Informal enterprises and their activities dominate the economy of the Sub-Saharan Africa (SSA). However, despise the increasing volume of eco-innovation research in recent years, the drivers of the eco-innovation of small medium enterprises (SMEs) in the informal sector remain largely unknown. Drawing from a triple theoretical anchoring method (entrepreneurship theory, shareholder theory, and resource theory), this study tests the validity of a set of eco-innovation drivers developed around the concept among firms of the informal sector in Ghana. The conceptual framework was tested using structural equation modeling and the data were obtained using the World Bank’s Ghana Informal Enterprise Survey (GIFS) as an area-based frame to survey 285 local entrepreneurs (n = 285). The results confirmed that informal enterprises do eco-innovate (mainly incremental innovation), and that innovation activities are driven by a government’s incentive regulations, market demand, and local entrepreneurs’ characteristic of hometown identity. This research highlights the contributions of the informal sector to sustainable development and draws the attention of policymakers, non-government agencies, and researchers on the drivers leading eco-innovation activities in the informal sector. The results could be used for future policy formulation.

The current advances in cloud-based services have significantly enhanced individual satisfaction in numerous modern life areas. Particularly, the recent spectacular innovations in the wireless body area networks (WBAN) domain have made e-Care services rise as a promising application field, which definitely improves the quality of the medical system. However, the forwarded data from the limited connectivity range of WBAN via a smart device (e.g., smartphone) to the application provider (AP) should be secured from an unapproved access and alteration (attacker) that could prompt catastrophic consequences. Therefore, several schemes have been proposed to guarantee data integrity and privacy during their transmission between the client/controller (C) and the AP. Thereby, numerous effective cryptosystem solutions based on a bilinear pairing approach are available in the literature to address the mentioned security issues. Unfortunately, the related solution presents security shortcomings, where AP can with ease impersonate a given C. Hence, this existing scheme cannot fully guarantee C’s data privacy and integrity. Therefore, we propose our contribution to address this data security issue (impersonation) through a secured and efficient remote batch authentication scheme that genuinely ascertains the identity of C and AP. Practically, the proposed cryptosystem is based on an efficient combination of elliptical curve cryptography (ECC) and bilinear pairing schemes. Furthermore, our proposed solution reduces the communication and computational costs by providing an efficient data aggregation and batch authentication for limited device’s resources in WBAN. These additional features (data aggregation and batch authentication) are the core improvements of our scheme that have great merit for limited energy environments like WBAN.

Cloud computing seems to be the new paradigm platform where data owner can not only remotely store their data, but also require service provision attributed with ubiquity, reliability, high-performance, efficiency, and scalability. But applying these cloud advantages on huge sensed data which contains sensitive information implies critical data security issues. Because, this new vision service: `Cloud of Things' arises some challenges in terms of user access control and outsourced data integrity and privacy protection as the data owner has no more the physical control of his data. Therefore several “Sensor-cloud” designs have been proposed to securely store and process sensed data. In this paper, we propose a new security architecture that tackles this challenge by reinforcing data owner access-controlled on outsourced service from public cloud environment. Specifically our solution is based on the design of an optimized implementation of CP-ABE algorithm for enhancing privacy. In addition our approach allows secure and efficient data owner access-controlled by using Attribute-Based encryption (ABE) in the perspective of a paring-based Cryptosystem (PBC) and lightweight token based authentication algorithm (using ECDSA) for the effectiveness of our solution in terms of computation and storage cost.

Data privacy protection is a paramount issue in cloud applications for the last decade. In addition, data encryption, which is the primary method to impart security in clouds, is proved insufficient to guarantee data privacy protection from some security issues like homogeneity and background knowledge attacks. Therefore, it is important to provide a security mechanism that provide not only anonymous data but also anonymous continuous queries. So, this paper proposes a new scheme (Moye) that tackles this challenge by protecting queries to be linked to specific sensitive data. Specifically, the proposed solution is based on the design of a hybrid implementation of public key encryption with keyword search (PEKS) and subset membership encryption (SME) cryptosystem to enhance both data and query privacy protection. In addition, this approach provides an efficient and anonymous data processing by using an optimized k-anonymity scheme. Doing so, the authors protect searchable keywords and queries from inside and outside guessing attacks for the effectiveness of the proposed solution.