A Trust Model Based on Service Classification in Mobile Services

Internet of Things (IoT) and B3G/4G communication are promoting the pervasive mobile services with its advanced features. However, security problems are also baffled the development. This paper proposes a trust model to protect the user's security. The billing or trust operator works as an agent to provide a trust authentication for all the service providers. The services are classified by sensitive value calculation. With the value, the user's trustiness for corresponding service can be obtained. For decision, three trust regions are divided, which is referred to three ranks: high, medium and low. The trust region tells the customer, with his calculated trust value, which rank he has got and which authentication methods should be used for access. Authentication history and penalty are also involved with reasons.Comment: IEEE/ACM Internet of Things Symposium (IOTS), in conjunction with GreenCom 2010, IEEE, Hangzhou, China, December 18-20, 201

A general framework for privacy-preserving computation on cloud environments

While privacy and security concerns dominate public cloud services, Homomorphic Encryption (HE) is seen as an emerging solution that can potentially assure secure processing of sensitive data by third-party cloud vendors. It relies on the fact that computations can occur on encrypted data without the need for decryption, although there are major stumbling blocks to overcome before the technology is considered mature for production cloud environments. This paper examines a proposed technology platform, known as the Homomorphic Encryption Bus (HEB), that leverages HE with data obfuscation methods over a minimal network interaction model, allowing a uniform, flexible and general approach to cloud-based privacy-preserving system integration. The platform is uniquely designed to overcome barriers limiting the mainstream application of existing Fully Homomorphic Encryption (FHE) schemes in the cloud. A client-server interaction model involving ciphertext decryption on the client end is necessary to achieve resetting of 'noisy' ciphertexts in place of a much more inefficient (server only) recryption procedure. Data perturbation techniques are used to obfuscate intermediate data decrypted on the client-side of ciphertext interactions, in a way that is unintelligible to the client. In addition to efficient noise resetting, interactions involving data perturbations also achieve plaintext (binary to integer-based and vice versa) message space swapping, and conversion of accumulated integerbased encodings to a reduced embedded binary form. There appears to be little existing literature that examines these techniques as a means of broadening HE processing capabilities and practical application over the cloud. Interaction performance is examined in terms of timing and multiplicative circuit depth costs, through a simple equation evaluation and against standard recryption

A Novel Proteogenomic Integration Strategy Expands the Breadth of Neo-Epitope Sources

Tumor-specific antigens can activate T cell-based antitumor immune responses and are ideal targets for cancer immunotherapy. However, their identification is still challenging. Although mass spectrometry can directly identify human leukocyte antigen (HLA) binding peptides in tumor cells, it focuses on tumor-specific antigens derived from annotated protein-coding regions constituting only 1.5% of the genome. We developed a novel proteogenomic integration strategy to expand the breadth of tumor-specific epitopes derived from all genomic regions. Using the colorectal cancer cell line HCT116 as a model, we accurately identified 10,737 HLA-presented peptides, 1293 of which were non-canonical peptides that traditional database searches could not identify. Moreover, we found eight tumor neo-epitopes derived from somatic mutations, four of which were not previously reported. Our findings suggest that this new proteogenomic approach holds great promise for increasing the number of tumor-specific antigen candidates, potentially enlarging the tumor target pool and improving cancer immunotherapy