Ambient Intelligence (AmI) in Internet of Things (IoT) has empowered healthcare professionals to monitor, diagnose, and treat patients remotely. Besides, the AmI-IoT has improved patient engagement and gratification as doctors’ interactions have become more comfortable and efficient. However, the benefits of the AmI-IoT-based healthcare applications are not availed entirely due to the adversarial threats. IoT networks are prone to cyber attacks due to vulnerable wireless mediums and the absentia of lightweight and robust security protocols. This paper introduces computationally-inexpensive privacy-assuring authentication protocol for AmI-IoT healthcare applications. The use of blockchain & fog computing in the protocol guarantees unforgeability, non-repudiation, transparency, low latency, and efficient bandwidth utilization. The protocol uses physically unclonable functions (PUF), biometrics, and Ethereum powered smart contracts to prevent replay, impersonation, and cloning attacks. Results prove the resource efficiency of the protocol as the smart contract incurs very minimal gas and transaction fees. The Scyther results validate the robustness of the proposed protocol against cyber-attacks. The protocol applies lightweight cryptography primitives (Hash, PUF) instead of conventional public-key cryptography and scalar multiplications. Consequently, the proposed protocol is better than centralized infrastructure-based authentication approaches.

The aviation community is employing various air traffic control and mobile communication technologies, such as ubiquitous data links, wireless communication architectures and protocols. Recently, software-defined networking (SDN) based architectures (i.e., cockpit network communications environment testing (COMET)) have been proposed for Air-Ground communication. However, an evil can break the communication between a pilot and air traffic control, resulting in a hazardous (or life-threatening) situation up in the air or failure of ground equipment. This paper proposes an efficient evil detection and prevention mechanism (called DoEF) for the COMET architecture. The proposed DoEF utilizes a deep learning-based approach, i.e., long-short term memory (LSTM), to detect the evil flies and provide possible countermeasures. Our preliminary results show that the proposed scheme reduces the detection time and increases the detection accuracy of distributed denial of service (DDoS) attacks for the aviation network.

Due to the outbreak of COVID-19, the Internet of Medical Things (IoMT) has enabled the doctors to remotely diagnose the patients, control the medical equipment, and monitor the quarantined patients through their digital devices. Security is a major concern in IoMT because the Internet of Things (IoT) nodes exchange sensitive information between virtual medical facilities over the vulnerable wireless medium. Hence, the virtual facilities must be protected from adversarial threats through secure sessions. This article proposes a lightweight and physically secure mutual authentication and secret key establishment protocol that uses physical unclonable functions (PUFs) to enable the network devices to verify the doctor's legitimacy (user) and sensor node before establishing a session key. PUF also protects the sensor nodes deployed in an unattended and hostile environment from tampering, cloning, and side-channel attacks. The proposed protocol exhibits all the necessary security properties required to protect the IoMT networks, like authentication, confidentiality, integrity, and anonymity. The formal AVISPA and informal security analysis demonstrate its robustness against attacks like impersonation, replay, a man in the middle, etc. The proposed protocol also consumes fewer resources to operate and is safe from physical attacks, making it more suitable for IoT-enabled medical network applications.

The smart home is an environment, where heterogeneous electronic devices and appliances are networked together to provide smart services in a ubiquitous manner to the individuals. As the homes become smarter, more complex, and technology dependent, the need for an adequate security mechanism with minimum individual's intervention is growing. The recent serious security attacks have shown how the Internet-enabled smart homes can be turned into very dangerous spots for various ill intentions, and thus lead the privacy concerns for the individuals. For instance, an eavesdropper is able to derive the identity of a particular device/appliance via public channels that can be used to infer in the life pattern of an individual within the home area network. This paper proposes an anonymous secure framework (ASF) in connected smart home environments, using solely lightweight operations. The proposed framework in this paper provides efficient authentication and key agreement, and enables devices (identity and data) anonymity and unlinkability. One-time session key progression regularly renews the session key for the smart devices and dilutes the risk of using a compromised session key in the ASF. It is demonstrated that computation complexity of the proposed framework is low as compared with the existing schemes, while security has been significantly improved.

