Ashley Chonka

Cloud security defence to protect cloud computing against HTTP-DoS and XML-DoS attacks

Cloud computing is still in its infancy in regards to its software as services (SAS), web services, utility computing and platform as services (PAS). All of these have remained individualized systems that you still need to plug into, even though these systems are heading towards full integration. One of the most serious threats to cloud computing itself comes from HTTP Denial of Service or XML-Based Denial of Service attacks. These types of attacks are simple and easy to implement by the attacker, but to security experts they are twice as difficult to stop. In this paper, we recreate some of the current attacks that attackers may initiate as HTTP and XML. We also offer a solution to traceback through our Cloud TraceBack (CTB) to find the source of these attacks, and introduce the use of a back propagation neutral network, called Cloud Protector, which was trained to detect and filter such attack traffic. Our results show that we were able to detect and filter most of the attack messages and were able to identify the source of the attack within a short period of time.

A Generic Framework for Three-Factor Authentication: Preserving Security and Privacy in Distributed Systems

As part of the security within distributed systems, various services and resources need protection from unauthorized use. Remote authentication is the most commonly used method to determine the identity of a remote client. This paper investigates a systematic approach for authenticating clients by three factors, namely password, smart card, and biometrics. A generic and secure framework is proposed to upgrade two-factor authentication to three-factor authentication. The conversion not only significantly improves the information assurance at low cost but also protects client privacy in distributed systems. In addition, our framework retains several practice-friendly properties of the underlying two-factor authentication, which we believe is of independent interest.

Chaos theory based detection against network mimicking DDoS attacks

DDoS attack traffic is difficult to differentiate from legitimate network traffic during transit from the attacker, or zombies, to the victim. In this paper, we use the theory of network self-similarity to differentiate DDoS flooding attack traffic from legitimate self-similar traffic in the network. We observed that DDoS traffic causes a strange attractor to develop in the pattern of network traffic. From this observation, we developed a neural network detector trained by our DDoS prediction algorithm. Our preliminary experiments and analysis indicate that our proposed chaotic model can accurately and effectively detect DDoS attack traffic. Our approach has the potential to not only detect attack traffic during transit, but to also filter it.

Detecting and Mitigating HX-DoS Attacks against Cloud Web Services

Cyber-Physical Systems allow for the interaction of the cyber world and physical worlds using as a central service called Cloud Web Services. Cloud Web Services can sit well within three models of Cyber-Physical Systems, Software-as-a-Service (SaaS), Platform-as-a-Service (PaaS), and Infrastructure-as-a-Service (IaaS). With any Cyber-Physical system use Cloud Web Services it inherits a security problem, the HX-DoS attack. HX-DoS attack is a combination of HTTP and XML messages that are intentionally sent to flood and destroy the communication channel of the cloud service provider. The relevance of this research is that TCP/IP flood attacks are a common problem and a lot of research to mitigate them has previously been discussed. But HTTP denial of service and XML denial of service problem has only been addressed in a few papers. In this paper, we get closer to closing this gap on this problem with our new defence system called Pre-Decision, Advance Decision, Learning System (ENDER). In our previous experiments using our Cloud Protector, we were successful at detecting and mitigate 91% with a 9% false positive of HX-DoS attack traffic. In this paper, ENDER was able to improve upon this result by being trained and tested on the same data, but with a greater result of 99% detection and 1% false positive.

Defending Grid Web Services from XDoS attacks by SOTA

Grid Web Services are still relevantly a new to business systems, and as more systems are being attached to it, any threat to it could bring collapse and huge harm. Some of these potential threats to Grid Web services come in a new form of a new denial of service attack (DoS), called XML Denial of Service or XDOS attacks. Though, as yet, there have not been any reported attacks from the media, we have observed these attacks are actually far less complex to implement than any previous Denial of Service (DoS), but still just as affective. Current security applications for grid web services (WS-Security for example), based on our observations, and are not up to job of handling the problem. In this paper, we build on our previous work called Service Oriented Traceback Architecture (SOTA), and apply our model to Grid Networks that employ web services. We further introduce a filter defence system, called XDetector, to work in combination with SOTA. Our results show that SOTA in conjunction with XDetector makes for an effective defence against XDoS attacks and upcoming DXDoS.

