A Review Paper on Security of Wireless Network

In the past few years, wireless networks, specifically those based on the IEEE 802.11 Standard, have experienced tremendous growth. A team at Rice University recovered the 802.11 Wired Equivalent Privacy 128-bit security key which is used by an active network. This Standard has increased the interest and attention of many researchers in recent years. The IEEE 802.11 is a family of standards, which defines and specifies the parts of the standard. This paper explains the survey on the latest development in how to secure an 802.11 wireless network by understanding its security protocols and mechanism. In order to fix security loopholes a public key authentication and key-establishment procedure has been proposed which fixes security loopholes in current standard. The public key cryptosystem is used to establish a session key securely between the client and Access point. Knowing how these mechanism and protocols works, including its weakness and vulnerabilities can be very helpful for planning, designing, implementing and/or hardening a much secure wireless network, effectively minimizing the impact of an attack. The methods used in current research are especially emphasized to analysis the technique of securing 802.11 standards. Finally, in this paper we pointed out some possible future directions of research

Development of a Client-Side Evil Twin Attack Detection System for Public Wi-Fi Hotspots based on Design Science Approach

Users and providers benefit considerably from public Wi-Fi hotspots. Users receive wireless Internet access and providers draw new prospective customers. While users are able to enjoy the ease of Wi-Fi Internet hotspot networks in public more conveniently, they are more susceptible to a particular type of fraud and identify theft, referred to as evil twin attack (ETA). Through setting up an ETA, an attacker can intercept sensitive data such as passwords or credit card information by snooping into the communication links. Since the objective of free open (unencrypted) public Wi-Fi hotspots is to provide ease of accessibility and to entice customers, no security mechanisms are in place. The public’s lack of awareness of the security threat posed by free open public Wi-Fi hotspots makes this problem even more heinous. Client-side systems to help wireless users detect and protect themselves from evil twin attacks in public Wi-Fi hotspots are in great need. In this dissertation report, the author explored the problem of the need for client-side detection systems that will allow wireless users to help protect their data from evil twin attacks while using free open public Wi-Fi. The client-side evil twin attack detection system constructed as part of this dissertation linked the gap between the need for wireless security in free open public Wi-Fi hotspots and limitations in existing client-side evil twin attack detection solutions. Based on design science research (DSR) literature, Hevner’s seven guidelines of DSR, Peffer’s design science research methodology (DSRM), Gregor’s IS design theory, and Hossen & Wenyuan’s (2014) study evaluation methodology, the author developed design principles, procedures and specifications to guide the construction, implementation, and evaluation of a prototype client-side evil twin attack detection artifact. The client-side evil twin attack detection system was evaluated in a hotel public Wi-Fi environment. The goal of this research was to develop a more effective, efficient, and practical client-side detection system for wireless users to independently detect and protect themselves from mobile evil twin attacks while using free open public Wi-Fi hotspots. The experimental results showed that client-side evil twin attack detection system can effectively detect and protect users from mobile evil twin AP attacks in public Wi-Fi hotspots in various real-world scenarios despite time delay caused by many factors

Masquerading Techniques in IEEE 802.11 Wireless Local Area Networks

The airborne nature of wireless transmission offers a potential target for attackers to compromise IEEE 802.11 Wireless Local Area Network (WLAN). In this dissertation, we explore the current WLAN security threats and their corresponding defense solutions. In our study, we divide WLAN vulnerabilities into two aspects, client, and administrator. The client-side vulnerability investigation is based on examining the Evil Twin Attack (ETA) while our administrator side research targets Wi-Fi Protected Access II (WPA2). Three novel techniques have been presented to detect ETA. The detection methods are based on (1) creating a secure connection to a remote server to detect the change of gateway\u27s public IP address by switching from one Access Point (AP) to another. (2) Monitoring multiple Wi-Fi channels in a random order looking for specific data packets sent by the remote server. (3) Merging the previous solutions into one universal ETA detection method using Virtual Wireless Clients (VWCs). On the other hand, we present a new vulnerability that allows an attacker to force the victim\u27s smartphone to consume data through the cellular network by starting the data download on the victim\u27s cell phone without the victim\u27s permission. A new scheme has been developed to speed up the active dictionary attack intensity on WPA2 based on two novel ideas. First, the scheme connects multiple VWCs to the AP at the same time-each VWC has its own spoofed MAC address. Second, each of the VWCs could try many passphrases using single wireless session. Furthermore, we present a new technique to avoid bandwidth limitation imposed by Wi-Fi hotspots. The proposed method creates multiple VWCs to access the WLAN. The combination of the individual bandwidth of each VWC results in an increase of the total bandwidth gained by the attacker. All proposal techniques have been implemented and evaluated in real-life scenarios

