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Voting is one of the most prominent components of democracy. The one-vote veto, which requires the voting result to be only “yes” or “no”, is a particularly noteworthy type of voting with widespread application. When obtaining a “no” result, no useful information about the number of “no” votes and who votes “no” is disclosed. In this paper, we introduce a protocol for anonymous one-vote veto utilizing qubits and local Pauli operations $\mathbb {Z}$ and $\mathbb {X}$ , building simple processes for easy implementation under the current technology. For better elaboration, we give two examples: all voters cast “yes” votes and only one voter casts a “no.” Then, the corresponding experiment tests are conducted on the simulated IBM quantum computer to verify their feasibility. We also show that the proposed protocol has the desirable properties of privacy, fairness, verifiability and robustness. Furthermore, we analyze the proposed protocol’s security against cheating from eavesdroppers, a semi-honest server and malicious voters. This work is the first attempt to illustrate how qubits can be useful for building a secure anonymous one-vote veto strategy.

To solve the problem that existing machine reading comprehension models can't understand the semantics of articles and questions well, this paper proposes a multi-level semantic fusion neural network based on natural language understanding and deep learning. The model combines calculations of attentions at different levels with cross-layer fusions of historical data. Experiments on the SQuAD dataset prove that our proposed model is superior to traditional models in terms of the exact match rate and F1 value. Our model can better transmit and interpret data and enhance the performance of question answering systems.

Nowadays, mobile apps are surging around the world. Instead of hitting shelves of official app stores, many apps are posted on webpages or spread by social media, because choosing the later way could save time and energy to release mobile apps. However, it is difficult to know the app type and developer information of this kind of mobile apps without installation. Sometimes, we need to know which mobile apps are similar, which apps are developed by the same person or group. Therefore, clustering mobile apps in an unsupervised way is quite important. In this paper, we propose a mobile app clustering scheme based on code design and app manufacturing genre. Results show that the clustering scheme could efficiently find similar apps and the similarity computed by functional design characteristics will achieve better clustering performance.

TV networks are no longer just closed networks. They are increasingly carrying Internet services, integrating and interoperating with home IoT and the Internet. In addition, client devices are becoming intelligent. At the same time, they are facing more security risks. Security incidents such as attacks on TV systems are commonplace, and there are many incidents that cause negative effects. The security protection of TV networks mainly adopts security protection schemes similar to other networks, such as constructing a security perimeter; there are few security researches specifically carried out for client-side devices. This paper focuses on the mainstream architecture of the integration of HFC TV network and the Internet, and conducts a comprehensive security test and analysis for client-side devices including EOC cable bridge gateways and smart TV Set-Top-BoX. Results show that the TV network client devices have severe vulnerabilities such as command injection and system debugging interfaces. Attackers can obtain the system control of TV clients without authorization. In response to the results, we put forward systematic suggestions on the client security protection of smart TV networks in current days.

With the rapid development of network and multimedia technologies, a large number of image databases have been produced, and image data has been experiencing an exponential growth. Meanwhile, the requirement for searching images, i.e. image retrieval in large databases is a hot issue. Many traditional methods search for images accurately according to the feature vector of the image, but this method is computationally expensive. The most famous improved solution is the Locality Sensitive Hashing (LSH, Locality Sensitive Hashing) method which sacrifices some search accuracy to improve efficiency. However, most of the current LSH methods are difficult to handle large-scale data. Therefore, in this paper we design and implement a distributed image retrieval approach based on LSH. The hash value of an image is used to filter out a batch of completely irrelevant pictures, and then the distributed computing resources are utilized to find similar pictures. Experimental results show that the accuracy rate and recall rate could reach about 90%, at the same time the retrieval speed is acceptable, about 120 ms for each retrieval on average.

DNS is a quite critical network service while it is a critical attack vector. DNS vulnerabilities and attacks have been studied for many years. However, what parameters are efficient to identify specific type of DNS attacks? This question becomes more important in order to ensure DNS security in this big data era. This paper firstly characterizes main types of DNS attacks, and then gives some analytic methods to detect malicious traffic in big network data. Based on a recent dataset in a competition, analysis is carried out to verify our methods. We try to obtain some hints along with DNS malicious traffic, which might be helpful to carry out quick and efficient attack detection in huge data.

Because of the high-value data of an enterprise, sophisticated cyber-attacks targeted at enterprise networks have become prominent. Attack graphs are useful tools that facilitate a scalable security analysis of enterprise networks. However, the administrators face difficulties in effectively modelling security problems and making right decisions when constructing attack graphs as their risk assessment experience is often limited. In this paper, we propose an innovative method of security assessment through an ontology- and graph-based approach. An ontology is designed to represent security knowledge such as assets, vulnerabilities, attacks, countermeasures, and relationships between them in a common vocabulary. An efficient algorithm is proposed to generate an attack graph based on the inference ability of the security ontology. The proposed algorithm is evaluated with different sizes and topologies of test networks; the results show that our proposed algorithm facilitates a scalable security analysis of enterprise networks.

