Addressing the challenges of modern DNS a comprehensive tutorial

Domain Name Systems (DNS) play a vital role in the proper functioning of the internet Almost all internet applications rely on DNS for the name resolutions. The existing DNS infrastructure has a number of security vulnerabilities and it is prone to attacks such as DNS Cache Poisoning attack, DNS Rebinding attack. Flooding attack, etc. If a DNS server is compromised, it affects all the users of the internet, resulting in adverse effect In this paper the focus has been on the prevention of DNS Rebinding attack. The solution for detecting and preventing DNS rebinding attack has been incorporated into DEEP A1. The extended DEEPA, viz., DEEPAV2 tool, containing the enhanced packet analyzer, the traffic differentiator, and enhanced packet filter modules, detects and differentiates the abnormal group of activities in the DNS traffic caused by the public IP DNS rebinding attack which is the combination of classical DNS rebinding attack and Anti-DNS pinning attack. The DEEPAV2 effectively filters the DNS rebinding attack packets by deeply analyzing the DNS packets. As the DNS rebinding attack is prevented, the subsequent attacks such as pharming, phishing, click frauds, email spamming, etc., could be prevented.

A deep dive into DNS behavior and query failures

The Domain Name System (DNS) is widely seen as a vital protocol of the modern Internet. For example, popular services like load balancers and Content Delivery Networks heavily rely on DNS. Because of its important role, DNS is also a desirable target for malicious activities such as spamming, phishing, and botnets. To protect networks against these attacks, a number of DNS-based security approaches have been proposed. The key insight of our study is to measure the effectiveness of security approaches that rely on DNS in large-scale networks. For this purpose, we answer the following questions, How often is DNS used? Are most of the Internet flows established after contacting DNS? In this study, we collected data from the University of Auckland campus network with more than 33,000 Internet users and processed it to find out how DNS is being used. Moreover, we studied the flows that were established with and without contacting DNS. Our results show that less than 5 percent of the observed flows use DNS. Therefore, we argue that those security approaches that solely depend on DNS are not sufficient to protect large-scale networks.

Visualizing and characterizing DNS lookup behaviors via log-mining

The Domain Name System (DNS) protocol essentially translates domain names to IP addresses, enabling browsers to load and utilize Internet resources. Despite its major role, DNS is vulnerable to various security loopholes that attackers have continually abused. Therefore, delivering secure DNS traffic has become challenging since attackers use advanced and fast malicious information-stealing approaches. To overcome DNS vulnerabilities, the DNS over HTTPS (DoH) protocol was introduced to improve the security of the DNS protocol by encrypting the DNS traffic and communicating it over a covert network channel. This paper proposes a lightweight, double-stage scheme to identify malicious DoH traffic using a hybrid learning approach. The system comprises two layers. At the first layer, the traffic is examined using random fine trees (RF) and identified as DoH traffic or non-DoH traffic. At the second layer, the DoH traffic is further investigated using Adaboost trees (ADT) and identified as benign DoH or malicious DoH. Specifically, the proposed system is lightweight since it works with the least number of features (using only six out of thirty-three features) selected using principal component analysis (PCA) and minimizes the number of samples produced using a random under-sampling (RUS) approach. The experiential evaluation reported a high-performance system with a predictive accuracy of 99.4% and 100% and a predictive overhead of 0.83 µs and 2.27 µs for layer one and layer two, respectively. Hence, the reported results are superior and surpass existing models, given that our proposed model uses only 18% of the feature set and 17% of the sample set, distributed in balanced classes.