Detecting and Tracing DDoS Attacks by Intelligent Decision Prototype

Over the last couple of months a large number of distributed denial of service (DDoS) attacks have occurred across the world, especially targeting those who provide Web services. IP traceback, a counter measure against DDoS, is the ability to trace IP packets back to the true source/s of the attack. In this paper, an IP traceback scheme using a machine learning technique called intelligent decision prototype (IDP), is proposed. IDP can be used on both probabilistic packet marking (PPM) and deterministic packet marking (DPM) traceback schemes to identify DDoS attacks. This will greatly reduce the packets that are marked and in effect make the system more efficient and effective at tracing the source of an attack compared with other methods. IDP can be applied to many security systems such as data mining, forensic analysis, intrusion detection systems (IDS) and DDoS defense systems.

Multi-Core Defense System (MSDS) for Protecting Computer Infrastructure against DDoS Attacks

Distributed Denial of Service attacks is one of the most challenging areas to deal with in Security. Not only do security managers have to deal with flood and vulnerability attacks. They also have to consider whether they are from legitimate or malicious attackers. In our previous work we developed a framework called bodyguard, which is to help security software developers from the current serialized paradigm, to a multi-core paradigm. In this paper, we update our research work by moving our bodyguard paradigm, into our new Ubiquitous Multi-Core Framework. From this shift, we show a marked improvement from our previous result of 20% to 110% speedup performance with an average cost of 1.5 ms. We also conducted a second series of experiments, which we trained up Neural Network, and tested it against actual DDoS attack traffic. From these experiments, we were able to achieve an average of 93.36%, of this attack traffic.

Protecting web services with Service Oriented Traceback Architecture

Service oriented architecture (SOA) is a way of reorganizing software infrastructure into a set of service abstracts. In the area of applying SOA to Web service security, there have been some well defined security dimensions. However, current Web security systems, like WS-Security are not efficient enough to handle distributed denial of service (DDoS) attacks. Our new approach, service oriented traceback architecture (SOTA), provides a framework to be able to identify the source of an attack. This is accomplished by deploying our defence system at distributed routers, in order to examine the incoming SOAP messages and place our own SOAP header. By this method, we can then use the new SOAP header information, to traceback through the network the source of the attack. According to our experimental performance evaluations, we find that SOTA is quite scaleable, simple and quite effective at identifying the source.

Multi-classifier Classification of Spam Email on a Ubiquitous Multi-core Architecture

This paper presents an innovative fusion based multi-classifier email classification on a ubiquitous multi-core architecture. Many approaches use text-based single classifiers or multiple weakly trained classifiers to identify spam messages from a large email corpus. We build upon our previous work on multi-core by apply our ubiquitous multi-core framework to run our fusion based multi-classifier architecture. By running each classifier process in parallel within their dedicated core, we greatly improve the performance of our proposed multi-classifier based filtering system. Our proposed architecture also provides a safeguard of user mailbox from different malicious attacks. Our experimental results show that we achieved an average of 30% speedup at the average cost of 1.4 ms. We also reduced the instance of false positive, which is one of the key challenges in spam filtering system, and increases email classification accuracy substantially compared with single classification techniques.

Assessing the level of I.T. security culture improvement: Results from three Australian SMEs

Transitioning towards an improved I.T. security culture that fosters desired I.T. security behaviour and attitudes in individuals is pertinent to any organizational I.T. security strategy. To improve the current I.T. security culture of an organization and its members, an initial assessment covering four core questions was necessary to determine how much of an improvement was needed. The assessments and data collection techniques and corresponding results and findings are presented and discussed. The implications of this research will be of great benefit to both practitioners wanting to improve I.T. security culture and awareness in their organization, and will help to fill the lack empirical research within the academic field of I.T. security.