Abstract Malware analysis and detection over the Android have been the focus of considerable research, during recent years, as customer adoption of Android attracted a corresponding number of malware writers. Antivirus companies commonly rely on signatures and are error‐prone. Traditional machine learning techniques are based on static, dynamic, and hybrid analysis; however, for large scale Android malware analysis, these approaches are not feasible. Deep neural architectures are able to analyze large scale static details of the applications, but static analysis techniques can ignore many malicious behaviors of applications. The study contributes to the documentation of various approaches for detection of malware, traditional and state‐of‐the‐art models, developed for analysis that facilitates the provision of basic insights for researchers working in malware analysis, and the study also provides a dynamic approach that employs deep neural network models for detection of malware. Moreover, the study uses Android permissions as a parameter to measure the dynamic behavior of around 16,900 benign and intruded applications. A dataset is created which encompasses a large set of permissions‐based dynamic behavior pertaining applications, with an aim to train deep learning models for prediction of behavior. The proposed architecture extracts representations from input sequence data with no human intervention. The state‐of‐the‐art Deep Convolutional Generative Adversarial Network extracted deep features and accomplished a general validation accuracy of 97.08% with an F1‐score of 0.973 in correctly classifying input. Furthermore, the concept of blockchain is utilized to preserve the integrity of the dataset and the results of the analysis.

Service-oriented architecture offers a flexible paradigm for information flow among collaborating organizations. As information moves out of an organization boundary, various security concerns may arise, such as confidentiality, integrity, and authenticity that needs to be addressed. Moreover, verifying the correctness of the communication protocol is also an important factor. This paper focuses on the formal verification of the xDAuth protocol, which is one of the prominent protocols for identity management in cross domain scenarios. We have modeled the information flow of xDAuth protocol using high-level Petri nets to understand the protocol information flow in a distributed environment. We analyze the rules of information flow using Z language, while Z3 SMT solver is used for the verification of the model. Our formal analysis and verification results reveal the fact that the protocol fulfills its intended purpose and provides the security for the defined protocol specific properties, e.g., secure secret key authentication, and Chinese wall security policy and secrecy specific properties, e.g., confidentiality, integrity, and authenticity.

ABSTRACT This paper has been written as a part of the research project that is working towards the implementation of dynamic behavioral attestation for mobile platforms. The motivation behind this paper was to analyze the existing remote attestation techniques in order to figure out their strengths and weaknesses. We have analyzed Integrity Measurement Architecture, Policy‐reduced Integrity Measurement Architecture, Property‐based Attestation, Remote Attestation on Program Execution, Semantic Remote Attestation, Trustable Remote Verification of Web Services, and Model‐based Behavior Attestation. Each of the existing remote attestation techniques was found to be effective in some situations but was found to be infeasible in others. Therefore, a new remote attestation technique is needed, which is platform independent and flexible enough to meet the challenges of today's scalable computing environments. Copyright © 2011 John Wiley & Sons, Ltd.

Service oriented architecture (SOA) is an architectural paradigm that enables dynamic composition of heterogeneous, independent, multi-vendor business services. A prerequisite for such inter-organizational workflows is the establishment of trustworthiness, which is mostly achieved through non-technical measures such as legislation, and/or social consent that businesses, or organizations simply pledge themselves to adhere. In our viewpoint, a business process can only be trustworthy if the behavior of all services in it is trustworthy. Trusted Computing Group (TCG) has defined an open set of specifications for the establishment of trustworthiness through a hardware root-of-trust. This paper has three objectives: firstly, the behavior of individual services in a business process is formally specified. Secondly, in order to overcome the inherent weaknesses of trust management through software alone, a hardware root of-trust devised by the TCG, is used for the measurement of the behavior of individual services in a business process. Finally, a verification mechanism is detailed through which the trustworthiness of a business process can be verified.

Remote attestation is an important characteristic of trusted computing technology which provides reliable evidence that a trusted environment actually exists. Existing approaches for the realization of remote attestation measure the trustworthiness of a target platform from its binaries, configurations, properties or security policies. All these approaches are low-level attestation techniques only, and none of them define what a trusted behavior actually is and how to specify it. In this paper, we present a novel approach where the trustworthiness of a platform is associated with the behavior of a policy model. In our approach, the behavior of a policy model is attested rather than a software or hardware platform. Thus, the attestation feature is not tied to a specific software or hardware platform, or to a particular remote attestation technique, or to an individual type of security policy. We select usage control (UCON) as our target policy model as it is a comprehensive and exible model. We propose a framework to identify, specify, and attest different behaviors of UCON.