The Domain Name System (DNS) is the backbone of the internet. It is a distributed hierarchical database which stores resource records like A, MX, AAAA, CNAME. The whole DNS is classified into three layers - root, top-level domain (TLD) and authoritative DNS servers. Each level has its own responsibility to resolve certain categories of domain names. It is very difficult for us to memorize the IP address of each site which we need to visit. In this case, the DNS comes into rescue to figure out the corresponding IP address a domain points to. In the current world, the internet is an inevitable part of our life and DNS is the soul of the internet. Due to this reason, DNS is a major attack target like amplification attack, cache poisoning attack, DNS hijacking, NXDomain attack and Phantom domain attack. These attacks could create a serious security threat to internet users. Threats can be a simple redirection to potentially stealing user credentials. Even though different mitigation techniques are available, the threat still exists. In this paper, we present our survey of the existing research and its shortcomings on securing the DNS. We have also introduced a novel idea which uses blockchain technology to validate the response sent by the DNS servers.

The Domain Name System (DNS) is a critical Internet infrastructure that provides name to address mapping services. In the past few years, distributed denial of service (DDoS) attacks have targeted the DNS infrastructure and threaten to disrupt this critical service. In this paper we show that the existing DNS can gain significant resilience against DDoS attacks through a simple change to the current DNS operations, by setting longer time-to-live values for a special class of DNS resource records, the infrastructure records. These records are used to navigate the DNS hierarchy and change infrequently. Furthermore, in combination with a set of simple and incrementally deployable record renewal policies, the DNS service availability can be improved by one order of magnitude. Our approach requires neither additional physical resources nor any change to the existing DNS design. We evaluate the effectiveness of our proposed enhancement by using DNS traces collected from multiple locations.

The Domain Name System (DNS) is an essential part of the Internet on whose function many other protocols rely. One key DNS function is Dynamic Update, which allows hosts on the network to make updates to DNS records dynamically, without the need for restarting the DNS service. Unfortunately, this dynamic process does expose DNS servers to security issues. To address these issues two protocols were introduced: Transaction Signature (TSIG) and Domain Name System Security Extensions (DNSSEC). In Internet Protocol version 4 (IPv4) networks using these protocols eliminated security issues. In Internet Protocol version 6 (IPv6) however, there is an issue with the DNS authentication process when using the Stateless Address Auto Configuration (SLAAC) mechanism (new to IPv6, nonexistent in IPv4). This authentication issue occurs when a node wants to update its resource records on a DNS server, during the DNS update process, or when a client wants to authenticate a DNS resolver to ensure that the DNS response does not contain a spoofed source address or message. In this paper we propose the use of a new mechanism which makes use of asymmetric cryptography to establish a trust relationship with the DNS server. We also consider the use of the current security parameters used to generate IPv6 addresses in a secure manner, i.e. Secure Neighbor Discovery (SeND), for assuring clients and DNS servers that the one they are communicating with is the real owner of this IP address. Since we are extending the RDATA field within the TSIG protocol to accommodate these new security parameters, we will call this new mechanism the CGA-TSIG algorithm.

The domain name system (DNS) is a cornerstone for the Internet and the most globally deployed Internet service that provides user-friendly naming for Internet hosts. DNS is a distributed data base that allows convenient storing and retrieving of resource records. Recently an interesting feature was added to BIND implementation of the DNS system to support secure dynamic updates. In this paper, we use the DNS and its ability to support dynamic updates to propose a mobility solution that locates and tracks mobile hosts while they change there points of attachment (IP addresses) in the network. The main objectives of this paper is to study and re-evaluate the DNS system with respect to dynamic updating protocol and provide a performance study to determine the ability of the DNS to support mobility and real time services. The experimental results have shown that updating speeds (i.e. propagation of updates along the system) are fast enough for the DNS to provide real time services, and we can conclude that the conventional DNS system with the dynamic updating feature can be used in a macro mobility handling scheme.

