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

An Effective SPOT System by Monitoring Outgoing Messages

ABSTRACT-Develop an effective spam zombie detection system named SPOT. In the network SPOT can be used to monitoring outgoing messages. Using internet some attacker try to spread the spams or malware in order to collect the information about the network. The detection of the compromised machines in the network that are involved in the spamming activities is known as spam zombie detection system. The detection system can be used to identify the misbehavior of the person using Spam zombie detection system. We will create a framework to identify the message from the various persons. This system will record the information of the IP address using SPOT Detection Algorithm. We also compare the performance of SPOT with two other spam zombie detection algorithms based on the count and percentage of spam messages originated or forwarded by internal machines. Using these above techniques we will avoid and block the person who sends the spam's message

An analysis of logical network distance on observed packet counts for network telescope data

This paper investigates the relationship between the logical distance between two IP addresses on the Internet, and the number of packets captured by a network telescope listening on a network containing one of the addresses. The need for the computation of a manageable measure of quantification of this distance is presented, as an alterna-tive to the raw difference that can be computed between two addresses using their Integer representations. A number of graphical analysis tools and techniques are presented to aid in this analysis. Findings are pre-sented based on a long baseline data set collected at Rhodes Universi-ty over the last three years, using a dedicated Class C (256 IP address) sensor network, and comprising 19 million packets. Of this total, 27% by packet volume originate within the same natural class A network as the telescope, and as such can be seen to be logically close to the collector network

A structured approach to malware detection and analysis in digital forensics investigation

A thesis submitted to the University of Bedfordshire in partial fulfilment of the requirement for the degree of PhDWithin the World Wide Web (WWW), malware is considered one of the most serious threats to system security with complex system issues caused by malware and spam. Networks and systems can be accessed and compromised by various types of malware, such as viruses, worms, Trojans, botnet and rootkits, which compromise systems through coordinated attacks. Malware often uses anti-forensic techniques to avoid detection and investigation. Moreover, the results of investigating such attacks are often ineffective and can create barriers for obtaining clear evidence due to the lack of sufficient tools and the immaturity of forensics methodology. This research addressed various complexities faced by investigators in the detection and analysis of malware. In this thesis, the author identified the need for a new approach towards malware detection that focuses on a robust framework, and proposed a solution based on an extensive literature review and market research analysis. The literature review focussed on the different trials and techniques in malware detection to identify the parameters for developing a solution design, while market research was carried out to understand the precise nature of the current problem. The author termed the new approaches and development of the new framework the triple-tier centralised online real-time environment (tri-CORE) malware analysis (TCMA). The tiers come from three distinctive phases of detection and analysis where the entire research pattern is divided into three different domains. The tiers are the malware acquisition function, detection and analysis, and the database operational function. This framework design will contribute to the field of computer forensics by making the investigative process more effective and efficient. By integrating a hybrid method for malware detection, associated limitations with both static and dynamic methods are eliminated. This aids forensics experts with carrying out quick, investigatory processes to detect the behaviour of the malware and its related elements. The proposed framework will help to ensure system confidentiality, integrity, availability and accountability. The current research also focussed on a prototype (artefact) that was developed in favour of a different approach in digital forensics and malware detection methods. As such, a new Toolkit was designed and implemented, which is based on a simple architectural structure and built from open source software that can help investigators develop the skills to critically respond to current cyber incidents and analyses

Modeling and defense against propagation of worms in networks

Worms are widely believed to be one of the most serious challenges in network security research. In order to prevent worms from propagating, we present a microcosmic model, which can benefit the security industry by allowing them to save significant money in the deployment of their security patching schemes

A framework for the application of network telescope sensors in a global IP network

The use of Network Telescope systems has become increasingly popular amongst security researchers in recent years. This study provides a framework for the utilisation of this data. The research is based on a primary dataset of 40 million events spanning 50 months collected using a small (/24) passive network telescope located in African IP space. This research presents a number of differing ways in which the data can be analysed ranging from low level protocol based analysis to higher level analysis at the geopolitical and network topology level. Anomalous traffic and illustrative anecdotes are explored in detail and highlighted. A discussion relating to bogon traffic observed is also presented. Two novel visualisation tools are presented, which were developed to aid in the analysis of large network telescope datasets. The first is a three-dimensional visualisation tool which allows for live, near-realtime analysis, and the second is a two-dimensional fractal based plotting scheme which allows for plots of the entire IPv4 address space to be produced, and manipulated. Using the techniques and tools developed for the analysis of this dataset, a detailed analysis of traffic recorded as destined for port 445/tcp is presented. This includes the evaluation of traffic surrounding the outbreak of the Conficker worm in November 2008. A number of metrics relating to the description and quantification of network telescope configuration and the resultant traffic captures are described, the use of which it is hoped will facilitate greater and easier collaboration among researchers utilising this network security technology. The research concludes with suggestions relating to other applications of the data and intelligence that can be extracted from network telescopes, and their use as part of an organisation’s integrated network security system