On Application Layer DDoS Attack Detection in High-Speed Encrypted Networks

Application-layer denial-of-service attacks have become a serious threat to modern high-speed computer networks and systems. Unlike network-layer attacks, application-layer attacks can be performed by using legitimate requests from legitimately connected network machines which makes these attacks undetectable for signature-based intrusion detection systems. Moreover, the attacks may utilize protocols that encrypt the data of network connections in the application layer making it even harder to detect attacker’s activity without decrypting users network traffic and violating their privacy. In this paper, we present a method which allows us to timely detect various applicationlayer attacks against a computer network. We focus on detection of the attacks that utilize encrypted protocols by applying an anomaly-detection-based approach to statistics extracted from network packets. Since network traffic decryption can violate ethical norms and regulations on privacy, the detection method proposed analyzes network traffic without decryption. The method involves construction of a model of normal user behavior by analyzing conversations between a server and clients. The algorithm is self-adaptive and allows one to update the model every time when a new portion of network traffic data is available. Once the model has been built, it can be applied to detect various types of application-layer denial-of- service attacks. The proposed technique is evaluated with realistic end user network traffic generated in our virtual network environment. Evaluation results show that these attacks can be properly detected, while the number of false alarms remains very low

Denial-of-service attack modelling and detection for HTTP/2 services

Businesses and society alike have been heavily dependent on Internet-based services, albeit with experiences of constant and annoying disruptions caused by the adversary class. A malicious attack that can prevent establishment of Internet connections to web servers, initiated from legitimate client machines, is termed as a Denial of Service (DoS) attack; volume and intensity of which is rapidly growing thanks to the readily available attack tools and the ever-increasing network bandwidths. A majority of contemporary web servers are built on the HTTP/1.1 communication protocol. As a consequence, all literature found on DoS attack modelling and appertaining detection techniques, addresses only HTTP/1.x network traffic. This thesis presents a model of DoS attack traffic against servers employing the new communication protocol, namely HTTP/2. The HTTP/2 protocol significantly differs from its predecessor and introduces new messaging formats and data exchange mechanisms. This creates an urgent need to understand how malicious attacks including Denial of Service, can be launched against HTTP/2 services. Moreover, the ability of attackers to vary the network traffic models to stealthy affects web services, thereby requires extensive research and modelling. This research work not only provides a novel model for DoS attacks against HTTP/2 services, but also provides a model of stealthy variants of such attacks, that can disrupt routine web services. Specifically, HTTP/2 traffic patterns that consume computing resources of a server, such as CPU utilisation and memory consumption, were thoroughly explored and examined. The study presents four HTTP/2 attack models. The first being a flooding-based attack model, the second being a distributed model, the third and fourth are variant DoS attack models. The attack traffic analysis conducted in this study employed four machine learning techniques, namely Naïve Bayes, Decision Tree, JRip and Support Vector Machines. The HTTP/2 normal traffic model portrays online activities of human users. The model thus formulated was employed to also generate flash-crowd traffic, i.e. a large volume of normal traffic that incapacitates a web server, similar in fashion to a DoS attack, albeit with non-malicious intent. Flash-crowd traffic generated based on the defined model was used to populate the dataset of legitimate network traffic, to fuzz the machine learning-based attack detection process. The two variants of DoS attack traffic differed in terms of the traffic intensities and the inter-packet arrival delays introduced to better analyse the type and quality of DoS attacks that can be launched against HTTP/2 services. A detailed analysis of HTTP/2 features is also presented to rank relevant network traffic features for all four traffic models presented. These features were ranked based on legitimate as well as attack traffic observations conducted in this study. The study shows that machine learning-based analysis yields better classification performance, i.e. lower percentage of incorrectly classified instances, when the proposed HTTP/2 features are employed compared to when HTTP/1.1 features alone are used. The study shows how HTTP/2 DoS attack can be modelled, and how future work can extend the proposed model to create variant attack traffic models that can bypass intrusion-detection systems. Likewise, as the Internet traffic and the heterogeneity of Internet-connected devices are projected to increase significantly, legitimate traffic can yield varying traffic patterns, demanding further analysis. The significance of having current legitimate traffic datasets, together with the scope to extend the DoS attack models presented herewith, suggest that research in the DoS attack analysis and detection area will benefit from the work presented in this thesis

Improvement of DDoS attack detection and web access anonymity

The thesis has covered a range of algorithms that help to improve the security of web services. The research focused on the problems of DDoS attack and traffic analysis attack against service availability and information privacy respectively. Finally, this research significantly advantaged DDoS attack detection and web access anonymity.<br /

Cloud Computing: Challenges And Risk Management Framework

Cloud-computing technology has developed rapidly. It can be found in a wide range of social, business and computing applications. Cloud computing would change the Internet into a new computing and collaborative platform. It is a business model that achieves purchase ondemand and pay-per-use in network. Many competitors, organizations and companies in the industry have jumped into cloud computing and implemented it. Cloud computing provides us with things such as convenience, reduced cost and high scalability. But despite all of these advantages, there are many enterprises, individual users and organizations that still have not deployed this innovative technology. Several reasons lead to this problem; however, the main concerns are related to security, privacy and trust. Low trust between users and cloud computing providers has been found in the literature

