The integration of the IoT and cloud technology is very important to have a better solution for an uninterrupted, secured, seamless, and ubiquitous framework. The complementary nature of the IoT and the could in terms of storage, processing, accessibility, security, service sharing, and components makes the convergence suitable for many applications. The advancement of mobile technologies adds a degree of flexibility to this solution. The health industry is one of the venues that can benefit from IoT-Cloud technology, because of the scarcity of specialized doctors and the physical movement restrictions of patients, among other factors. In this article, as a case study, we discuss the feasibility of and propose a solution for voice pathology monitoring of people using IoT-cloud. More specifically, a voice pathology detection system is proposed inside the monitoring framework using a local binary pattern on a Mel-spectrum representation of the voice signal, and an extreme learning machine classifier to detect the pathology. The proposed monitoring framework can achieve high accuracy of detection, and it is easy to use.

Nowadays, telemedicine is an emerging healthcare service where the healthcare professionals can diagnose, evaluate, and treat a patient using telecommunication technology. To diagnose and evaluate a patient, the healthcare professionals need to access the electronic medical record (EMR) of the patient, which might contain huge multimedia big data including X-rays, ultrasounds, CT scans, and MRI reports. For efficient access and supporting mobility for both the healthcare professionals as well as the patients, the EMR needs to be kept in big data storage in the healthcare cloud. In spite of the popularity of the healthcare cloud, it faces different security issues; for instance, data theft attacks are considered to be one of the most serious security breaches of healthcare data in the cloud. In this paper, the main focus has been given to secure healthcare private data in the cloud using a fog computing facility. To this end, a tri-party one-round authenticated key agreement protocol has been proposed based on the bilinear pairing cryptography that can generate a session key among the participants and communicate among them securely. Finally, the private healthcare data are accessed and stored securely by implementing a decoy technique.

The problem of malicious activities in online social networks, such as Sybil attacks and malevolent use of fake identities, can severely affect the social activities in which users engage while online. For example, this problem can affect content publishing, creation of friendships, messaging, profile browsing, and commenting. Moreover, fake identities are often created to disseminate spam, use the private information of other users, commit fraud, and so on. A malicious person can generate numerous fake accounts for these purposes to reach a large number of trustworthy users. Thus, these types of malicious accounts must be detected and deactivated as quickly as possible. However, this objective is challenging, because a fake account can exhibit trustworthy behaviors and have a type of name that will prevent it from being detected by the security system. In this paper, we provide a comprehensive survey of literature from 2006 to 2016 on Sybil attacks in online social networks and use of social networks as a tool to analyze and prevent these attack types. We first review existing Sybil attack definitions, including those in the context of online social networks. We then discuss a new taxonomy of Sybil attack defense schemes and methodologies. Finally, we compare the literature and identify areas for further research in Sybil attacks in online social networks.

In this paper, we propose a new notion of public key encryption scheme with authorized equality test (PKE-AET), which allows authorized users those who have warrants to test the equivalence between two messages, where the messages are encrypted using different public keys. Comparing with the existing researches, our PKE-AET provides two kinds of warrants that are referred to as receiver's warrants and cipher-warrants. The proposed PKE-AET is able to deal with the following complicated scenario: Assume that a receiver authorizes a receiver's warrant to a tester, which makes the tester be able to perform equality test on all of receivers’ ciphertext; on the other hand, if receiver authorizes a cipher-warrant corresponding to a specific ciphertext to the tester, then the tester only acquires the equality test on that particular ciphertext. The equality between two ciphertexts can be verified by the tester without decryption after he or she receives two warrants and varies their validations. Moreover, for security analysis, we define two types of adversaries and security notions for PKE-AET in the multi-user setting. Furthermore, we prove that our PKE-AET is one-way CCA secure against type-I adversaries and IND-CCA secure against type-II adversaries. Finally, the proposed scheme leads better efficiency than most of previous equality test schemes.

The IoT is the next generation of innovation in the smart world, which has the potential to improve safety, security, and the quality of our daily lives through pervasive communication and computation. Currently, we have observed that a plethora of interconnected smartphones, devices, and sensors are deployed for providing personalized services (e.g., social media, smart home, health monitoring) at any time from anywhere. The personalized services offered by IoT, although enhancing the quality of our lives, have serious challenges of securing networks and data in transit, as every day a myriad of devices and services are connected to the IoT. However, existing security solutions, such as two-factor authentication based on passwords along with second-level protection may not be efficient and reliable for providing end-to-end secure communication solutions among different devices and services connected to the IoT. To this end, this article proposes an end-to-end secure IoT-based solution using biometrics and pairing-based cryptography. Because of the uniqueness of one’s biometric traits (e.g., face, fingerprint, palm, iris, voice, heartbeat), a biometric-based security solution is less vulnerable to security breaches for IoT systems or infrastructure. We present a biometric- based IoT infrastructure comprising four layers, and for each layer, we discuss possible security challenges along with the corresponding countermeasures. Finally, we provide a case study of face-based biometric recognition, where sensors or smartphones capture a face image and securely transmit it to the IoT platform to provide end-to end security.

Smart home systems can provide health care services for people with special needs in their own homes. Briefly defined, such a smart home has special electronics to enable the remote control of automated devices specifically designed for remote health care to ensure the safety of the patient at home and the supervision of their health status. These sensors are linked to a local intelligence unit responsible for analyzing sensor data, detecting emergency situations, and interfacing between the patient at home and a set of people involved in their health care, such as doctors, nurses, emergency services, and paramedics. Smart homes can improve the patient’s quality of life and safety through the innovative use of advanced technologies. Telemedicine and telecare are driving forces behind the adoption of smart homes. The telecare medicine information system (TMIS) has drawn worldwide attention for the past 20 years, as modern technologies have made remote delivery of healthcare a reality. TMIS using multidisciplinary research and application involves advanced technologies in information processing, telecommunications, bio-sensing, and artificial intelligence including smart technologies. TMIS leverages the latest mobile and wireless communication technologies and widely available internet infrastructure to deliver quality services to home patients enabling them to remotely access information about their health and obtain telemedical services. TMIS delivers capabilities to remotely provide $24\times 7$ health care facilities to patients. Its purpose is to provide patients with convenient and expedited remote health care services, greatly improving the quality and efficiency of health care services. However, the open and insecure nature of the internet poses a number of security threats to patient secrecy and privacy. Security design for TMIS is not trivial. Essential security and privacy are provided by mutual authentication and key agreement protocols. This paper proposes an efficient and secure, bilinear pairing-based, unlink-able, mutual authentication and key agreement protocol for TMIS. The proposed protocol adopts a fuzzy extractor for the identification of patients using the biometric data. The security of the proposed protocol is based on the hardness of the elliptic curve discrete logarithm problem (ECDLP) and elliptic curve computational Diffie–Hellman problem (ECCDHP) to preserve the privacy of the user. The detailed security analysis is discussed, and the results of comparison are provided.