Public reports show that crimes linked to social networks have increased sharply in past years. The social networking activity records extracted from a suspect's mobile device plays an important role in the investigation. However, previous works mainly conducted forensics by extracting electronic evidence that is cached in mobile devices and may be deleted for various reasons. In this paper, we proposed a novel investigating approach on Twitter and WeChat based on a customised Android emulator, which can collect evidence from both local device and remote online services. Our approach was evaluated using data copies of Twitter and WeChat from different Android smartphones, which validated the practicability of the proposed method. This paper is intended to provide vital references for the investigators and researchers working on the digital forensics.

Because of the distributed nature of cloud computing, the data of cloud may be stored and processed across jurisdictional borders. In such case, collecting digital evidence from cloud computing requires multiparty cooperation. However, as far as we known, there is still no available technic approach for improving the trustworthy of the interaction records of all stakeholders in cloud forensics. This work proposed a process provenance, which provides proof of existence and privacy preservation for process records by using technologies of blockchain and cryptography group signature. The process provenance enhances the trustworthy of the chain of custody for cloud forensics.

The permission model is an essential Android mechanism for resisting security threats: android malware can do very little if the user denies its requests for permissions. However, the recent literatures show that certain vulnerable applications with insufficiently enforced privileges may lead to critical permissions leakage via inter-application interaction. Malicious applications can trick these vulnerable applications to perform actions that are beyond their given privileges. This study proposes an efficient approach for the analysis of permission leakage vulnerabilities in Android inter-process communications; this approach identifies suspicious vulnerable paths based on an analysis of control-flow and dataflow. We handle the unsafe control flows over inter-component communication and asynchronous calls through Android callbacks, which is the major difference from previous related studies. The proposed system was evaluated using 550 real-world Android applications and the experiment result demonstrated the practicality of our method.

Public reports show that crimes linked to Smartphones have increased sharply in past years. Because of the largest market share of Android, forensics on Android device had become a focus in the field of digital forensics. Data acquisition is a key aspect for smartphones forensics. In this paper, we proposed an improved approach of acquiring data image using special modes of Qualcomm processors, which almost taken more than half of market share of mobile smartphones' CPU. Evaluation experiments confirmed that proposed methods are practicability and the data integrity of extracted partition images is preserved. This work is intended to provide vital references for the investigators and researchers working on the digital forensics.

Cloud computing delegates the management of physical data to the third parties who cannot be trusted fully. This may result in security risks in integrity of outsourcing data, the cloud users are hard to convince that their data which is processed in cloud computational tasks is kept intact. Although identity-based signature has been proven useful within cloud security infrastructures by offering more light weight and flexible key management approaches than traditional PKI does. However, the inherent key escrow problem of identity-based signature is hard to be accepted by cloud users. In this paper, we proposed an identity-based signature with escrow free and ID-protection for Cloud Computing, which can solve the key escrow problem better. The idea behind our solution is to utilize a trusted third party to bind the partial secret and the identity of the user together, which prevents the malicious PKG from impersonating the honest user's identity. Detailed security proofs and comparisons (in terms of computational cost, communication overhead and security properties) show that our proposal is secure and efficient.

Logs are one of the most important pieces in forensics, which can be leveraged to extract critical evidences or help drastically speed up the investigation. Nevertheless, collecting the logs from cloud infrastructure is extremely difficult, since the investigators almost totally lack of control over the cloud. In this work, we introduce the notion of secure logging monitor service, which is deployed in the cloud and generates integrity proofs of cloud logs in real time. Once a proof entry has been produced, a dishonest cloud service provider (CSP) even colludes with the investigator, can't fake or remove the corresponding logs without being detected. Compared with related works, the proposed scheme can simultaneously meet the most major requirements of cloud forensics, including the integrity of log evidences, privacy protection and low computational burden.

Nowadays, short message service (SMS) is faced with various security threats. Thus, the fields of high confidentiality(e.g., mobile E-commerce) require a higher level of security protection on SMS. Secure communication in incredible mobile network has very important significance. This paper presents a high security communication protocol for SMS. Through authentication, decryption and integrity protection, it establishes an end-to-end secure channel between server-side and mobile terminal. Through analyzed it by svo logic, this protocol is proved to ensure confidentiality, integrity and non-repudiation of SMS messages.