Biblio
Under the situation of regular epidemic prevention and control, teleworking has gradually become a normal working mode. With the development of modern information technologies such as big data, cloud computing and mobile Internet, it's become a problem that how to build an effective security defense system to ensure the information security of teleworking in complex network environment while ensuring the availability, collaboration and efficiency of teleworking. One of the solutions is Zero Trust Network(ZTN), most enterprise infrastructures will operate in a hybrid zero trust/perimeter-based mode while continuing to invest in IT modernization initiatives and improve organization business processes. In this paper, we have systematically studied the zero trust principles, the logical components of zero trust architecture and the key technology of zero trust network. Based on the abstract model of zero trust architecture and information security technologies, a prototype has been realized which suitable for iOS terminals to access enterprise resources safely in teleworking mode.
As millions of IoT devices are interconnected together for better communication and computation, compromising even a single device opens a gateway for the adversary to access the network leading to an epidemic. It is pivotal to detect any malicious activity on a device and mitigate the threat. Among multiple feasible security threats, malware (malicious applications) poses a serious risk to modern IoT networks. A wide range of malware can replicate itself and propagate through the network via the underlying connectivity in the IoT networks making the malware epidemic inevitable. There exist several techniques ranging from heuristics to game-theory based technique to model the malware propagation and minimize the impact on the overall network. The state-of-the-art game-theory based approaches solely focus either on the network performance or the malware confinement but does not optimize both simultaneously. In this paper, we propose a throughput-aware game theory-based end-to-end IoT network security framework to confine the malware epidemic while preserving the overall network performance. We propose a two-player game with one player being the attacker and other being the defender. Each player has three different strategies and each strategy leads to a certain gain to that player with an associated cost. A tailored min-max algorithm was introduced to solve the game. We have evaluated our strategy on a 500 node network for different classes of malware and compare with existing state-of-the-art heuristic and game theory-based solutions.
The Internet of things (IoT) is revolutionizing the management and control of automated systems leading to a paradigm shift in areas such as smart homes, smart cities, health care, transportation, etc. The IoT technology is also envisioned to play an important role in improving the effectiveness of military operations in battlefields. The interconnection of combat equipment and other battlefield resources for coordinated automated decisions is referred to as the Internet of battlefield things (IoBT). IoBT networks are significantly different from traditional IoT networks due to the battlefield specific challenges such as the absence of communication infrastructure, and the susceptibility of devices to cyber and physical attacks. The combat efficiency and coordinated decision-making in war scenarios depends highly on real-time data collection, which in turn relies on the connectivity of the network and the information dissemination in the presence of adversaries. This work aims to build the theoretical foundations of designing secure and reconfigurable IoBT networks. Leveraging the theories of stochastic geometry and mathematical epidemiology, we develop an integrated framework to study the communication of mission-critical data among different types of network devices and consequently design the network in a cost effective manner.
The Internet of things (IoT) is revolutionizing the management and control of automated systems leading to a paradigm shift in areas, such as smart homes, smart cities, health care, and transportation. The IoT technology is also envisioned to play an important role in improving the effectiveness of military operations in battlefields. The interconnection of combat equipment and other battlefield resources for coordinated automated decisions is referred to as the Internet of battlefield things (IoBT). IoBT networks are significantly different from traditional IoT networks due to battlefield specific challenges, such as the absence of communication infrastructure, heterogeneity of devices, and susceptibility to cyber-physical attacks. The combat efficiency and coordinated decision-making in war scenarios depends highly on real-time data collection, which in turn relies on the connectivity of the network and information dissemination in the presence of adversaries. This paper aims to build the theoretical foundations of designing secure and reconfigurable IoBT networks. Leveraging the theories of stochastic geometry and mathematical epidemiology, we develop an integrated framework to quantify the information dissemination among heterogeneous network devices. Consequently, a tractable optimization problem is formulated that can assist commanders in cost effectively planning the network and reconfiguring it according to the changing mission requirements.