Malicious Code Propagation Research Articles

Malicious Code Propagation Model Based on Sleep Monitoring Mechanism in Wireless Sensor Networks

<p>Wireless sensor networks (WSNs) are characterized by high node density and finite energy storage. Each node exchanges information with all its neighboring nodes frequently, which makes it easy for nodes to run out of energy, leading to paralysis of the WSNs when facing network malicious code attacks. To address this problem, a malicious code propagation model based on sleep-monitoring technology for WSNs is proposed. As a Multi-compartment propagation, sleep nodes and monitoring nodes are introduced to the conventional SIR model. Sleep nodes can turn the infected node into a dormant state and stop the dissemination of information to save energy. Monitoring nodes can contain malicious codes spread in wireless sensor networks by sharing prevention information in real time. Additionally, by calculating the equilibrium point and propagation threshold of the new feedback model, the corresponding Lyapunov function is constructed to prove the local stability and global stability of the equilibrium point. Finally, the results of numerical simulation experiments show that when the sleep rate is 0.3 and feedback rate is 0.0000005, the number of infected nodes in the wireless sensor network decreases by 43.45%. Therefore, adding sleep-monitoring technology can effectively control the spread of malicious code in the networks.</p> <p> </p>

Modeling of malicious code propagation in the industrial control network

With the development of digitalization, industrial control network have more connections and open to external network, which breaks their “isolation” from Internet and makes them more vulnerable to be attacked especially by malicious code. To model and analyze the impact of different containment strategies for attacks by malicious code in the industrial control network, the SUIQMR model is established to simulate malicious code propagation. Since the industrial control network is often coupled with Internet, industrial control coupling network is also considered in the SUIQMR model and the containment strategies of quarantine,benign worms and honeypot are added into the model to evaluate their effect against malicious code propagation.The simulation results show the effectiveness of our model.

A novel model for malware propagation on wireless sensor networks.

The main goal of this work was to propose a novel mathematical model for malware propagation on wireless sensor networks (WSN). Specifically, the proposed model was a compartmental and global one whose temporal dynamics were described by means of a system of ordinary differential equations. This proposal was more realistic than others that have appeared in the scientific literature since. On the one hand, considering the specifications of malicious code propagation, several types of nodes were considered (susceptible, patched susceptible, latent non-infectious, latent infectious, compromised non-infectious, compromised infectious, damaged, ad deactivated), and on the other hand, a new and more realistic term of the incidence was defined and used based on some particular characteristics of transmission protocol on wireless sensor networks.

A numerical study of a new non-linear fractal fractional mathematical model of malicious codes propagation in wireless sensor networks

This paper presents a novel non-linear fractal fractional mathematical model for analyzing the spread of malicious codes in wireless sensor networks (WSNs). The model incorporates fractional calculus and non-linear interactions among nodes in a WSN. It is based on the Fractal-Fractional (FF) operator, a powerful mathematical tool that combines fractional and fractal calculus. This study explores the potential of fractional derivatives in addressing computer virus-related issues and proposes a model that elucidates the spread of viruses in a vulnerable system and potential countermeasures. The Fractal-Fractional operator is utilized to fractionalize the model, and the fixed point theory of Schauder and Banach is applied to establish the existence and uniqueness of a solution. Numerical simulations, employing MATLAB and the Adams-Bashforth method, validate the effectiveness of the proposed model in capturing the propagation dynamics of malicious codes. Ulam-Hyers stability techniques are also employed for stability analysis. The model's insights contribute to enhancing the security and robustness of WSNs against malicious code propagation, paving the way for more secure network designs. This research provides a unique perspective on analyzing the dynamics of WSNs and underscores the significance of fractional derivatives in addressing security threats in network systems.

Search engine: The social relationship driving power of Internet of Things

Social Internet of Things (SIoT) integrates the social network with the Internet of Things (IoT) and has become a hot research issue for its potential to support novel IoT applications and networking services in more effective and efficient ways. The search engine, which is primarily designed for social network users to acquire interested information, also plays an important role in SIoT. There even exist search engines specially designed for SIoT. Using a search engine, people can easily find the smart devices in SIoT. Specifically, a search engine assists the information dissemination, i.e., enabling users (both humans and things) to access interested objects (both humans and things) with keywords-searching and transferring contents from the source directly to potential interested users. Accompanying such processes, the SIoT evolves as new links emerge between users and their interested objects. In this paper, we aim to quantitatively characterize how a search engine influences the social relationship in the IoT. Firstly, we point out that the search engine serves as the medium between the social network and the IoT, and then we propose a Search Social Internet of Things (SSIoT) model for SIoT evolution. Secondly, we adopt six performance metrics, namely, degree distribution, network diameter, average distance, network density, network stability, and user betweenness. Theoretically, we prove that the degree distribution follows an intensified power-law, the network diameter and the average distance shrink, network density, network stability, and user betweenness are greater in SSIoTs. Thirdly, we quantitatively show that a search engine accelerates malicious code propagation in SIoTs. Finally, based on four real-world data sets (i.e., CDBLP, Facebook, Weibo, and P2P), we verify our theoretical findings.

