Lattice Based Authenticated Key Exchange with Universally Composable Security

Security is a significant problem for communications in many scenarios in Internet of Things (IoT), such as military applications, electronic payment, wireless reprogramming of smart devices and so on. To protect communications, a secret key shared by the communicating parties is often required. Authenticated key exchange (AKE) is one of the most widely used methods to provide two or more parties communicating over an open network with a shared secret key. It has been studied for many years. A large number of protocols are available by now. The majority of existing AKE protocols require the two communicating parties execute equivalent computational tasks. However, many communications take place between two devices with significantly different computational capabilities, such as a cloud center and a mobile terminal, a gateway and a sensor node, and so on. Most available AKE protocols do not perfectly match these scenarios. To further address the security problem in communications between parties with fairly unbalanced computational capabilities, this thesis studies AKE protocols with unbalanced computational requirements on the communicating parties. We firstly propose a method to unbalance computations in the Elliptic Curve Diffie-Hellman (ECDH) key exchange scheme. The resulting scheme is named as UECDH scheme. The method transfers one scalar multiplication from the computationally limited party to its more powerful communicating partner. It significantly reduces the computational burden on the limited party since scalar multiplication is the most time-consuming operation in the ECDH scheme. When applying the UECDH scheme to design AKE protocols, the biggest challenge is how to achieve authentication. Without authentication, two attacks (the man-in-the-middle attack and the impersonation attack) can be launched to the protocols. To achieve authentication, we introduce different measures that are suitable for a variety of use cases. Based on the authentication measures, we propose four suites of UECDH-based AKE protocols. The security of the protocols is discussed in detail. We also implement prototypes of these protocols and similar protocols in international standards including IEEE 802.15.6, Transport Layer Security (TLS) 1.3 and Bluetooth 5.0. Experiments are carried out to evaluate the performance. The results show that in the same experimental platform, the proposed protocols are more friendly to the party with limited computational capability, and have better performance than similar protocols in these international standards.

3P-SAKE: Privacy-preserving and physically secured authenticated key establishment protocol for wireless industrial networks

Designed as a specialized ad hoc network suitable for applications such as emergency responses, OppNets are considered as a sub-class of DTN where communication opportunities are intermittent, so an end-to-end path between the source and the destination may never exist. Existing networks have already brought connectivity to a broad range of devices, such as hand held devices, laptops, tablets, PC, etc. The Internet of Things (IoT) will extend the connectivity to devices beyond just mobile phones and laptops, but to buildings, wearable devices, cars, different things and objects. There are different issues for these networks. One of them is the selection of IoT nodes in order to carry out a task in opportunistic networks. In this work, we implement a Fuzzy-Based System for IoT node selection in opportunistic networks. For our proposed system, we use four input parameters: IoT Node’s Unique Encounters (NUE), IoT Node’s Free Buffer Space (NFBS), IoT Node’s Batter Level (NBL) and IoT Node Contact Duration (NCD). The output parameter is IoT Node Selection Decision (NSD). The results show that the proposed system makes a proper selection decision of IoT nodes in opportunistic networks. The IoT node selection is increased up to 25% and 11% by increasing NCD and NUE, respectively.

Maintaining adequate energy in low-powered Internet of Things (IoT) nodes is crucial for the development of several applications like smart homes, autonomous industries, etc. These IoT nodes exploit adaptive duty cycling techniques for the efficient utilization of energy resources. However, such adaptive duty cycling of IoT nodes results in their asynchronous operations thereby inducing energy holes in the network. These energy holes lead to information loss and poor quality of services of IoT networks. In this regard, energy harvesting using Mobile Energy Transmitters (MET) can improve the lifetime of an IoT network. In this work, we are introducing a metric named Age of Charging (AoC) metric to quantify the repetitive charging of power deficit IoT nodes. Energy-efficient scheduling of MET is proposed to minimize the expected average AoC such that the energy harvested by IoT nodes is maximized. In this regard, the optimization problem is first remodeled into a Markov decision process. Subsequently, a deep reinforcement learning algorithm is developed based upon the twin delayed deep deterministic policy gradient scheme for energy-efficient scheduling of MET in asynchronous IoT networks. The simulation results indicate that the proposed algorithm outperforms the conventional Deep Q-networks and soft-actor-critic algorithms. These results motivate the usage of MET-aided energy harvesting in self-sustaining IoT networks.

Current technology driven world is moving forward with massive implementation of smart objects. These smart objects or Internet of Things (IoT) nodes are involved in sensing of real time critical data from surroundings. Though these IoT nodes are involved in very specific task but their existence is very important for the complete system. Usually, in an IoT architecture, several heterogeneous nodes connect with a nearest gateway. The gateway itself connects with the world via Internet. IoT nodes need to flexible about connectivity as those may need to leave and join any gateway based on context (time, location etc.). To achieve flexibility, IoT components need a trust relationship between each other. In this paper, we have proposed a mechanism for integrating distributed trust management in IoT by using edge computing technology, considering the scalability and heterogeneous capability of IoT devices.

