Exploiting Zero Knowledge Proof and Blockchain Towards the Enforcement of Anonymity, Data Integrity and Privacy (ADIP) on IoT

Abstract : In recent years, the Internet of Things (IoT) has been contemplated as the next technological advancement in the era of internet. This paper discloses the architecture of a multilayer, multimode security system for IoT. The proposed system is capable of providing multiple security solutions that support anonymous authentication, device privacy, data integrity, and the detection of device sybil attacks and IoT server spoofing attacks. For IoT access control and authentication, our system can support two modes of operations, one mode endorses protection of device privacy over network, and the second mode relinquishes device identity to establish data tracing during safety critical IoT events. The new security system is incorporated with two crypto approaches, Zero Knowledge Proof (ZKP) and Blockchain. IoT devices anonymity were achieved via multimode ZKP protocol. Data integrity and protection against sybil and IoT spoofing attacks were maintained via blockchain. Our threats analysis models showed that data modification and data injections attacks are not feasible. A probabilistic modeling of IoT spoofing attack was presented in this paper, it shows that our security system provides high resiliency against such attacks with a probability approaching 1.

 EXISTING SYSTEM :

 ? In contrast to existing location-proof methods, the proposed system does not require a trusted centralized third-party. ? There are several existing consensus generation algorithms, including Proof-of-Work (PoW), Proof-of-Stake (PoS), Proof-of-Space (PoSpace) and practical Byzantine fault tolerance (PBFT). ? There always exists a trade-off between the performance and security level when deciding the public key length. ? Although LBS provided by SRC (especially BLE) techniques are highly demanded in the contact tracing of COVID19 pandemic and many more daily demands, much uncertainty still exists on data security, privacy, and deployment efficiency.

 DISADVANTAGE :

 ? The BC was employed by Nakamoto in the first cryptocurrency (CC) system, Bitcoin, where it was used to solve the double spending problem. ? Manufacturers announce updates by deploying a smart contract (SC), which in turn will issue cryptocurrency payments to any distributor who provides an unforgeable proof-of-delivery. ? It works as an unforgeable digital commitment through which an IoT device is authorizing the SC to issue a payment to a certain distributor. ? To address this issue in our proposal, we introduce the possibility for distributors to share the update with new distributors in exchange for a CC payment.

 PROPOSED SYSTEM :

 • An artificial potential field-based incentive allocation mechanism is proposed to incentivize IoT witnesses to pursue the maximum monitoring coverage deployment. • To empower Bychain with the ability of witness deployment, an incentive allocation algorithm is proposed based on the virtual potential field. • By jointly design of crucial escrow and zero-knowledge proof method, the proposed protocol is able to obtain location identity privacy and security. • A generalized block structure is proposed to fulfill the requirement of new on-chain operations. • Short-range communication technologies, such as Bluetooth, have been proposed to generate location evidence from its neighbors.

 ADVANTAGE :

 ? We intend to develop a full prototype implementation of the protocol and extensively evaluate its performance in real deployments. ? The need for efficient and lightweight cryptographic primitives and protocols. ? The latter can be now used to decrypt the file, and the update is finally obtained by the IoT device. ? We exploit the only reliable information a distributor is required to provide: the public key used as recipient for CC payments. ? This value, stored on the BC and accessible by anyone, can be used by other participants to judge the relative trustworthiness of any distributor compared to others. ? Facts are used to model all the possible components of the system states, while rules describe the transitions between those states.