From botnets to MobiBots: a novel malicious communication paradigm for mobile botnets

Cyber security is moving from traditional infrastructure to sophisticated mobile infrastructureless threats. A major concern is that such imminent transition is happening at a rate far exceeding the evolution of security solutions. In fact, the transformation of mobile devices into highly capable computing platforms makes the possibility of security attacks originating from within the mobile network a reality. Today, mobile devices are capable of initiating sophisticated cyberattacks, especially when they coordinate together to form what we call a MobiBot. MobiBots differ from classical botnets in that they exploit mobile operating system vulnerabilities and the advantages of device-to-device communication to mask malicious code propagation.

Investigation of the C-SEIRA model for controlling malicious code infection in computer networks

Recently, there has been great concern about the serious burden and damage caused by malicious objects, such as computer worms, on the Internet. Therefore, the establishment of efficient policies for preventing the propagation of malicious objects becomes an important issue in the operation of computer networks. Because the propagation of malicious code is similar in many aspects to the infectious spread of biological viruses, ordinary-differential-equation-based population models, frequently used in the field of epidemiology, are useful in studying the population change of infectious hosts in computer networks. In this paper, we propose the controlled susceptible-exposed-infectious-removed-antidotal (C-SEIRA) model, an epidemiological population model describing the state transitions of a computer network under malicious code infection. For the proposed model, we derive stability results for the infection-free state and the endemic state. In addition, we apply optimal control theory to the C-SEIRA model with the goal of minimizing the infectious compartment population and the system treatment cost of isolating infectious computers from the network. Simulation results show that the spread of malicious objects can be controlled reasonably well via the optimal control approach.

Lightweight Attestation Scheme for Wireless Sensor Network

Wireless sensor networks (WSNs) have been deployed for several applications that use M2M communications. Malicious code propagation is considered a serious threat on WSNs. In this paper, we considere a simple, distributed remote attestation method for a WSN that does not require secret information, precise timing measurement, or a tamper-resistant device. Each node holds a value for the attestation of other nodes, and sensor nodes check the validity of each other's data. A sensor node terminates itself to prevent propagation of malicious code, when the sensor node nds a unexpected changes in stored program and data. We analyzed the probability of success in protecting the WSN against malicious code under random network models. The analyses con rmed the feasibility of the attestation scheme and we obtained a fundamental approach to nding an appropriate frequency for attestation.

The Study Found that the Intelligent Mobile Phone Technology of Malicious Code

This paper studies the development trend of intelligent mobile phone, confirmed the necessity of research on intelligent mobile phone malicious code. Study on the detection technology, proposed intelligent mobile phone regular networks and random networks based on malicious code propagation model, propagation mechanism is studied. Set up a perfect malicious code discovery and defense system model, at different levels is put forward that different, prove the necessity of scanning algorithm and Semantic Detection Algorithm for eigenvalue. To improve the security of the whole communication network.

Protecting online information sharing in peer‐to‐peer (P2P) networks

PurposeThe purpose of this paper is to present a P2P network security pricing model that promotes more secure online information sharing in P2P networks through the creation of networks with increased resistance to malicious code propagation. Online information sharing is at an all‐time high partly due to the recent growth in, and use of, online peer‐to‐peer (P2P) networks.Design/methodology/approachThe model integrates current research findings in incentive compatible network pricing with recent developments in complex network theory. File download prices in P2P networks are linked to network security using a graph theory measurement called the Pearson coefficient. The Pearson coefficient indicates a structural dimension of scale‐free networks (scale‐free networks like the internet) called preferential attachment. Preferential attachment refers to the network property where the probability for a node to connect to a new node is greater if the new node already has a high number of connections.FindingsThe P2P network security pricing model concept is illustrated to show how the model functions to create more secure P2P networks.Research limitations/implicationsFuture research in P2P network security pricing should focus on testing the model presented in this paper by numerical experiments and simulation including the tracking of malicious code propagation on networks grown under the pricing model.Originality/valueThe P2P network security pricing model demonstrated here is a different approach to network security that has a strong potential to impact on the future security of P2P and other computer based networks.