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1. P-HIP: A Lightweight and Privacy-Aware Host Identity Protocol for Internet of Things

   https://doi.org/10.1109/JIOT.2020.3009024  

   Hossain, Mahmud ; Hasan, Ragib ( July 2020 , IEEE Internet of Things Journal)

   null (Ed.)

   The Host Identity Protocol (HIP) has emerged as the most suitable solution to uniquely identify smart devices in the mobile and distributed Internet of Things (IoT) systems, such as smart cities, homes, cars, and healthcare. The HIP provides authentication methods that enable secure communications between HIP peers. However, the authentication methods provided by the HIP cannot be adopted by the IoT devices with limited processing power because of the computation-intensive cryptographic operations involved in hash generation, signature validation, and session key establishment. Moreover, IoT devices cannot utilize the HIP as is to communicate securely in the low power and lossy networks as there is a considerable communication overhead, such as packet fragmentation and reassembly, for exchanging certificates over a lossy link. Additionally, the use of static host identifiers makes IoT devices vulnerable to cyber espionage and user-targeted attacks. In this article, we propose an authentication scheme, P-HIP, that protects the identity privacy of an IoT device by enabling the device to compute and use unique host identifiers from networks to networks and sessions to sessions. To make the HIP suitable for resource-constrained IoT devices, P-HIP provides methods that unburden IoT devices from computation-intensive operations, such as modular exponentiation, involved in authentication and session-key exchange. Additionally, P-HIP minimizes the communication overheads for exchanging certificates in lossy networks. We implement a prototype of P-HIP on Contiki enabled IoT that shows P-HIP can reduce computation costs, communication overheads, and the session-key establishment time when used by low-powered devices in a lossy network. 

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2. Wake-up radio-based data forwarding for green wireless networks

   https://doi.org/10.1016/j.comcom.2020.05.046  

   Koutsandria, G. ; DiValerio, V. ; Spenza, D. ; Basagni, S. ; Petrioli, C. ( April 2020 , Computer communications)

   Green wireless networks Wake-up radio Energy harvesting Routing Markov decision process Reinforcement learning 1. Introduction With 14.2 billions of connected things in 2019, over 41.6 billions expected by 2025, and a total spending on endpoints and services that will reach well over $1.1 trillion by the end of 2026, the Internet of Things (IoT) is poised to have a transformative impact on the way we live and on the way we work [1–3]. The vision of this ‘‘connected continuum’’ of objects and people, however, comes with a wide variety of challenges, especially for those IoT networks whose devices rely on some forms of depletable energy support. This has prompted research on hardware and software solutions aimed at decreasing the depen- dence of devices from ‘‘pre-packaged’’ energy provision (e.g., batteries), leading to devices capable of harvesting energy from the environment, and to networks – often called green wireless networks – whose lifetime is virtually infinite. Despite the promising advances of energy harvesting technologies, IoT devices are still doomed to run out of energy due to their inherent constraints on resources such as storage, processing and communica- tion, whose energy requirements often exceed what harvesting can provide. The communication circuitry of prevailing radio technology, especially, consumes relevant amount of energy even when in idle state, i.e., even when no transmissions or receptions occur. Even duty cycling, namely, operating with the radio in low energy consumption ∗ Corresponding author. E-mail address: koutsandria@di.uniroma1.it (G. Koutsandria). https://doi.org/10.1016/j.comcom.2020.05.046 (sleep) mode for pre-set amounts of time, has been shown to only mildly alleviate the problem of making IoT devices durable [4]. An effective answer to eliminate all possible forms of energy consumption that are not directly related to communication (e.g., idle listening) is provided by ultra low power radio triggering techniques, also known as wake-up radios [5,6]. Wake-up radio-based networks allow devices to remain in sleep mode by turning off their main radio when no communication is taking place. Devices continuously listen for a trigger on their wake-up radio, namely, for a wake-up sequence, to activate their main radio and participate to communication tasks. Therefore, devices wake up and turn their main radio on only when data communication is requested by a neighboring device. Further energy savings can be obtained by restricting the number of neighboring devices that wake up when triggered. This is obtained by allowing devices to wake up only when they receive specific wake-up sequences, which correspond to particular protocol requirements, including distance from the destina- tion, current energy status, residual energy, etc. This form of selective awakenings is called semantic addressing [7]. Use of low-power wake-up radio with semantic addressing has been shown to remarkably reduce the dominating energy costs of communication and idle listening of traditional radio networking [7–12]. This paper contributes to the research on enabling green wireless networks for long lasting IoT applications. Specifically, we introduce a ABSTRACT This paper presents G-WHARP, for Green Wake-up and HARvesting-based energy-Predictive forwarding, a wake-up radio-based forwarding strategy for wireless networks equipped with energy harvesting capabilities (green wireless networks). Following a learning-based approach, G-WHARP blends energy harvesting and wake-up radio technology to maximize energy efficiency and obtain superior network performance. Nodes autonomously decide on their forwarding availability based on a Markov Decision Process (MDP) that takes into account a variety of energy-related aspects, including the currently available energy and that harvestable in the foreseeable future. Solution of the MDP is provided by a computationally light heuristic based on a simple threshold policy, thus obtaining further computational energy savings. The performance of G-WHARP is evaluated via GreenCastalia simulations, where we accurately model wake-up radios, harvestable energy, and the computational power needed to solve the MDP. Key network and system parameters are varied, including the source of harvestable energy, the network density, wake-up radio data rate and data traffic. We also compare the performance of G-WHARP to that of two state-of-the-art data forwarding strategies, namely GreenRoutes and CTP-WUR. Results show that G-WHARP limits energy expenditures while achieving low end-to-end latency and high packet delivery ratio. Particularly, it consumes up to 34% and 59% less energy than CTP-WUR and GreenRoutes, respectively. 

