Adaptive Response System for Distributed Denial-of-Service Attacks

The continued prevalence and severe damaging effects of the Distributed Denial of Service (DDoS) attacks in today’s Internet raise growing security concerns and call for an immediate response to come up with better solutions to tackle DDoS attacks. The current DDoS prevention mechanisms are usually inflexible and determined attackers with knowledge of these mechanisms, could work around them. Most existing detection and response mechanisms are standalone systems which do not rely on adaptive updates to mitigate attacks. As different responses vary in their “leniency” in treating detected attack traffic, there is a need for an Adaptive Response System. We designed and implemented our DDoS Adaptive ResponsE (DARE) System, which is a distributed DDoS mitigation system capable of executing appropriate detection and mitigation responses automatically and adaptively according to the attacks. It supports easy integrations for both signature-based and anomaly-based detection modules. Additionally, the design of DARE’s individual components takes into consideration the strengths and weaknesses of existing defence mechanisms, and the characteristics and possible future mutations of DDoS attacks. These components consist of an Enhanced TCP SYN Attack Detector and Bloom-based Filter, a DDoS Flooding Attack Detector and Flow Identifier, and a Non Intrusive IP Traceback mechanism. The components work together interactively to adapt the detections and responses in accordance to the attack types. Experiments conducted on DARE show that the attack detection and mitigation are successfully completed within seconds, with about 60% to 86% of the attack traffic being dropped, while availability for legitimate and new legitimate requests is maintained. DARE is able to detect and trigger appropriate responses in accordance to the attacks being launched with high accuracy, effectiveness and efficiency. We also designed and implemented a Traffic Redirection Attack Protection System (TRAPS), a stand-alone DDoS attack detection and mitigation system for IPv6 networks. In TRAPS, the victim under attack verifies the authenticity of the source by performing virtual relocations to differentiate the legitimate traffic from the attack traffic. TRAPS requires minimal deployment effort and does not require modifications to the Internet infrastructure due to its incorporation of the Mobile IPv6 protocol. Experiments to test the feasibility of TRAPS were carried out in a testbed environment to verify that it would work with the existing Mobile IPv6 implementation. It was observed that the operations of each module were functioning correctly and TRAPS was able to successfully mitigate an attack launched with spoofed source IP addresses

A critical review of cyber-physical security for building automation systems

Modern Building Automation Systems (BASs), as the brain that enables the smartness of a smart building, often require increased connectivity both among system components as well as with outside entities, such as optimized automation via outsourced cloud analytics and increased building-grid integrations. However, increased connectivity and accessibility come with increased cyber security threats. BASs were historically developed as closed environments with limited cyber-security considerations. As a result, BASs in many buildings are vulnerable to cyber-attacks that may cause adverse consequences, such as occupant discomfort, excessive energy usage, and unexpected equipment downtime. Therefore, there is a strong need to advance the state-of-the-art in cyber-physical security for BASs and provide practical solutions for attack mitigation in buildings. However, an inclusive and systematic review of BAS vulnerabilities, potential cyber-attacks with impact assessment, detection & defense approaches, and cyber-secure resilient control strategies is currently lacking in the literature. This review paper fills the gap by providing a comprehensive up-to-date review of cyber-physical security for BASs at three levels in commercial buildings: management level, automation level, and field level. The general BASs vulnerabilities and protocol-specific vulnerabilities for the four dominant BAS protocols are reviewed, followed by a discussion on four attack targets and seven potential attack scenarios. The impact of cyber-attacks on BASs is summarized as signal corruption, signal delaying, and signal blocking. The typical cyber-attack detection and defense approaches are identified at the three levels. Cyber-secure resilient control strategies for BASs under attack are categorized into passive and active resilient control schemes. Open challenges and future opportunities are finally discussed.Comment: 38 pages, 7 figures, 6 tables, submitted to Annual Reviews in Contro

Dyn DDoS Cyberattack: A Position Paper

The strategy adopted in the Dyn distributed denial of service (DDoS) attack remains a purported accentuation to classify it as a recent state-of-the-art DDoS even though it took place in 2016. It was one of the biggest DDoS ever launched and affected the availability of essential internet services. In exploiting vulnerabilities, the attack exposed the insecurity that surrounds some IoT devices. It helps experts in further deployment of detection techniques and countermeasures strategy. In this paper, a multi-stakeholder approach to mitigating against such attacks explored by critically analyse and reflect on the Dyn DDoS attack and hacking techniques. A discussion on possible countermeasures followed to suggest hybrid solutions by multiple different organisations to provide a secured solution to the internet against similar attacks

