Mobile Agent Based Authentication for Wireless Network Security

Wireless Local Area Network (WLAN) is an alternative in overcoming cabling problems in a local network. Often wireless network security that is installed still uses vendor default settings such as SSID, IP Address, remote management, DHCP enabled, frequency channels, without encryption, even user or password for wireless administration. How does a strong WLAN security system work? The most common security system applied to wireless networks at this time is starting from securing access points by applying the MAC Filtering concept, using WPA / WPA2-PSK security keys, and RADIUS server authentication. To see the quality of wireless LAN network security, how do you analyze the test of the existing security system in the network. The method that can be used in evaluating wireless networks is by testing the system by simulating forms of attacks on wireless networks with the Penetration Testing method. By carrying out 4 stages of research using the penetration testing method (i) the planning stage, (ii) the discovery stage, (iii) the attack stage and (iv) the report stage, from the attack stage (Cracking The Encryption, Bypassing MAC Address, Attacking The Infrastructure and MITM ) using Kali Linux got the results of four types of attacks carried out, only one of which was failed, namely the cracking attack type of the encryption on the RADIUS server due to using captive portal authentication

This study evaluates the current state of wireless network security in the CBD of Nuku'alofa. Wireless Networks have grown significantly since their introduction. Security protocols supplied with the wireless equipment have reached a level of strong and robust security. However, security remains a problem; this study aims to answer two questions. What is the status of wireless network growth and security in Tonga? and what can be done to improve wireless network security in Tonga. The war-drive results of Nuku'alofa produced comprehensive data which clearly shows the number of networks, both company and home networks. An exploratory research approach is employed to guide the design of the study. The results show that there is a significant growth in terms of WLAN usage since the implementation of the fiber optic network. However, this study concludes that WLAN security in Nuku'alofa is still in its early stages.

Mobile and Wireless Network Security and Privacy analyzes important security and privacy problems in the realms of wireless networks and mobile computing. The material includes a report to the National Science Foundation of the United States which will be used by program managers for the foundation in setting priorities for research directions in this area. In the following chapters field experts expand upon the report and provide further information about important research directions in the fields of wireless networks and mobile computing. The chapters are written by the leading international researchers and professionals in thes fields. Each chapter represents state-of-the-art research and includes several influential contributions. A multitude of valuable discussions on relevant concepts, such as the various approaches that define emerging security and privacy in mobile and wireless environment, are featured. The book is useful to researchers working in the fields of mobile and wireless security and privacy and to graduate students seeking new areas to perform research. It also provides information for academics and industry people researching recent trends and developments in the mobile and wireless security fields.

Machine learning has been used in wireless networking for wireless RF allocation, power allocations, predicting traffic load and inferencing/estimating channels. However, machine learning in wireless networking faces several challenges because of the big or small data, unlabeled data, system complexity, long training process, resource constrained (energy, storage, computing) wireless devices, and constantly changing user mobility, dynamic network topology, susceptibility of wireless jammers and eavesdroppers, and operating wireless environment. In order to address these challenges, transfer learning is regarded as one of the viable solutions as it leverages the knowledge from similar past tasks for learning of new problems. In this paper, we investigate deep transfer learning for physical layer security in wireless networks with large-scale multiple-input multiple output (MIMO) system where previously trained model is transferred to a new wireless environment to predict secure waveform vectors and power levels for users who coexist with eavesdroppers (who overhear communications passively for resulting in lower secrecy rate for legitimate users) and jammers (who actively jam the channels or deteriorate the received signal at the legitimate receivers). In this case, a legitimate transmitter adapts it's transmit waveform and power using transfer learning to avoid jamming and eavesdropping impacts. This is analogous to training war-fighters in a training camp and deploying them to a completely new real battlefield where they are expected to (learn instantly and) defeat the enemy based on their past training. We evaluate the performance of the proposed approach using numerical results obtained from extensive simulations.