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3. SIA: Secure Intermittent Architecture for Off-the-Shelf Resource-Constrained Microcontrollers

   Dinu, Daniel ; Krishnan, Archanaa ; Schaumont, Patrick ( May 2019 , IEEE International Symposium on Hardware Oriented Security and Trust (HOST))

   Recent advancements in energy-harvesting techniques provide an alternative to batteries for resource constrained IoT devices and lead to a new computing paradigm, the intermittent computing model. In this model, a software module continues its execution from where it left off when an energy shortage occurred. Enforcing security of an intermittent software module is challenging because its power-off state has to be protected from a malicious adversary in addition to its power-on state, while the security mechanisms put in place must have a low overhead on the performance, resource consumption, and cost of a device. In this paper, we propose SIA (Secure Intermittent Architecture), a security architecture for resource-constrained IoT devices. SIA leverages low-cost security features available in commercial off-the-shelf microcontrollers to protect both the power-on and power-off state of an intermittent software module. Therefore, SIA enables a host of secure intermittent computing applications such as self-attestation, remote attestation, and secure communication. Moreover, our architecture provides confidentiality and integrity guarantees to an intermittent computing module at no cost compared to previous approaches in the literature that impose significant overheads. The salient characteristic of SIA is that it does not require any hardware modifications, and hence, it can be directly applied to existing IoT devices. We implemented and evaluated SIA on a resource-constrained IoT device based on an MSP430 processor. Besides being secure, SIA is simple and efficient. We confirm the feasibility of SIA for resource-constrained IoT devices with experimental results of several intermittent computing applications. Our prototype implementation outperforms by two to three orders of magnitude the secure intermittent computing solution of Suslowicz et al. presented at IGSC 2018. 

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4. SIA: Secure Intermittent Architecture for Off-the-Shelf Resource-Constrained Microcontrollers

   Dinu, Daniel ; Krishan, Archanaa ; Schaumont, Patrick ( May 2019 , IEEE International Symposium on Hardware Oriented Security and Trust (HOST))

   Recent advancements in energy-harvesting techniques provide an alternative to batteries for resource-constrained IoT devices and lead to a new computing paradigm, the intermittent computing model. In this model, a software module continues its execution from where it left off when an energy shortage occurred. Enforcing security of an intermittent software module is challenging because its power-off state has to be protected from a malicious adversary in addition to its power-on state, while the security mechanisms put in place must have a low overhead on the performance, resource consumption, and cost of a device. In this paper, we propose SIA (Secure Intermittent Architecture), a security architecture for resource-constrained IoT devices. SIA leverages low-cost security features available in commercial off-the-shelf microcontrollers to protect both the power-on and power-off state of an intermittent software module. Therefore, SIA enables a host of secure intermittent computing applications such as self-attestation, remote attestation, and secure communication. Moreover, our architecture provides confidentiality and integrity guarantees to an intermittent computing module at no cost compared to previous approaches in the literature that impose significant overheads. The salient characteristic of SIA is that it does not require any hardware modifications, and hence, it can be directly applied to existing IoT devices. We implemented and evaluated SIA on a resource-constrained IoT device based on an MSP430 processor. Besides being secure, SIA is simple and efficient. We confirm the feasibility of SIA for resource-constrained IoT devices with experimental results of several intermittent computing applications. Our prototype implementation outperforms by two to three orders of magnitude the secure intermittent computing solution of Suslowicz et al. presented at IGSC 2018. 

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5. Low-Cost Standard Public Key Cryptography Services for Wireless IoT Systems

   https://doi.org/10.1145/3139937.3139940  

   Ozmen, Muslum Ozgur ; Yavuz, Attila A. ( November 2017 , The First ACM CCS Workshop on Internet of Things Security and Privacy (IoT S&P) '17)

   Internet of Things (IoT) is an integral part of application domains such as smart-home and digital healthcare. Various standard public key cryptography techniques (e.g., key exchange, public key encryption, signature) are available to provide fundamental security services for IoTs. However, despite their pervasiveness and well-proven security, they also have been shown to be highly energy costly for embedded devices. Hence, it is a critical task to improve the energy efficiency of standard cryptographic services, while preserving their desirable properties simultaneously. In this paper, we exploit synergies among various cryptographic primitives with algorithmic optimizations to substantially reduce the energy consumption of standard cryptographic techniques on embedded devices. Our contributions are: (i) We harness special pre-computation techniques, which have not been considered for some important cryptographic standards to boost the performance of key exchange, integrated encryption, and hybrid constructions. (ii) We provide self-certification for these techniques to push their performance to the edge. (iii) We implemented our techniques and their counterparts on 8-bit AVR ATmega 2560 and evaluated their performance. We used microECC library and made the implementations on NIST-recommended secp192 curve, due to its standardization. Our experiments conirmed signiicant improvements on the battery life (up to 7×) while preserving the desirable properties of standard techniques. Moreover, to the best of our knowledge, we provide the first open-source framework including such set of optimizations on low-end devices. 

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