Characteristic Insights on Industrial Cyber Security and Popular Defense Mechanisms

Due to the deep integration of information technology and operational technology,networked control systems are experiencing an increasing risk of international cyber attacks.In practice,industrial cyber security is a significant topic because current networked control systems are supporting various critical infrastructures to offer vital utility services.By comparing with traditional IT systems,this paper first analyzes the uncontrollable cyber threats and classified attack characteristics,and elaborates the intrinsic vulnerabilities in current networked control systems and novel security challenges in future Industrial Internet.After that,in order to overcome partial vulnerabilities,this paper presents a few representative security mechanisms which have been successfully applied in today’s industrial control systems,and these mechanisms originally improve traditional IT defense technologies from the perspective of industrial availability.Finally,several popular security viewpoints,adequately covering the needs of industrial network structures and service characteristics,are proposed to combine with burgeoning industrial information technologies.We target to provide some helpful security guidelines for both academia and industry,and hope that our insights can further promote in-depth development of industrial cyber security.

A Detection Method of WLAN Security Mechanisms Based on MAC Frame Resolution

Security mechanism detection is not only an important content of vulnerabilities evaluation but also the foundation of key strength test for wireless local area network （WLAN）. This paper analyzes the specifications of WLAN security mechanisms and points out the defects in design of security mechanisms detection algorithm based on the standards. By capturing and analyzing a large number of Beacon frames from different vendor＇s access points （APs）, we summarize the relevant fields and information elements in a Beacon frame, and present their values or status when an AP is set to every specific security mechanism. A detection algorithm of WLAN security mechanisms is proposed based on the experimental study result and the pseudo code of a reference implementation for the algorithm is designed. The validity of the algorithm is illustrated by examples, which shows it can detect every WLAN security mechanism accurately.

A Survey on the Evolution of Bootkits Attack and Defense Techniques

According to the boot process of modern computer systems,whoever boots first will gain control first.Taking advantage of this feature,a malicious code called bootkit can hijack the control before the OS bootloader and bypass security mechanisms in boot process.That makes bootkits difficult to detect or clean up thoroughly.With the improvement of security mechanisms and the emergence of UEFI,the attack and defense techniques for bootkits have constantly been evolving.We first introduce two boot modes of modern computer systems and present an attack model of bootkits by some sophistical samples.Then we discuss some classic attack techniques used by bootkits from their initial appearance to the present on two axes,including boot mode axis and attack phase axis.Next,we evaluate the race to the bottom of the system and the evolution process between bootkits and security mechanisms.At last,we present the possible future direction for bootkits in the context of continuous improvement of OS and firmware security mechanisms.

Protecting Terminals by Security Domain Mechanism Based on Trusted Computing

Networks are composed with servers and rather larger amounts of terminals and most menace of attack and virus come from terminals. Eliminating malicious code and ac cess or breaking the conditions only under witch attack or virus can be invoked in those terminals would be the most effec tive way to protect information systems. The concept of trusted computing was first introduced into terminal virus immunity. Then a model of security domain mechanism based on trusted computing to protect computers from proposed from abstracting the general information systems. The principle of attack resistant and venture limitation of the model was demonstrated by means of mathematical analysis, and the realization of the model was proposed.

Neuro-Computing Applications in Security of Network Information Systems

Currently computing information systems have entered a new stage and the security of systems is more and more serious, and the research on system security is developing in depth. This paper discusses neuro-computing applications in security of network information systems.

Advanced Authentication Mechanisms for Identity and Access Management inCloud Computing

Identity management is based on the creation and management of useridentities for granting access to the cloud resources based on the user attributes.The cloud identity and access management (IAM) grants the authorization tothe end-users to perform different actions on the specified cloud resources. Theauthorizations in the IAM are grouped into roles instead of granting them directlyto the end-users. Due to the multiplicity of cloud locations where data resides anddue to the lack of a centralized user authority for granting or denying cloud userrequests, there must be several security strategies and models to overcome theseissues. Another major concern in IAM services is the excessive or the lack ofaccess level to different users with previously granted authorizations. This paperproposes a comprehensive review of security services and threats. Based on thepresented services and threats, advanced frameworks for IAM that provideauthentication mechanisms in public and private cloud platforms. A threat modelhas been applied to validate the proposed authentication frameworks with different security threats. The proposed models proved high efficiency in protectingcloud platforms from insider attacks, single sign-on failure, brute force attacks,denial of service, user privacy threats, and data privacy threats.

A Systematic Overview of Underwater Wireless Sensor Networks:Applications,Challenge and Research Perspectives

Underwater Wireless Sensor Networks(UWSNs)are becoming increasingly popular in marine applications due to advances in wireless and microelectronics technology.However,UWSNs present challenges in processing,energy,and memory storage due to the use of acoustic waves for communication,which results in long delays,significant power consumption,limited bandwidth,and packet loss.This paper provides a comprehensive review of the latest advancements in UWSNs,including essential services,common platforms,critical elements,and components such as localization algorithms,communication,synchronization,security,mobility,and applications.Despite significant progress,reliable and flexible solutions are needed to meet the evolving requirements of UWSNs.The purpose of this paper is to provide a framework for future research in the field of UWSNs by examining recent advancements,establishing a standard platform and service criteria,using a taxonomy to determine critical elements,and emphasizing important unresolved issues.

Adaptive multi-channel Bayesian graph attention network for IoT transaction security

With the rapid advancement of 5G technology,the Internet of Things(IoT)has entered a new phase of appli-cations and is rapidly becoming a significant force in promoting economic development.Due to the vast amounts of data created by numerous 5G IoT devices,the Ethereum platform has become a tool for the storage and sharing of IoT device data,thanks to its open and tamper-resistant characteristics.So,Ethereum account security is necessary for the Internet of Things to grow quickly and improve people's lives.By modeling Ethereum trans-action records as a transaction network,the account types are well identified by the Ethereum account classifi-cation system established based on Graph Neural Networks(GNNs).This work first investigates the Ethereum transaction network.Surprisingly,experimental metrics reveal that the Ethereum transaction network is neither optimal nor even satisfactory in terms of accurately representing transactions per account.This flaw may significantly impede the classification capability of GNNs,which is mostly governed by their attributes.This work proposes an Adaptive Multi-channel Bayesian Graph Attention Network(AMBGAT)for Ethereum account clas-sification to address this difficulty.AMBGAT uses attention to enhance node features,estimate graph topology that conforms to the ground truth,and efficiently extract node features pertinent to downstream tasks.An extensive experiment with actual Ethereum transaction data demonstrates that AMBGAT obtains competitive performance in the classification of Ethereum accounts while accurately estimating the graph topology.

A Secure Multi-Routing Platform for Ad Hoc Network

In an ad hoc network, it is usually difficult to optimize the assignment of network routing resources using a single type of routing protocol due to the differences in network scale, node moving mode and node distribution. Therefore, it is desirable to have nodes run multiple routing protocols simultaneously so that more than one protocols can be chosen to work jointly. For this purpose, a multiple routing platform for Ad hoc networks is proposed on a higher level of current routing protocols. In order to ensure the security of the platform, a security mechanism and its formal analysis by BAN logic is given. The simulation results of the network performance demonstrate that the proposed multi-routing platform is practicable in some complex applications.