The Domain Name System (DNS) is a necessary component of the Internet that allows hosts on the Internet to communicate with other hosts without needing to know their cryptic IP addresses. When this protocol was first introduced it did not contain robust security features because scalability was an issue. One of the useful features added to DNS was the DNS update mechanism that allowed other hosts to dynamically change DNS entries. This feature, though, exposed new vulnerabilities to DNS servers which necessitated the implementation of new security protocols. Some of the security protocols introduced to address these issues were Transaction SIGnature (TSIG) and DNS Security Extension (DNSSEC). Although, in IPv4, these mechanisms did resolve most of the security issues dealing with authentication between a node and a DNS server, they are not viable in IPv6 networks. This is because the Neighbor Discovery Protocol (NDP) introduced to organize the large IPv6 address space automatically does not support DNS authentication or have an option for secure DNS updating. In this chapter, the authors first explain the common approaches used in IPv4 to address these security issues. Then they explain the differences between the use of these approaches in IPv4 and IPv6, where the focus is on new research with regard to authentication mechanisms between hosts and DNS servers.

Domain Name System (DNS) is one of the most important services of the Internet since most communications normally begin with domain name resolutions provided by DNS. However, DNS has vulnerability against some kind of attacks such as DNS spoofing, DNS cache poisoning, and so on. DNSSEC is an security extension of DNS to provide secure name resolution services by using digital signature based on public key cryptography. However, there are several problems with DNSSEC such as failing resolution in case of validation failure, increasing the load of DNS full resolver, and so on. To mitigate these problems, we proposed a Client Based DNSSEC Validation System. This system performs DNSSEC validation on the client, and in case of validation failure, it forwards the failed response and alerts the user to the fact. However, this system has a problem that it inactivates the cache function of validation library so that it always performs DNSSEC validation even for the same query. In this paper, we report how to solve this problem by multithreading of DNSSEC validation system.

DNS(Domain Name System)는 인터넷상의 호스트의 도메인주소를 IP주소로 변환하거나 IP주소를 도메인주소로 변환하는 이름해결 메카니즘을 총칭한다. 본 논문에서는 1차 DNS 서버가 오류로 인해 정지하더라도 2차 DNS 서버가 대신하여 서비스를 지속할 수 있도록 하는 결함내성을 갖는 DNS 시스템 구축에 관해 연구하였다. DNS(Domain Name System) is the Name Resolution Mechanism that makes conversion from a Domain Name of a computer on the Internet to an IP Address or the reverse conversion. In this paper we researched on the Foundation techniques of Fault-tolerant DNS Servers that the secondary DNS can take over and provide continuous services even though primary DNS stops due to some critical errors.

Securing the internet’s backbone: A blockchain-based and incentive-driven architecture for DNS cache poisoning defense

Domain Name System (DNS) is one of the pillars of today's Internet. Due to its appealing properties such as low data volume, wide-ranging applications and encryption free, DNS traffic has been extensively utilized for network monitoring. Most existing studies of DNS traffic, however, focus on domain name reputation. Little attention has been paid to understanding and profiling what people are doing from DNS traffic, a fundamental problem in the areas including Internet demographics and network behavior analysis. Consequently, simple questions like “How to determine whether a DNS query for www.google.com means searching or any other behaviors?” cannot be answered by existing studies. In this paper, we take the first step to identify user activities from raw DNS queries. We advance a multiscale hierarchical framework to tackle two practical challenges, i.e., behavior ambiguity and behavior polymorphism. Under this framework, a series of novel methods, such as pattern upward mapping and multi-scale random forest classifier, are proposed to characterize and identify user activities of interest. Evaluation using both synthetic and real-world DNS traces demonstrates the effectiveness of our method.

Domain Name System (DNS) is an essential component in internet infrastructure to direct domains to IP addresses or conversely. Despite its important role in delivering internet services, attackers often use DNS as a bridge to breach a system. A DNS traffic analysis system is needed for early detection of attacks. However, the available security tools still have many shortcomings, for example broken authentication, sensitive data exposure, injection, etc. This research uses DNS analysis to develop anomaly-based techniques to detect malicious traffic on the DNS infrastructure. To do this, We look for network features that characterize DNS traffic. Features obtained will then be processed using the Decision Tree algorithm to classifyincoming DNS traffic. We experimented with 2.291.024 data traffic data matches the characteristics of BotNet and normal traffic. By dividing the data into 80% training and 20% testing data, our experimental results showed high detection aacuracy (96.36%) indicating the robustness of our method.