In three-party password authenticated key exchange (AKE) protocol, since two users use their passwords to establish a secure session key over an insecure communication channel with the help of the trusted server, such a protocol may suffer the password guessing attacks and the server has to maintain the password table. To eliminate the shortages of password-based AKE protocol, very recently, according to chaotic maps, Lee et al. [2015 Nonlinear Dyn. 79 2485] proposed a first three-party-authenticated key exchange scheme without using passwords, and claimed its security by providing a well-organized BAN logic test. Unfortunately, their protocol cannot resist impersonation attack, which is demonstrated in the present paper. To overcome their security weakness, by using chaotic maps, we propose a biometrics-based anonymous three-party AKE protocol with the same advantages. Further, we use the pi calculus-based formal verification tool ProVerif to show that our AKE protocol achieves authentication, security and anonymity, and an acceptable efficiency.

SUMMARYThis paper investigates authenticated key exchange (AKE) protocol under computational Diffie–Hellman assumption in the extended Canetti–Krawczyk model. The core technical component of our protocol is the trapdoor test technique, which is originally introduced to remove the gap Diffie–Hellman (GDH) assumption for the public key encryption schemes. Our contributions are twofold.First, we clarify some misunderstandings of the usage of the trapdoor test technique in AKE protocols showing its adaptation to the AKE protocols is not trivial. We point out some errors in some recent work which attempts to make use of the trapdoor test technique to remove GDH assumption.Second, based on trapdoor test technique, we propose an efficient extended Canetti–Krawczyk secure AKE protocol under computational Diffie–Hellman assumption instead of GDH assumption. Additionally, our protocol does not make use of NAXOS trick and has a tight reduction. In comparison with all existing AKE protocols with the properties as previously mentioned, our protocol with only three exponentiations is most efficient. Copyright © 2013 John Wiley & Sons, Ltd.

Blockchain (BC) in the Internet of Things (IoT) is a novel technology that acts with decentralized, distributed, public and real-time ledger to store transactions among IoT nodes. A blockchain is a series of blocks, each block is linked to its previous blocks. Every block has the cryptographic hash code, previous block hash, and its data. The transactions in BC are the basic units that are used to transfer data between IoT nodes. The IoT nodes are different kind of physical but smart devices with embedded sensors, actuators, programs and able to communicate with other IoT nodes. The role of BC in IoT is to provide a procedure to process secured records of data through IoT nodes. BC is a secured technology that can be used publicly and openly. IoT requires this kind of technology to allow secure communication among IoT nodes in heterogeneous environment. The transactions in BC could be traced and explored through anyone who are authenticated to communicate within the IoT. The BC in IoT may help to improve the communication security. In this paper, I explored this approach, its opportunities and challenges.

An unresolved problem in research on authenticated key exchange (AKE) is to construct a secure protocol against advanced attacks such as key compromise impersonation and maximal exposure attacks without relying on random oracles. HMQV, a state of the art AKE protocol, achieves both efficiency and the strong security model proposed by Krawczyk (we call it the CK + model), which includes resistance to advanced attacks. However, the security proof is given under the random oracle model. We propose a generic construction of AKE from a key encapsulation mechanism (KEM). The construction is based on a chosen-ciphertext secure KEM, and the resultant AKE protocol is CK + secure in the standard model. The protocol gives the first CK + secure AKE protocols based on the hardness of integer factorization problem, code-based problems, or learning problems with errors. In addition, instantiations under the Diffie-Hellman assumption or its variant can be proved to have strong security without non-standard assumptions such as πPRF and KEA1.

The Internet of Things (IoT) is one of the fastest-growing technologies in recent years. However, many IoT service providers design their IoT solutions with non-interoperable hard-ware, scenario-specific features, and unique architectures that make these deployments fragmented rather than collaborative. Collaborative IoT (C-IoT) systems are considered the natural evolution of the traditional IoT. Sharing the infrastructure is one of the main concepts that C-IoT depends on to create a collaborative environment between different applications. With the current fragmented IoT, these applications cannot share their infrastructure and data due to the lack of standards to organize the C-IoT space. In this paper, we introduced Unified Interoperable Driver for IoT (UIDI) nodes. UIDI uses a novel programming methodology that enables node interpreters to provide general-purpose firmware for IoT nodes. UIDI allows the users to configure IoT nodes according to their usage, preferences, and needs through the cloud. We developed a proof-of-concept prototype to demonstrate the feasibility and usability of the proposed UIDI using NodeMCU and Arduino-Uno. The performance of UIDI outperforms Firmata by 27%. In addition to that, the UIDI platform is a standalone node that connects directly to the cloud, whereas the Firmata node requires a host to be accessible from the cloud.

