In this paper, we propose a new secure data integrity verification scheme for mobile edge computing (MEC), named IntactEdge, which provides an efficient method for end users in MEC to verify that the edge servers correctly maintain their stored data. Particularly, IntactEdge is designed using lightweight cryptographic mechanisms, such as message authentication codes and hash functions, to ensure efficiency in generating and verifying data integrity proofs. Batch verification is also supported to further enhance computational efficiency for end users during integrity checks. In addition, IntactEdge offers the desirable feature of multi-replica secure storage, allowing user data to be distributed across multiple edge servers to enhance data availability. To prevent edge nodes from exploiting data replicas stored on other nodes to falsely satisfy integrity verification requests, IntactEdge generates distinct data replicas for different edge nodes, while still enabling each replica to support proof generation using the same authentication tag. Finally, we demonstrate that IntactEdge is secure against potential data integrity attacks on edge servers and highly efficient in both tag generation and integrity verification.

In this paper, we propose an efficient and distributed service access control framework (E-DAC) in the pervasive edge computing (PEC) environment, where the resources of peer devices at the network edge are integrated to provide latencysensitive computing services to the nearby devices on behalf of edge servers. E-DAC addresses the challenge of efficient and distributed service access control, comprising edge service authorization, service access authorization, and mutual authentication between edge servers and edge devices. In dong so, E-DAC first extends a key-aggregate cryptosystem to enable batch service authorization, in which a service provider can aggregate the authorization keys of different services to produce a constant-size aggregate key for an edge server. Second, E-DAC enables users to acquire authorization from the service provider for service access on edge servers by using efficient secret sharing. Third, edge servers and users can authenticate with each other without interacting with a centralized server, while enabling secure zero-round trip communication, so that the service data is protected and the communication bandwidth cost is low. In addition, the service provider is capable of efficiently revoking the authorization of the dropout or compromised edge servers or users in response to the dynamics of the PEC environment. Finally, we prove the security of service access control in E-DAC, including unforgeability of service authorization and confidentiality of service data, and conduct extensive analysis and experiments to demonstrate that E-DAC is highly computational and communication-efficient on service authorization, authentication, and revocation.

Pervasive edge computing (PEC) integrates the re-sources of peer devices at the network edge to serve users' latency-sensitive computation needs. Due to the high dynamics of the PEC environment, it is very challenging to achieve efficient service access control of edge servers and users without an “always-online” centralized server. In this paper, we propose a secure, efficient, and distributed service access control frame-work (SE-DAC) in the PEC environment. Specifically, SE-DAC extends the key-aggregate cryptosystem to achieve batch service authorization, where the service provider aggregates the access keys of different services to produce a constant-size aggregate key for the edge servers. Meanwhile, user authentication tasks are delegated to the edge servers by integrating secret sharing. The mutual authentication between the edge servers and the users is based on zero-round trip communication, such that the communication bandwidth cost is low. In addition, the service provider can efficiently revoke the authorization of the dropout or compromised edge servers in response to the dynamics of the PEC environment. Finally, we conduct numerical analysis and experiments to demonstrate that SE-DAC is highly computational efficient on service authorization, authentication, and revocation.

Over last two decades, Speaker Recognition has primarily been focused on source, system, and prosodic features of the speech. The breath, however, has either been treated as a trivial part of the speech, or considered a noise entity. Our observation reveals that breath is a unique fingerprint of human respiratory system which offers overwhelming results for Speaker Recognition. Moreover, its passive nature, short-duration, fewer occurrences and simple processing results to a light-weight, text-independent and transparent system, which we articulate as BreathID. The breath features are extracted and classified by Mel Frequency Cepstral Coefficients, MFCC, based template matching technique. The verification is performed by a similarity based scheme, whose efficiency competes with classification algorithms. We process a data set collected from 50 users. Our system offers a 0.04 percent False Identification Rate, FIR, for Speaker Identification, and 0.12 percent False Acceptance Rate, FAR, and 0.15 percent False Rejection Rate, FRR, for Speaker Verification. We further evaluate our scheme under various practical modalities, like text in-dependence, replay scenario, users' motion status (sitting and walking), recording equipment (03 smartphones and 02 microphones), recording period (08 months), and bilingual contents (English and Chinese). Though we use Matlab to formulate a fine-grained approach, we foresee breath biometric as a viable security measure for practical realizations.