Geometry-based Detection of Flash Worms

While it takes traditional internet worms hours to infect all the vulnerable hosts on the Internet, a flash worm takes seconds. Because of the rapid rate with which flash worms spread, the existing worm defense mechanisms cannot respond fast enough to detect and stop the flash worm infections. In this project, we propose a geometric-based detection mechanism that can detect the spread of flash worms in a short period of time. We tested the mechanism on various simulated flash worm traffics consisting of more than 10,000 nodes. In addition to testing on flash worm traffics, we also tested the mechanism on non-flash worm traffics to see if our detection mechanism produces false alarms. In order to efficiently analyze bulks of various network traffics, we implemented an application that can be used to convert the network traffic data into graphical notations. Using the application, the analysis can be done graphically as it displays the large amount of network relationships as tree structures

NEDAC: A worm countermeasure mechanism

This article presents an Internet worm countermeasure mechanism that uses DNS activities as a behavioural technique to detect worm propagation. The mechanism also uses a data-link containment solution to block traffic from an infected host. The concept has been demonstrated using a developed prototype and tested in a virtualised network environment. An empirical analysis of network worm propagation has been conducted to test the capabilities of the developed countermeasure mechanism. The results show that the developed mechanism is sensitive in containing Internet worms.Keywords: Worm Detection, Malware, cyber defens

Containment of fast scanning computer network worms

This paper presents a mechanism for detecting and containing fast scanning computer network worms. The countermeasure mechanism, termed NEDAC, uses a behavioural detection technique that observes the absence of DNS resolution in newly initiated outgoing connections. Upon detection of abnormal behaviour by a host, based on the absence of DNS resolution, the detection system then invokes a data link containment system to block traffic from the host. The concept has been demonstrated using a developed prototype and tested in a virtualised network environment. An empirical analysis of network worm propagation has been conducted based on the characteristics of reported contemporary vulnerabilities to test the capabilities of the countermeasure mechanism. The results show that the developed mechanism is sensitive in detecting and blocking fast scanning worm infection at an early stage

Exploiting Temporal Complex Network Metrics in Mobile Malware Containment

Malicious mobile phone worms spread between devices via short-range Bluetooth contacts, similar to the propagation of human and other biological viruses. Recent work has employed models from epidemiology and complex networks to analyse the spread of malware and the effect of patching specific nodes. These approaches have adopted a static view of the mobile networks, i.e., by aggregating all the edges that appear over time, which leads to an approximate representation of the real interactions: instead, these networks are inherently dynamic and the edge appearance and disappearance is highly influenced by the ordering of the human contacts, something which is not captured at all by existing complex network measures. In this paper we first study how the blocking of malware propagation through immunisation of key nodes (even if carefully chosen through static or temporal betweenness centrality metrics) is ineffective: this is due to the richness of alternative paths in these networks. Then we introduce a time-aware containment strategy that spreads a patch message starting from nodes with high temporal closeness centrality and show its effectiveness using three real-world datasets. Temporal closeness allows the identification of nodes able to reach most nodes quickly: we show that this scheme can reduce the cellular network resource consumption and associated costs, achieving, at the same time, a complete containment of the malware in a limited amount of time.Comment: 9 Pages, 13 Figures, In Proceedings of IEEE 12th International Symposium on a World of Wireless, Mobile and Multimedia Networks (WOWMOM '11

Early detection and containment of network worm

This paper presents a network security framework for containing the propagation of network worms. The framework employs a detection mechanism at the network layer to identify the presence of a network worm and a data-link containment solution to block the infected host. A prototype of the mechanism has been used to demonstrate the effectiveness of the developed framework. An empirical analysis of network worm propagation has been conducted to test the framework. The results show that the developed framework is effective in containing network worms with almost no false positives

Early containment of fast network worm malware

This paper presents a countermeasure mechanism for the propagation of fast network worm malware. The mechanism uses a cross layer architecture with a detection technique at the network layer to identify worm infection and a data-link containment solution to block an identified infected host. A software prototype of the mechanism has been used to demonstrate its effective. An empirical analysis of network worm propagation has been conducted to test the mechanism. The results show that the developed mechanism is effective in containing self-propagating malware with almost no false positives

Collaborative internet worm containment

Large-scale worm outbrakes that leads to distributed denial-of-dervice attacks pose a major threat to internet infrastructure security. To prevent computers from such attacks deployment of fast, scalable security overlay networks based on distributed hash tables to facilitate high-speed intrusion detection and alert-information exchange are proposed. An effective system for worm detection and cyberspace defence must have robustness, cooperation among multiple sites, responsiveness to unexpected worms and efficiency and scalability. Deployment of collaborative WormShield monitors on just 1 percent of the vulnerable edge networks can detect worm signatures roughly 10 times faster than with independent monitors.published_or_final_versio

An Innovative Signature Detection System for Polymorphic and Monomorphic Internet Worms Detection and Containment

Most current anti-worm systems and intrusion-detection systems use signature-based technology instead of anomaly-based technology. Signature-based technology can only detect known attacks with identified signatures. Existing anti-worm systems cannot detect unknown Internet scanning worms automatically because these systems do not depend upon worm behaviour but upon the worm’s signature. Most detection algorithms used in current detection systems target only monomorphic worm payloads and offer no defence against polymorphic worms, which changes the payload dynamically. Anomaly detection systems can detect unknown worms but usually suffer from a high false alarm rate. Detecting unknown worms is challenging, and the worm defence must be automated because worms spread quickly and can flood the Internet in a short time. This research proposes an accurate, robust and fast technique to detect and contain Internet worms (monomorphic and polymorphic). The detection technique uses specific failure connection statuses on specific protocols such as UDP, TCP, ICMP, TCP slow scanning and stealth scanning as characteristics of the worms. Whereas the containment utilizes flags and labels of the segment header and the source and destination ports to generate the traffic signature of the worms. Experiments using eight different worms (monomorphic and polymorphic) in a testbed environment were conducted to verify the performance of the proposed technique. The experiment results showed that the proposed technique could detect stealth scanning up to 30 times faster than the technique proposed by another researcher and had no false-positive alarms for all scanning detection cases. The experiments showed the proposed technique was capable of containing the worm because of the traffic signature’s uniqueness