On The Impact of Internet Naming Evolution: Deployment, Performance, and Security Implications

As one of the most critical components of the Internet, the Domain Name System (DNS) provides naming services for Internet users, who rely on DNS to perform the translation between the domain names and network entities before establishing an In- ternet connection. In this dissertation, we present our studies on different aspects of the naming infrastructure in today’s Internet, including DNS itself and the network services based on the naming infrastructure such as Content Delivery Networks (CDNs). We first characterize the evolution and features of the DNS resolution in web ser- vices under the emergence of third-party hosting services and cloud platforms. at the bottom level of the DNS hierarchy, the authoritative DNS servers (ADNSes) maintain the actual mapping records and answer the DNS queries. The increasing use of upstream ADNS services (i.e., third-party ADNS-hosting services) and Infrastructure-as-a-Service (IaaS) clouds facilitates the deployment of web services, and has been fostering the evo- lution of the deployment of ADNS servers. to shed light on this trend, we conduct a large-scale measurement to investigate the ADNS deployment patterns of modern web services and examine the characteristics of different deployment styles, such as perfor- mance, life-cycle of servers, and availability. Furthermore, we specifically focus on the DNS deployment for subdomains hosted in IaaS clouds. Then, we examine a pervasive misuse of DNS names and explore a straightforward solution to mitigate the performance penalty in DNS cache. DNS cache plays a critical role in domain name resolution, providing (1) high scalability at Root and Top-level- domain nameservers with reduced workloads and (2) low response latency to clients when the resource records of the queried domains are cached. However, the pervasive misuses of domain names, e.g., the domain names of “one-time-use” pattern, have negative impact on the effectiveness of DNS caching as the cache has been filled with those entries that are highly unlikely to be retrieved. By leveraging the domain name based features that are explicitly available from a domain name itself, we propose simple policies for improving DNS cache performance and validate their efficacy using real traces. Finally, we investigate the security implications of a fundamental vulnerability in DNS- based CDNs. The success of CDNs relies on the mapping system that leverages the dynamically generated DNS records to distribute a client’s request to a proximal server for achieving optimal content delivery. However, the mapping system is vulnerable to malicious hijacks, as it is very difficult to provide pre-computed DNSSEC signatures for dynamically generated records in CDNs. We illustrate that an adversary can deliberately tamper with the resolvers to hijack CDN’s redirection by injecting crafted but legitimate mappings between end-users and edge servers, while remaining undetectable by exist- ing security practices, which can cause serious threats that nullify the benefits offered by CDNs, such as proximal access, load balancing, and DoS protection. We further demonstrate that DNSSEC is ineffective to address this problem, even with the newly adopted ECDSA that is capable of achieving live signing for dynamically generated DNS records. We then discuss countermeasures against this redirection hijacking

Engineering Self-Adaptive Applications on Software Defined Infrastructure

Cloud computing is a flexible platform that offers faster innovation, elastic resources, and economies of scale. However, it is challenging to ensure non-functional properties such as performance, cost and security of applications hosted in cloud. Applications should be adaptive to the fluctuating workload to meet the desired performance goals, in one hand, and on the other, operate in an economic manner to reduce the operational cost. Moreover, cloud applications are attractive target of security threats such as distributed denial of service attacks that target the availability of applications and increase the cost. Given such circumstances, it is vital to engineer applications that are able to self-adapt to such volatile conditions. In this thesis, we investigate techniques and mechanisms to engineer model-based application autonomic management systems that strive to meet performance, cost and security objectives of software systems running in cloud. In addition to using the elasticity feature of cloud, our proposed autonomic management systems employ run-time network adaptations using the emerging software defined networking and network function virtualization. We propose a novel approach to self-protecting applications where the application traffic is dynamically managed between public and private cloud depending on the condition of the traffic. Our management approach is able to adapt the bandwidth rates of application traffic to meet performance and cost objectives. Through run-time performance models as well as optimization, the management system maximizes the profit each time the application requires to adapt. Our autonomous management solutions are implemented and evaluated analytically as well as on multiple public and community clouds to demonstrate their applicability and effectiveness in real world environment