Cyber Security

This open access book constitutes the refereed proceedings of the 16th International Annual Conference on Cyber Security, CNCERT 2020, held in Beijing, China, in August 2020. The 17 papers presented were carefully reviewed and selected from 58 submissions. The papers are organized according to the following topical sections: access control; cryptography; denial-of-service attacks; hardware security implementation; intrusion/anomaly detection and malware mitigation; social network security and privacy; systems security

Packet filter performance monitor (anti-DDOS algorithm for hybrid topologies)

DDoS attacks are increasingly becoming a major problem. According to Arbor Networks, the largest DDoS attack reported by a respondent in 2015 was 500 Gbps. Hacker News stated that the largest DDoS attack as of March 2016 was over 600 Gbps, and the attack targeted the entire BBC website. With this increasing frequency and threat, and the average DDoS attack duration at about 16 hours, we know for certain that DDoS attacks will not be going away anytime soon. Commercial companies are not effectively providing mitigation techniques against these attacks, considering that major corporations face the same challenges. Current security appliances are not strong enough to handle the overwhelming traffic that accompanies current DDoS attacks. There is also a limited research on solutions to mitigate DDoS attacks. Therefore, there is a need for a means of mitigating DDoS attacks in order to minimize downtime. One possible solution is for organizations to implement their own architectures that are meant to mitigate DDoS attacks. In this dissertation, we present and implement an architecture that utilizes an activity monitor to change the states of firewalls based on their performance in a hybrid network. Both firewalls are connected inline. The monitor is mirrored to monitor the firewall states. The monitor reroutes traffic when one of the firewalls become overwhelmed due to a HTTP DDoS flooding attack. The monitor connects to the API of both firewalls. The communication between the rewalls and monitor is encrypted using AES, based on PyCrypto Python implementation. This dissertation is structured in three parts. The first found the weakness of the hardware firewall and determined its threshold based on spike and endurance tests. This was achieved by flooding the hardware firewall with HTTP packets until the firewall became overwhelmed and unresponsive. The second part implements the same test as the first, but targeted towards the virtual firewall. The same parameters, test factors, and determinants were used; however a different load tester was utilized. The final part was the implementation and design of the firewall performance monitor. The main goal of the dissertation is to minimize downtime when network firewalls are overwhelmed as a result of a DDoS attack

Network Security Concepts, Dangers, and Defense Best Practical

In today's highly interconnected world, network security has become a critical aspect of protecting organizations from cyber-attacks. The increasing sophistication of attackers and their ability to exploit software and firmware vulnerabilities pose significant dangers to the security of networks. However, many organizations often neglect the essential steps required to secure their networks, leading to an increased risk of security breaches. In this research article, we aim to address this issue by investigating network security concepts, potential dangers, and practical defense strategies. We begin by exploring the different types of cyber-attacks and their sources, highlighting the various ways attackers exploit network vulnerabilities. We also examine the reasons why organizations often overlook network security and the consequences of not prioritizing it. To better understand the complexity of network security, we categorize the different security concerns using the CIA (confidentiality, integrity, and availability) triangle. This approach allows us to identify the various areas of vulnerability and their potential impact on network security. Next, we focus on the most crucial basic concepts and steps involved in various network security operations. We outline the best practices and practical approaches organizations can take to improve their network security, including implementing security policies and procedures, using encryption and authentication methods, and conducting regular security assessments. By highlighting the importance of network security and providing practical guidance on how organizations can defend against cyber-attacks, we hope to raise awareness and help prevent security breaches. Keywords: Network, Internet, Security, Security Threats, IP Address, Network Attack, Attackers DOI: 10.7176/CEIS/14-2-03 Publication date:March 31st 202

A Study on Security Attributes of Software-Defined Wide Area Network

For organizations to communicate important data across various branches, a reliable Wide Area Network (WAN) is important. With the increase of several factors such as usage of cloud services, WAN bandwidth demand, cost of leased lines, complexity in building/managing WAN and changing business needs led to need of next generation WAN. Software-defined wide area network (SD- WAN) is an emerging trend in today’s networking world as it simplifies management of network and provides seamless integration with the cloud. Compared to Multiprotocol Label Switching (MPLS) majorly used in traditional WAN architecture, SD-WAN incurs less cost, highly secure and offers great performance. This paper will mainly focus to investigate this next-generation WAN’s security attributes as security plays a crucial role in SD-WAN implementation. The goal of the paper is to analyze SD-WAN security by applying principles of CIA triad principle. Comparison of SD-WAN products offered by three different vendors in SD-WAN market with respect to its security is another important area that will be covered in this paper