An Immunity-Based IOT Environment Security Situation Awareness Model

Abstract

To effectively perceive network security situation under IOT environment, an Immunity-based IOT Environment Security Situation Awareness (IIESSA) model is proposed. In IIESSA, some formal definitions for self, non-self, antigen and detector are given. According to the relationship between the antibody-concentration of memory detectors and the intensity of network attack activities, the security situation evaluation method under IOT environment based on artificial immune system is presented. And then according to the situation time series obtained by the mentioned evaluation method, the security situation prediction method based on grey prediction theory is presented for forecasting the intensity and security situation of network attack activities that the IOT environment will be suffered in next step. The experimental results show that IIESSA provides a novel and effective model for perceiving security situation of IOT environment.

Towards a Secure Internet of Things: A Comprehensive Study of Second Line Defense Mechanisms

“…In [113], the proposed hybrid architecture is implemented using a Central Security System (CSS), but the aggregation of information such as RSSI is done by Radio Probes. In [108], the detection components are 6BR as a security awareness center (SAC) and security sensors (SS). The SS is viewed as immunitybased sensor which extracts, evaluates and predicts security situations.…”

“…Clonal selection algorithms, a common technique in AIS has been used to evolve the detector for new and mutated attacks in [106]. Further amelioration of AIS involves delegating the training of AIS to the cloud platform [107] and grey prediction method for intrusion prediction and response [108]. [114] propose lightweight GRU with one hidden layer and one hidden unit and performed ten experiments for tuning each hyper parameter to an optimal value.…”

“…In reality, Cooja is not a simulator rather an emulator, thus producing realistic IoT scenarios. In order to reproduce such realistic scenarios, authors in [46], [48], [82], [86], [87], [108], [132], [135], [136], [143] run experiments on emulated Tmote sky nodes within the Cooja Simulator, running Contiki code. Cooja emulates real IoT traffic with additional features like PowerTrace [162], which helps to analyze the power consumption of a sensor node.…”

“…Theoretical analysis by creating a system model, lemma and proofs are done in [100], [101], [105]. [46], [48], [70]- [73], [77]- [79], [86], [89], [95]- [97], [107], [108], [112]- [115], [128], [129], [131], [134], [136], [143], [144], [148], [150]- [152] [80]- [82], [84], [85], [87], [88], [98], [101], [103], [109], [110], [118], [119], [122], [123], [130], [135], [138], [146], [147] [74], [83] Hybrid [102] [125], [132],…”

Security Privacy in Internet of Things(IOT)

“…The security and Privacy requirements in IOT are authentication, Access control, Data confidentiality, security and trust, etc. different layers of IOT [6]. Security problems, such as denial of service attacks, sybil attacks, data attacks, code attacks, local security of sensing nodes.…”