Wireless Handheld Solution for the Gaming Industry

of the essential elements of success in the gaming industry is the requirement of providing exceptional customer service. Technology plays a significant role in bringing state of the art solutions that enhance the overall customer experience. Currently a guest must go through multiple steps and a variety of departments to simply resolve issues with their player accounts (loyalty programs), update customer profiles, book hotel and restaurant reservations, sign up for promotions, etc. In order to effectively take care of these customers in both a timely and efficient manner, a wireless handheld device is needed that employees can carry with them to resolve and address these concerns. This project is aimed at identifying the proper wireless infrastructure for the gaming environment and also the wireless handheld device, such as an Ultra Mobile PC (UMPC) to effectively and efficiently take care of customers

An efficient deep learning model for intrusion classification and prediction in 5G and IoT networks

A Network Intrusion Detection System is a critical component of every internet-connected system due to likely attacks from both external and internal sources. Such Security systems are used to detect network born attacks such as flooding, denial of service attacks, malware, and twin-evil intruders that are operating within the system. Neural networks have become an increasingly popular solution for network intrusion detection. Their capability of learning complex patterns and behaviors make them a suitable solution for differentiating between normal traffic and network attacks. In this paper, we have applied a deep autoencoded dense neural network algorithm for detecting intrusion or attacks in 5G and IoT network. We evaluated the algorithm with the benchmark Aegean Wi-Fi Intrusion dataset. Our results showed an excellent performance with an overall detection accuracy of 99.9% for Flooding, Impersonation and Injection type of attacks. We also presented a comparison with recent approaches used in literature which showed a substantial improvement in terms of accuracy and speed of detection with the proposed algorithm

Darma: Defeating And Reconnaissance Manna-Karma Attacks In 802.11 With Multiple Detections And Prevention

The vast growing usage of mobile phones increases Wi-Fi technology. At present, the pattern of human interaction with the internet is not a desktop or laptop anymore. The assimilation of tools for surfing, working, and communication is now shifting to mobile phones. Thus, this is the motivation to expand Wi-Fi technology so that it will be the primary medium for internet connectivity. Hence, increasing the security risk for it attracts attackers despite its popularity among users. The DOS attack in 802.11 management frames is widely known as an initial process before Man-in-the-middle (MiTM) attacks in 802.11 takes part. Karma and Manna's attacks are an unprecedented attack in the 802.11 management frames. This paper proposed a mechanism called Defeating and Reconnaissance Manna-karma Attack (DARMA), which is client-side multiple detection techniques to defeat and prevent karma-manna attack. The proposed mechanism consisted of 4 layers of processes inclusive of monitors, detection, confirmation, and preventions. The effectiveness of the detection is base of the current real-time behaviour of the packets

Empirical Techniques To Detect Rogue Wireless Devices

Media Access Control (MAC) addresses in wireless networks can be trivially spoofed using off-the-shelf devices. We proposed a solution to detect MAC address spoofing in wireless networks using a hard-to-spoof measurement that is correlated to the location of the wireless device, namely the Received Signal Strength (RSS). We developed a passive solution that does not require modification for standards or protocols. The solution was tested in a live test-bed (i.e., a Wireless Local Area Network with the aid of two air monitors acting as sensors) and achieved 99.77%, 93.16%, and 88.38% accuracy when the attacker is 8–13 m, 4–8 m, and less than 4 m away from the victim device, respectively. We implemented three previous methods on the same test-bed and found that our solution outperforms existing solutions. Our solution is based on an ensemble method known as Random Forests. We also proposed an anomaly detection solution to deal with situations where it is impossible to cover the whole intended area. The solution is totally passive and unsupervised (using unlabeled data points) to build the profile of the legitimate device. It only requires the training of one location which is the location of the legitimate device (unlike the misuse detection solution that train and simulate the existing of the attacker in every possible spot in the network diameter). The solution was tested in the same test-bed and yield about 79% overall accuracy. We build a misuseWireless Local Area Network Intrusion Detection System (WIDS) and discover some important fields in WLAN MAC-layer frame to differentiate the attackers from the legitimate devices. We tested several machine learning algorithms and found some promising ones to improve the accuracy and computation time on a public dataset. The best performing algorithms that we found are Extra Trees, Random Forests, and Bagging. We then used a majority voting technique to vote on these algorithms. Bagging classifier and our customized voting technique have good results (about 96.25 % and 96.32 %respectively) when tested on all the features. We also used a data mining technique based on Extra Trees ensemble method to find the most important features on AWID public dataset. After selecting the most 20 important features, Extra Trees and our voting technique are the best performing classifiers in term of accuracy (96.31 % and 96.32 % respectively)