A smart grid is envisioned as a promising platform for the next-generation power supply network, where the electricity is generated based on the demand from the consumers energy-use information. However, the security and privacy issues over insecure wireless communications are still big obstacles in the success of smart grid networks. In this paper, we present an efficient authentication model in smart grid networks. The proposed model justifies its feasibility with an early test-bed using off-the-shelf 802.15.4 low- cost sensors. Moreover, this poster reports preliminary performance evaluation results, and shows that the proposed scheme is effective and efficient than the prior works.

In this paper, we propose two secure virtual private network architectures for the long-term evolution backhaul network.They are layer 3 Internet protocol (IP) security virtual private network architectures based on Internet key exchange version 2 mobility and multihoming protocol and host identity protocol.Both architectures satisfy a complete set of 3GPP backhaul security requirements such as authentication, authorization, payload encryption, privacy protection, and IP-based attack prevention.The security analysis and simulation results verify that the proposed architectures are capable enough to protect long-term evolution backhaul traffic against various IP-based attacks.

The Internet of Things (IoT) technologies interconnect wide ranges of network devices irrespective of their resource capabilities and local networks. The device constraints and the dynamic link creations make it challenging to use pre-shared keys for every secure end-to-end (E2E) communication scenario in IoT. Variants of Host Identity Protocol (HIP) are adopted for constructing dynamic and secure E2E connections among the heterogenous network devices with imbalanced resource profiles and less or no previous knowledge about each other. We propose a collaborative HIP solution with an efficient key establishment component for the high constrained devices in IoT, which delegates the expensive cryptographic operations to the resource rich devices in the local networks. Finally, we demonstrate the applicability of the key establishment in collaborative HIP solution for the constrained IoT devices rather than the existing HIP variants, by providing performance and security analysis.

In the centralized Wireless Sensor Network (WSN) architecture there exists a central entity, which acquires, processes and provides information from sensor nodes. Conversely, in the WSN applications in distributed Internet of Things (IoT) architecture, sensor nodes sense data, process, exchange information and perform collaboratively with other sensor nodes and endusers. In order to maintain the trustworthy connectivity and the accessibility of distributed IoT, it is important to establish secure links for end-to-end communication with proper authentication. The authors propose an implicit certificate-based authentication mechanism for WSNs in distributed IoT applications. The developed two-phase authentication protocol allows the sensor nodes and the end-users to authenticate each other and initiate secure connections. The proposed protocol supports the resource scarcity of the sensor nodes, heterogeneity and scalability of the network. The performance and security analysis justify that the proposed scheme is viable to deploy in resource constrained WSNs.

Cloud computing is combination of various computing entities, globally separated, but electronically connected. As the geography of computation is moving towards corporate server rooms, it bring more issues including security, such as virtualization security, distributed computing, application security, identity management, access control and authentication. However, strong user authentication is the paramount requirement for cloud computing that restrict illegal access of cloud server. In this regard, this paper proposes a strong user authentication framework for cloud computing, where user legitimacy is strongly verified before enter into the cloud. The proposed framework provides identity management, mutual authentication, session key establishment between the users and the cloud server. A user can change his/her password, whenever demanded. Furthermore, security analysis realizes the feasibility of the proposed framework for cloud computing and achieves efficiency.

This paper presents a user authentication scheme for healthcare application using wireless medical sensor networks (WMSNs), where wireless medical sensors are used for patients monitoring. These medical sensors' sense the patient body data and transmit it to the professionals (e.g., doctors, nurses, and surgeons). Since, the data of an individual are highly vulnerable, it must ensures that patients medical vital signs are secure, and are not exposed to an unauthorized person. In this regards, we propose a user authentication scheme for healthcare application using medical sensor networks. The proposed scheme includes: a novel two-factor professionals authentication (user authentication), where the healthcare professionals are authenticated before access the patient's body data; a secure session key is establish between the patient sensor node and the professional at the end of user authentication. Furthermore, the analysis shows that the proposed scheme is safeguard to various practical attacks and achieves efficiency at low computation cost.