Different from the traditional wide-swath synthetic aperture radar (SAR) system, ultra-wide swath SAR can achieve ultra-wide swath observation without the expense of an unimpaired azimuth resolution. However, due to the limitation of one receiving window, the radar echoes of near-range and far-range scatters arrive at the SAR receiver simultaneously, and this leads to the range ambiguity occurrence. This paper proposes a novel method based on chaotic frequency modulation (CFM) signals is proposed to suppress range ambiguity in ultra-wide swath synthetic aperture radar (SAR). Time-variant transmission avoids mutual interferences from the radar echoes of near-range and far-range scatters due to the uncorrelated property. Simulations and experiments on raw data are performed to verify the effectiveness of the proposed method.

Keyword search over encrypted data is essential for accessing outsourced sensitive data in cloud computing. In some circumstances, the keywords that the user searches on are only semantically related to the data rather than via an exact or fuzzy match. Hence, semantic-based keyword search over encrypted cloud data becomes of paramount importance. However, existing schemes usually depend upon a global dictionary, which not only affects the accuracy of search results but also causes inefficiency in data updating. Additionally, although compound keyword search is common in practice, the existing approaches only process them as single words, which split the original semantics and achieve low accuracy. To address these limitations, we initially propose a compound concept semantic similarity (CCSS) calculation method to measure the semantic similarity between compound concepts. Next, by integrating CCSS with Locality-Sensitive Hashing function and the secure kk-Nearest Neighbor scheme, a semantic-based compound keyword search (SCKS) scheme is proposed. SCKS achieves not only semantic-based search but also multi-keyword search and ranked keyword search. Additionally, SCKS also eliminates the predefined global library and can efficiently support data update. The experimental results on real-world dataset indicate that SCKS introduces low overhead on computation and the search accuracy outperforms the existing schemes.

The authorization mechanism of smart devices is mainly implemented by firmware, yet many smart devices have security issues about their firmware. Limited research has focused on securing the firmware of smart devices, although increasingly more smart devices are used to deal with the very sensitive applications, activities, and data of users. Thus, research on smart device firmware security is of growing importance. Disassembly is a common method for evaluating the security of authorization mechanisms. When disassembling firmware, the processor type of the running environment and the image base of the firmware should first be determined. In general, the processor type can be obtained by tearing down the device or consulting the product manual. However, it is not easy to determine the image base of firmware. Since the processors of many smart devices are ARM architectures, in this paper, we focus on firmware under the ARM architecture and propose an automated method for determining the image base. By studying the storage law of the jump table in the firmware of ARM-based smart devices, we propose an algorithm, named determining the image base by searching jump tables (DBJT), to determine the image base. The experimental results indicate that the proposed method can successfully determine the image base of firmware, which stores the absolute address in the jump table.

With the development of the Internet and personal digital devices, self-organizing and open-pattern collaborations are becoming popular. In such environments, data are usually outsourced to third-party servers in the cloud, which are out of the control domain of data owners. Hence, traditional access control models, which are enforced relying on data storage servers, will face new security challenges. In this paper, we propose a self- contained read and write access control (RWAC) scheme based on ciphertext-policy attribute-based encryption (CP-ABE) and attribute-based group signature (ABGS) mechanism. By adopting a two-step encryption strategy using CP-ABE and utilizing the write control policy as the signature policy in ABGS, RWAC ensures that fine-grained read and write access control can be enforced during decryption and signature generation without dependence on any third parties. To prevent privacy leakage from RWAC policies, we adopt a CP-ABE scheme with hidden policy. Then, we introduce the policy hiding method into ABGS and propose an ABGS scheme with hidden policy. Moreover, users can trace the edit history of each data object with the signature or a write list. The security analysis indicates that RWAC is able to enforce fine-grained read and write access controls for group collaborations while also ensuring data confidentiality and integrity.

Media streaming has largely dominated the Internet traffic and the trend will keep increasing in the next years. To efficiently distribute the media content, Information-Centric Networking (ICN) has attracted many researchers. Since end users usually obtain content from indeterminate caches in ICN, the publisher cannot reinforce data security and access control depending on the caches. Hence, the ability of self-contained protection is important for the cached contents. Attribute-based encryption (ABE) is considered the preferred solution to achieve this goal. However, the existing ABE schemes usually have problems regarding efficiency. The exponentiation in key generation and pairing operation in decryption respectively increases linearly with the number of attributes involved, which make it costly. In this paper, we propose an efficient key-policy ABE with fast key generation and decryption (FKP-ABE). In the key generation, we get rid of exponentiation and only require multiplications/divisions for each attribute in the access policy. And in the decryption, we reduce the pairing operations to a constant number, no matter how many attributes are used. The efficiency analysis indicates that our scheme has better performance than the existing KP-ABE schemes. Finally, we present an implementation framework that incorporates the proposed FKP-ABE with the ICN architecture.

The computation of semantic similarity between words is important in information retrieval, knowledge acquisition and many other fields. The existing studies are mainly aiming at single concepts composed of single terms. For the compound concepts composed of multiple terms, they usually neglect the special constitution features of compounds and only process them as single concepts, which may affect the ultimate accuracy. In this paper, we propose a novel ontology-based Compound Concept Semantic Similarity calculation approach called CCSS which exploits concept constitution features. In CCSS, the compound is decomposed into Subject headings and Auxiliary words (SaA), and the relationships between these two sets are used to measure the similarity. Besides, the errors that may be caused by SaA recognition are corrected. Moreover, several information sources of ontology such as taxonomical features, local density and depth are considered. Extensive experimental evaluations demonstrate that our approach significantly outperforms existing approaches.