Evil-twin framework: a Wi-Fi intrusion testing framework for pentesters

In today’s world there is no scarcity of Wi-Fi hotspots. Although users are always recommended to join protected networks to ensure they are secure, this is by far not their only concern. The convenience of easily connecting to a Wi-Fi hotspot has left security holes wide open for attackers to abuse. This stresses the concern about the lack of security on the client side of Wi-Fi capable technologies. The Wi-Fi communications security has been a concern since it was first deployed. On one hand protocols like WPA2 have greatly increased the security of the communications between clients and access points, but how can one know if the access point is legitimate in the first place? Nowadays, with the help of open-source software and the great amount of free information it is easily possible for a malicious actor to create a Wi-Fi network with the purpose of attracting Wi-Fi users and tricking them into connecting to a illegitimate Wi-Fi access point. The risk of this vulnerability becomes clear when studying client side behaviour in Wi-Fi communications where these actively seek out to access points in order to connect to them automatically. In many situations they do this even if there is no way of verifying the legitimacy of the access point they are connecting to. Attacks on the Wi-Fi client side have been known for over a decade but there still aren’t any effective ways to properly protect users from falling victims to these. Based on the presented issues there is a clear need in both, securing the Wi-Fi client side communications as well as raising awareness of the Wi-Fi technologies everyday users about the risks they are constantly facing when using them. The main contribution from this project will be a Wi-Fi vulnerability analysis and exploitation framework. The framework will focus on client-side vulnerabilities but also on extensibility for any type of Wi-Fi attack. The tool is intended to be used by auditors (penetration testers - pentesters) when performing intrusion tests on Wi-Fi networks. It also serves as a proof-of-concept tool meant to teach and raise awareness about the risks involved when using Wi-Fi technologies.Actualmente existem inúmeros pontos de acesso Wi-Fi. Apesar dos utilizadores serem sempre recomendados a utilizar redes protegidas, esta não é a única preocupação que devem ter. A conveniência de nos ligarmos facilmente a um ponto de acesso deixou grandes falhas de segurança em aberto para atacantes explorarem. Isto acentua a preocupação em relação à carência de segurança do lado cliente em tecnologias Wi-Fi. A segurança nas comunicações Wi-Fi foi uma preocupação desde os dias em que esta tecnologia foi primeiramente lançada. Por um lado, protocolos como o WPA2 aumentaram consideravelmente a segurança das comunicações Wi-Fi entre os pontos de acesso e os seus clientes, mas como saber, em primeiro lugar, se o ponto de acesso é legítimo? Hoje em dia, com a ajuda de software de código aberto e a imensa quantidade de informação gratuita, é fácil para um atacante criar uma rede Wi-Fi falsa com o objetivo de atrair clientes. O risco desta vulnerabilidade torna-se óbvio ao estudar o comportamento do lado do cliente Wi-Fi. O cliente procura activamente redes conhecidas de forma a ligar-se automaticamente a estas. Em muitos casos os clientes ligam-se sem interação do utilizador mesmo em situações em que a legitimidade do ponto de acesso não é verificável. Ataques ao lado cliente das tecnologias Wi-Fi já foram descobertos há mais de uma década, porém continuam a não existirem formas eficazes de proteger os clientes deste tipo de ataques. Com base nos problemas apresentados existe uma necessidade clara de proteger o lado cliente das comunicações Wi-Fi e ao mesmo tempo sensibilizar e educar os utilizadores de tecnologias Wi-Fi dos perigos que advêm da utilização destas tecnologias. A contribuição mais relevante deste projeto será a publicação de uma ferramenta para análise de vulnerabilidades e ataques em comunicações WiFi. A ferramenta irá focar-se em ataques ao cliente mas permitirá extensibilidade de funcionalidades de forma a possibilitar a implementação de qualquer tipo de ataques sobre Wi-Fi. A ferramenta deverá ser utilizada por auditores de segurança durante testes de intrusão Wi-Fi. Tem também como objetivo ser uma ferramenta educacional e de prova de conceitos de forma a sensibilizar os utilizadores das tecnologias Wi-Fi em relação aos riscos e falhas de segurança destas