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers). 2015.

Digital documents are prone to be compromised, especially the archival records which are intended to be stored for a very long period (say 30+ years). Many modern security mechanisms, such as cryptography, are poorly suited to protect these archival records because it is often difficult to maintain decryption keys and update cryptographic systems over decades. An adversary that wants to tamper these archival records may only need to wait until the encryption algorithm used is compromised. In addition, the preservation of encrypted documents is not generally accepted in the international archival community. Thus, in this paper, we propose a framework for the assessment of the trustworthiness of digital records. The framework looks into evidence around digital records. On the assessment of the trustworthiness of a record, it structures the preserved evidence into an evidence tree and assigns evidential values to every pieces of evidence using experts' knowledge or a reputation system. Finally, using the Dempster-Shafer (D-S) theory, the framework combines these evidential values from different evidence in the face of uncertainty, and arrive at the trustworthiness of digital records.

The issue of trust in the management of digital records has been a topic of research for a number of years. During this time most researchers have concentrated on the nature and meaning of the record itself, rather than the potential use of the record as evidence of the originators' origins, functions, and activities. Through a comparison of trust in the real world and trust in the digital world, we demonstrate the importance of evidential value in the assessment of the trustworthiness of a record. In this paper we investigate, identify and specify the requirements for evidential value, based on our life cycle model of the record. Finally, we show briefly how these requirements can be used in the assessment of the trustworthiness of records in long-term storage.

Component-Based Software Engineering (CBSE) with Open Source Software and Commercial-Off-the-Shelf (COTS) components, Open Source Software (OSS) based development, and Software Outsourcing (SO) are becoming increasingly important for the Chinese software industry. It is therefore necessary to establish pragmatic and possibly nation-specific guidelines for Chinese software companies regarding the use of CBSE, OSS, and SO. Such guidelines should be based on insights from actual practice, which are in our case, obtained through surveys. A European state-of-the-practice survey on COTS- and OSS-oriented CBSE was conducted in Germany, Italy, and Norway in 2004-2005. We repeated similar surveys in China, with an extended survey on OSS and SO. We encountered many difficulties in conducting the surveys, but in most cases managed to find working solutions. We report on the lessons learned while conducting these surveys. In particular, we address issues relating to sampling, contacting respondents, data collection, and data validation. The main lessons are: 1) it was necessary to cooperate with a third-party organization with close relations to Chinese software companies; 2) it was necessary to assign researchers to this third-party organization to facilitate data collection and to control the quality of the data collected; and 3) an email survey, after an initial telephone call to establish contact, was the best method for getting questionnaires completed by Chinese respondents.

The business relationship between a software outsourcer and its suppliers is gradually moving from contract relationship to partnership. The partnership type between the outsourcer and the supplier is considered as a key predictor of outsourcing success. Although several studies have investigated the practices and benefits of building partnership from an outsourcer's perspective, few of them have studied these issues from the supplier's viewpoint, especially in the context of offshore software outsourcing. Since more and more Chinese software companies are getting outsourcing subcontracts from abroad, it is important to investigate the effect of business relationship on their performance, and to identify possible enhancements. Our study has collected data by a questionnaire-based survey from 53 finished projects in 41 Chinese software suppliers. Twenty-six of our investigated suppliers claim to have contract relationship with their outsourcers and the remaining 27 think they have partnership with outsourcers. Results from our study show, however, that 1) processes and methods used by suppliers to solve conflicts with outsourcers do not follow their self-claimed contract relationships or partnership; 2) there is no significant correlations between the type of relationship and the success of outsourced projects; 3) more personnel with proper language and communication skills need to be educated in order to facilitate Chinese companies to build and maintain a proper partnership with their outsourcers.