Due to the wireless network is popularly used, the security of wireless network is more important than past. Wireless network is considerably more susceptible to MitM (man-in-the-middle) attack. This paper proposes a Rogue AP based MitM attack framework. In actual wireless network, the mobile terminals cannot properly validate the server due to their limitation. The attackers force the user to connect the Rogue AP so as to obtain the authentication credentials of the unauthorized users. Then the attackers use these credentials to connect to the legitimate AP. We test this MitM framework in the actual wireless network environment under the EAP-TTLS/MSCHAPv2 using different mobile terminals. Last we propose a two-factor based dynamic password technology to prevent this MitM attack.

Aiming at the problems of traditional wireless communication network security vulnerability monitoring systems such as low monitoring accuracy and time-consuming, a machine learning-based intelligent monitoring system for wireless communication network security vulnerabilities is proposed. In the hardware design of the monitoring system, based on the overall architecture of the wireless communication network and the data characteristics of the wireless communication network, it is divided into a vulnerability data collection module, a vulnerability data scanning module, and a network security vulnerability intelligent monitoring module. In the vulnerability data collection module, the wireless data collector is used to collect vulnerability data in the vulnerability database, and according to the attributes of the vulnerability data, the XSS vulnerability detection plug-in is connected to the vulnerability scanner to scan for wireless communication network vulnerabilities; When the communication network vulnerability data signal is traced, the system session operation of monitoring the vulnerability data. The software part introduces the neural network algorithm in the machine learning intelligent algorithm to process the hidden data in the security vulnerability data. The experimental results show that the wireless communication network security vulnerability intelligent monitoring system based on machine learning can effectively improve the system monitoring accuracy and the efficiency of wireless communication network security vulnerability monitoring.

The communication network indicators are analyzed and cryptographic analysis is considered to ensure information security of wireless communication networks using the application. Exploring fundamental principles and key algorithms like Advanced Encryption Standard and Rivest-Shamir-Adleman, this article equips readers with practical insights. This paper examines the challenges of researching cryptographic analysis to ensure the security of wireless communication networks using the application By understanding cryptographic algorithms and their application in wireless networks, readers can enhance the security their digital communications. A wireless network is used to connect various wired organizational structures and provide connectivity within the organization for employees to move freely by avoiding the hurdle of a physical network. Subsequent sections offer theoretical insights and performance analysis of cryptographic algorithms using the Java programming language.

In wireless sensor networks, the mobile agent technology is used in data transmission from one cluster to another cluster. The Optimization of mobile agent in the routing within the clustering algorithm for wireless sensor networks to further reduce the amount of data transfer. the main objectives of wireless sensor network design is to improve the energy efficiency & effective utilization of sensor nodes to prolong the lifespan of a wireless network .This paper presents an effective clustering algorithm, which is an extension to the LEACH routing algorithm., this algorithm fully utilizes the location information of network nodes in routing to reduce the routing cost. Through a clustering approach of intelligent mobile agents, it is possible to reduce the cost of time for each individual agent, here the problem of Multiple Clustering of Mobile Agents (MCCMA) where the decision is to cluster mobile agents such that a group of similar intelligent mobile agents will visit a group of similar sensor nodes are compare with location based clustering algorithm of wsn. both of Simulation results indicate that these algorithm & approach of mobile agent & wireless sensor network Nodes can have balance nodes' energy consumption and prolong the network's life span. It also has good extensibility & stability

SonicWALL Secure Wireless Network Integrated Solutions Guide

Facing Global Environmental Change

Computer networks have come a long way since their inception, and wireless networks are the new trend in the IT market. However, every new technology comes with several advantages and disadvantages. This paper addresses some of the key advances and some of the shortcomings of wireless networks security. It reviews various types of security levels currently offered by standard wireless networks, such as the wired equivalent privacy (WEP); the Wi-Fi protected access (WPA); and 802.11 - the latter defined as the ultimate security available for wireless networks to date. The paper also lists benefits of wireless networks and examples of cost savings. Corporations have been found to consider wireless installations based on the lower total cost of ownership (TCO) and return on investment (ROI) scenarios. In addition to general financial benefits, wireless networks have their own performance benefits such as, for example, increases in data accuracy, and increases in user productivity. There are few industries that have expanded their boundaries in the wireless arena: financial, educational institutions, healthcare facilities and airports (travel). With security being one of the major concerns irrespective of the industry type, the authors highlight factors that senior and mid level IT management should consider when implementing wireless networks. The success story of General Motors investment in wireless LANs factories presents a best practice for WLANs implementations. In the conclusions, questions still open and opportunities for future research are discussed.