Recently, Roy et al. proposed a physically unclonable function (PUF)-based authentication and key exchange protocol for Internet of Things (IoT) devices. The PUF protocol is efficient, because it integrates both the Node-to-Node (N2N) authentication and the Node-to-Server (N2S) authentication into a standalone protocol. In this paper, we therefore examine the security of the PUF protocol under the assumption of an insider attack. Our cryptanalysis findings are the following. (1) A legitimate but malicious IoT node can monitor the secure communication among the server and any other IoT nodes in both N2N authentication and N2S authentication. (2) A legitimate but malicious IoT node is able to impersonate a target IoT node to cheat the server and any other IoT nodes in N2N authentication and the server in N2S authentication, respectively. (3) A legitimate but malicious IoT node can masquerade as the server to cheat any other target IoT nodes in both N2N authentication and N2S authentication. To the best of our knowledge, our work gives the first non-trivial concrete security analysis for the PUF protocol. In addition, we employ the automatic verification tool of security protocols, i.e., Scyther, to confirm the weaknesses found in the PUF protocol. We finally consider how to prevent weaknesses in the PUF protocol.

Both mutual authentication and generation of session keys can be accomplished by an authenticated key exchange (AKE) protocol. Let us consider the following situation: (1) a client, who communicates with many different servers, remembers only one password and has insecure devices (e.g., mobile phones or PDAs) with very-restricted computing power and built-in memory capacity; (2) the counterpart servers have enormous computing power, but they are not perfectly secure against various attacks (e.g., virus or hackers); (3) neither PKI (Public Key Infrastructures) nor TRM (Tamper-Resistant Modules) is available. The main goal of this paper is to provide security against the leakage of stored secrets as well as to attain high efficiency on client's side. For those, we propose an efficient and leakage-resilient RSA-based AKE (RSA-AKE) protocol suitable for the above situation whose authenticity is based on password and another secret. In the extended model where an adversary is given access to the stored secret of client, we prove that its security of the RSA-AKE protocol is reduced tightly to the RSA one-wayness in the random oracle model. We also show that the RSA-AKE protocol guarantees several security properties (e.g., security of password, multiple sever scenario with only one password, perfect forward secrecy and anonymity). To our best knowledge, the RSA-AKE protocol is the most efficient, in terms of both computation costs of client and communication costs, over the previous AKE protocols of their kind (using password and RSA).

Recent work by Krawczyk [12] and Menezes [16] has highlighted the importance of understanding well the guarantees and limitations of formal security models when using them to prove the security of protocols. In this paper we focus on security models for authenticated key exchange (AKE) protocols. We observe that there are several classes of attacks on AKE protocols that lie outside the scope of the Canetti-Krawczyk model. Some of these additional attacks have already been considered by Krawczyk [12]. In an attempt to bring these attacks within the scope of the security model we extend the Canetti-Krawczyk model for AKE security by providing significantly greater powers to the adversary. Our contribution is a more compact, integrated, and comprehensive formulation of the security model. We then introduce a new AKE protocol called NAXOS and prove that it is secure against these stronger adversaries.

In recent years, the Internet of Things (IoT) devices have become an inseparable part of our lives. With the growing demand for Smart Applications, it becomes clear that IoT will bring regular automation and intelligent sensing to a new level thus improving quality of life. The core component of the IoT ecosystem is data which exists in various forms and formats. The collected data is then later used to create context awareness and make meaningful decisions. Besides an undoubtedly large number of advantages from the usage of IoT, there exist numerous challenges attributed to the security of objects that cannot be neglected for uninterrupted services. The Mirai botnet attack demonstrated that the IoT system is susceptible to different forms of cyberattacks. While advanced data analytics and Machine Learning have proved efficiency in various applications of cybersecurity, those still have not been explored enough in the literature from the applicability perspective in the domain of resource-constrained IoT. Several architectures and frameworks have been proposed for defining the ways for analyzing the data, yet mostly investigating off-chip analysis. In this contribution, we show how an Artificial Neural Network model can be trained and deployed on trivial IoT nodes for detecting intelligent similarity-based network attacks. This article proposes a concept of the resource-constrained intelligent system as a part of the IoT infrastructure to be able to harden the cybersecurity on microcontrollers. This work will serve as a stepping stone for the application of Artificial Intelligence on devices with limited computing capabilities such as end-point IoT nodes.

In this article, a review of commercial devices on the edge of the Internet of Things (IoT), or IoT nodes, is presented in terms of hardware requirements. IoT nodes are the interface between the IoT and the physical world (e.g., sensor nodes). To this aim, we introduce a wide survey of existing devices made publicly available for the further analysis of trends and state of the art. This data-driven approach permits developing quantitative insight into the big picture of the current status of IoT nodes. The analysis shows that an order (ultimately two orders) of magnitude gap needs to be filled in terms of size, lifetime, and cost (energy efficiency) to ultimately make IoT nodes truly ubiquitous and trigger the widely expected exponential growth of the IoT ecosystem. Overall, this article presents a view from the edge of the IoT and a glimpse of its tipping point.