By expanding the connection of objects to the Internet and their entry to human life, the issue of security and privacy has become important. In order to enhance security and privacy on the Internet, many security protocols have been developed. Unfortunately, the security analyzes that have been carried out on these protocols show that they are vulnerable to one or few attacks, which eliminates the use of these protocols. Therefore, the need for a security protocol on the Internet of Things (IoT) has not yet been resolved. Recently, Khor and Sidorov cryptanalyzed the protocol and presented an improved version of it. In this paper, at first, we show that this protocol also does not have sufficient security and so it is not recommended to be used in any application. More precisely, we present a full secret disclosure attack against this protocol, which extracted the whole secrets of the protocol by two communication with the target tag. In addition, recently proposed an ultralightweight mutual authentication RFID protocol for blockchain enabled supply chains, supported by formal and informal security proofs. However, we present a full secret disclosure attack against this protocol as well.
A factor that can help expand the IoT is to create confidence for users of this technology in terms of maintaining their privacy and security, because if there is no proper security in its infrastructure, damage to IoT-based equipment, the possibility of losing personal information, the loss of privacy, and even the disclosure of economic and other data, are highly likely, and this may lead to the inability to use it in critical applications. Ronen and Shamir in @cite_6 pointed out that if security is not taken into account in the IoT-based infrastructure, the technology will threaten the future of the world as a nuclear bomb.
@cite_6
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Internet of Things (IoT) is a technology in which for any object the ability to send data via communications networks is provided. Ensuring the security of Internet services and applications is an important factor in attracting users to use this platform. In the other words, if people are unable to trust that the equipment and information will be reasonably safe against damage, abuse and the other security threats, this lack of trust leads to a reduction in the use of IoT-based applications. Recently, Tewari and Gupta (J Supercomput 1–18, 2016) have proposed an ultralightweight RFID authentication protocol to provide desired security for objects in IoT. In this paper, we consider the security of the proposed protocol and present a passive secret disclosure attack against it. The success probability of the attack is ‘1’ while the complexity of the attack is only eavesdropping one session of the protocol. The presented attack has negligible complexity. We verify the correctness of the presented attack by simulation. Abstract In large-scale Internet of Things (IoT) systems, huge volumes of data are collected from anywhere at any time, which may invade people’s privacy, especially when the systems are used in medical or daily living environments. Preserving privacy is an important issue, and higher privacy demands usually tend to require weaker identity. However, previous research has indicated that strong security tends to demand strong identity, especially in authentication processes. Thus, defining a good tradeoff between privacy and security remains a challenging problem. This motivates us to develop a privacy-preserving and accountable authentication protocol for IoT end-devices with weaker identity, which integrates an adapted construction of short group signatures and Shamir’s secret sharing scheme. We analyze the security properties of our protocol in the context of six typical attacks and verify the formal security using the Proverif tool. Experiments using our implementation in MacBook Pro and Intel Edison development platforms show that our authentication protocol is feasible in practice. With the advent of the Internet of Things (IoT), billions of devices are expected to continuously collect and process sensitive data (e.g., location, personal health). Due to limited computational capacity available on IoT devices, the current de facto model for building IoT applications is to send the gathered data to the cloud for computation. While private cloud infrastructures for handling large amounts of data streams are expensive to build, using low cost public (untrusted) cloud infrastructures for processing continuous queries including on sensitive data leads to concerns over data confidentiality. This paper presents STYX, a novel programming abstraction and managed runtime system, that ensures confidentiality of IoT applications whilst leveraging the public cloud for continuous query processing. The key idea is to intelligently utilize partially homomorphic encryption to perform as many computationally intensive operations as possible in the untrusted cloud. STYX provides a simple abstraction to the IoT developer to hide the complexities of (1) applying complex cryptographic primitives, (2) reasoning about performance of such primitives, (3) deciding which computations can be executed in an untrusted tier, and (4) optimizing cloud resource usage. An empirical evaluation with benchmarks and case studies shows the feasibility of our approach. Emerging Internet of Things (IoTs) technologies provide many benefits to the improvement of eHealth. The successful deployment of IoTs depends on ensuring security and privacy that need to adapt to their processing capabilities and resource use. IoTs are vulnerable to attacks since communications are mostly wireless, unattended things are usually vulnerable to physical attacks, and most IoT components are constrained by energy, communications, and computation capabilities necessary for the implementation of complex security-supporting schemes. This paper describes a risk-based adaptive security framework for IoTs in eHealth that will estimate and predict risk damages and future benefits using game theory and context-awareness techniques. The paper also describes the validation case study.