Cyberbullying has emerged as a pervasive issue in today''''''''s digitally connected society, with detrimental effects on individuals’ mental health and well-being. Despite increasing awareness and efforts to address cyberbullying, there remains a significant gap in utilizing wireless network security measures as a means of mitigation. The existing literature predominantly focuses on social and psychological aspects of cyberbullying, overlooking the potential role of wireless network security in prevention and intervention strategies. This research seeks to fill this gap by exploring the effectiveness of leveraging wireless network security to secure cyberspace against cyberbullying incidents. The research employs a multifaceted methodology, beginning with the estimation of expected rates and derivative risks of cyberbullying within wireless networks. These metrics are combined into a risk index value, which serves as a basis for prioritizing mitigation efforts. Additionally, the study explores the application of cyberspace modeling techniques, specifically Support Vector Machines (SVM), to enhance screening processes and identify potential cyberbullying incidents on Wireless Network Security (WNS). The findings of this research demonstrate the efficacy of integrating wireless network security measures into cyberbullying prevention strategies. By combining risk index values and leveraging SVM-based cyberspace modeling, the study identifies and prioritizes cyberbullying risks effectively. Furthermore, the implementation of wireless network security protocols contributes to a reduction in cyberbullying incidents, fostering safer digital environments for users.

We kindly welcome you to the 17th ACM International Symposium on QoS and Security for Wireless and Mobile Networks (Q2SWinet'21). This year, Q2SWinet will exceptionally be held online due to the COVID-19 pandemic, on November 22nd to November 26th, 2021. The Q2SWinet 2021 Symposium aims at serving as a meeting point and a forum for exchanging ideas, discussing solutions, and sharing experiences among researchers, professionals, application developers, and practitioners from institutions around the world. As with the previous sixteen editions of the Q2SWinet symposium series, the scope of this year's Symposium will remain on general issues related to QoS and security in wireless and mobile networks networking and computing. The call for papers has attracted a large number of high-quality submissions worldwide. Every paper submitted had been peer-reviewed by at least three referees from the Technical Program Committee. The featured papers span from a wide range of topics related to multimedia content delivery and video streaming, 5G and wireless networks, fog computing, and Internet of Things.

Objectives: This paper proposes a new mobile agent based cloud security framework comprising four different security and authentication layers to establish the trust relationship between two entities before using cloud services. Methods/Analysis: The proposed framework is divided into four layers with each layer performing authentication, verification and integrity at different levels of communication between two entities. An algorithm is used to check and analyze the validity and functionality of each layer. Mobile agents are used as main components for performing different tasks assigned and requested by clients from cloud service providers. Findings: The framework uses authenticated mobile agents from both clients and cloud service provider to perform the tasks on behalf of users to establish trustworthy computing relationship. This makes the whole process transparent and clear according to users and cloud service providers’ perspective. The proposed framework effectively ensures privacy and security of client data and gives control to client over his data using the security agents. Conclusion/Application: The main contribution of this paper is undoubtedly the agreement of trustworthy relationship between two entities to agree on security service level agreements to dynamically configure and add mobile agents on virtual machines handled by task managers in their respective mobile agent platforms.

Security in wireless networks is a serious challenge due to the access of the channel to adversaries because of the channel being unguided. Conventional encryption mechanisms cannot guarantee security in wireless networks since even the most complex encryption algorithms can be broken. Hence, deliberate jamming is one way to safeguard data from possible attacks. This paper proposes a band jamming technique using fast frequency hopping (FFH) along with non-coherent detection for evading possible attacks. The performance parameters evaluated the bit error rate (BER) and the outage probability of the proposed system. Non-coherent detection has been employed since maintaining coherence for a fast frequency hopping technique is extremely challenging under practical noisy channel conditions. The results show the various stages of the jamming and de-jamming processes.