Client-side Attacks Research Articles

Uncovering Cybersecurity Vulnerabilities: A Kali Linux Investigative Exploration Perspective

Abstract This research exploration presents a comprehensive methodology for conducting penetration testing for networking security protocols and vulnerabilities on the Wi-Fi networks using Kali Linux, an open-source penetration testing platform. The methodology also encompasses four main stages which are Preparation, Information Gathering, Simulated Attack, Reporting. In the Preparation Stage, the scope of the penetration test is defined, authorization is obtained, and within the testing environment the experimentation is prepared. The Information Gathering Stage involves scanning for associated nearby wireless access points (APs), identifying encryption modes, and assessing network coverage. The Simulated Attack Phase verifies the types of vulnerabilities through password cracking, infrastructure penetration tests, and client-side attacks. Finally, the Reporting Phase entails compiling of a very detailed test report with results visualized, findings and recommendations with directions. Experimental results validate the overall effectiveness of the methodology in identifying and mitigating Wi-Fi network vulnerabilities. Through systematic testing and analysis, Kali Linux facilitates proactive security measures to enhance Wi-Fi network defenses.

Malicious URL Detection Using Machine Learning

Throughout the years, internet usage has grown significantly. The internet continues to transform how we interact with people, organise the flow of goods, and communicate knowledge all across the world. The attackers have used this popularity to their advantage to participate in illegal activities that would lead to monetary advantage. There has been a rise in malicious websites that launch client-side attacks over time, which cannot be identified effectively by existing approaches such as blacklisting. As a result, an efficient solution to detect these malicious websites is required. In this study, we used the random forest method to develop a machine learning model while integrating lexical features, hostbased features, and content-based features. The model has an accuracy of 94.7%

A Robust Multi-Stage Power Consumption Prediction Method in a Semi-Decentralized Network of Electric Vehicles

A Virtual Power Plant (VPP) balances the load on a power grid by allocating power generated by various interconnected units during periods of peak demand. In addition, demand-side energy devices such as Electric Vehicles (EVs) and mobile robots can also balance energy supply and demand when effectively deployed. However, the fluctuation of energy generated by renewable resources makes balancing energy supply a challenging goal. This paper proposes a semi-decentralized robust network of electric vehicles (NoEV) integration system for power management in a smart grid platform. The proposed approach integrates an aggregator with EV fleets into a blockchain framework. The EVs execute a multi-stage algorithm to predict the power consumption based on a novel federated learning algorithm named Federated Learning for Qualified Local Model Selection (FL-QLMS). From the evaluation results, the proposed system requires 35% fewer transactions in short intervals and propagation delays than the previous approaches and achieves better network efficiency while maintaining a high level of security. Moreover, NoEV achieves a 5.7% lower root mean square error (RMSE) than the conventional approach for power consumption prediction, which is a significant improvement. In addition, the FL-QLMS approach outperforms state-of-the-art methods in terms of robustness to client-side attacks. The evaluation results also show that the performance of FL-QLMS is not affected when 10% to 40% percent of the models are manipulated.

A Secure Methodology to Detect and Prevent Ddos and Sql Injection Attacks

As most of the applications host on cloud, Security is a major concern for the data owners. The cloud environment has to be secure and protect data owner data from cloud attacks. In this project work, we study about securing firewall against client side attacks namely Denial of firewall and SQL injection attacks. Denial of firewall is nothing but overloading the firewall by bursting n number of requests through vulnerable scripts. SQL injection attack is defined as bypassing the security protocols by malicious scripts. Thus we proposed to design and develop a web application to detect and prevent denial of firewall and SQL injection attacks.
 The denial of firewall attack can be performed using Java environment based servers and prevention can be performed using Digital Signature Algorithm (DSA) in which filter based approach and software puzzle based approach are performed to detect the malicious script based requests. Once the Deep Packet Inspection (DPI): filter based approach and software puzzle based approach are find satisfactory only the request would be processed. If the request is find malicious automatically the requested IP address would be blocked. Various type of SQL injection attacks namely SQL login bypass, Blind injection, SQL sleep attack, Data fetching attack are analysed and performed. The SQL injection attack can be prevented using PREPARE statements. This statements are created to make the SQL queries more efficient and render security benefits. This statement provides effective prevention mechanism against SQL injection attacks. Thus our proposed solution, provides high security against firewall attacks namely denial of firewall and SQL injection securing the data owner files and preventing compromising of firewall

Detection of Malicious Servers for Preventing Client-Side Attacks

The number of client-side attacks is increasing day-by-day. These attacks are launched by using various methods like phishing, drive-by downloads, click-frauds, social engineering, scareware, and ransomware. To get more advantage with less exertion and time, the attackers are focus on the clients, rather than servers which are more secured as compared to the clients. This makes clients as an easy target for the attackers on the Internet. A number of systems/tools have been created by the security community with various functions for detection of client-side attacks. The discovery of malicious servers that launch the client side attacks can be characterized in two types. First to detect malicious servers with passive detection which is often signature based. Second to detect the malicious servers with active detection often with dynamic malware analysis. Current systems or tools have more focus on identifying malicious servers rather than preventing the clients from those malicious servers. In this paper, we have proposed a solution for the detection and prevention of malicious servers that use the Bro Intrusion Detection System (IDS) and VirusTotal API 2.0. The detected malicious link is then blocked at the gateway.

DOM based Cross Site Scripting - Client-Side Attacks on Browsers

DOM based Cross Site Scripting - Client-Side Attacks on Browsers

MiGuard : Detecting and Guarding against Malicious Iframe through API Hooking

Recently, client-side attacks through the Microsoft Internet Explorer have increased. In this paper, we present a method to detect and block malware programs resulting from successful malicious iframe attacks. This method can detect malware program execution through distinguishing API sequences of normal execution and abnormal API sequences resulting from an exploit using Win32 API hooks. We implemented MiGuard (Guard against malicious iframes) and performed experiments. The evaluation results indicate that our approach can effectively detect and block malicious iframes. We also believe that our research can help prevent threats of malicious iframes.

Network infiltration with client-side attacks

This article is the first in a 2-part series on the vulnerabilities of networks to client-side attacks, and the risk to networks from 'inside-out' compromises. Internet and computer usage is exponentially increasing; more people are beginning to use the internet as part of their everyday lives, these activities ranging from instant messaging to ordering shopping online. Even most large corporate businesses provide their employees with some kind of access to the internet.

New threats and attacks on the World Wide Web

Ten years ago, very few networks had a firewall; today, they're ubiquitous. The newest target is the workstation: client-side attacks have increased because direct attacks on servers aren't so easy any more. Moreover, as new defenses are raised, information flows are increasingly embedded into Web applications, making them extremely valuable as well, and, thus, the next target. This article describes some of these new threats.