1,083 research outputs found

    Study of Peer-to-Peer Network Based Cybercrime Investigation: Application on Botnet Technologies

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    The scalable, low overhead attributes of Peer-to-Peer (P2P) Internet protocols and networks lend themselves well to being exploited by criminals to execute a large range of cybercrimes. The types of crimes aided by P2P technology include copyright infringement, sharing of illicit images of children, fraud, hacking/cracking, denial of service attacks and virus/malware propagation through the use of a variety of worms, botnets, malware, viruses and P2P file sharing. This project is focused on study of active P2P nodes along with the analysis of the undocumented communication methods employed in many of these large unstructured networks. This is achieved through the design and implementation of an efficient P2P monitoring and crawling toolset. The requirement for investigating P2P based systems is not limited to the more obvious cybercrimes listed above, as many legitimate P2P based applications may also be pertinent to a digital forensic investigation, e.g, voice over IP, instant messaging, etc. Investigating these networks has become increasingly difficult due to the broad range of network topologies and the ever increasing and evolving range of P2P based applications. In this work we introduce the Universal P2P Network Investigation Framework (UP2PNIF), a framework which enables significantly faster and less labour intensive investigation of newly discovered P2P networks through the exploitation of the commonalities in P2P network functionality. In combination with a reference database of known network characteristics, it is envisioned that any known P2P network can be instantly investigated using the framework, which can intelligently determine the best investigation methodology and greatly expedite the evidence gathering process. A proof of concept tool was developed for conducting investigations on the BitTorrent network.Comment: This is a thesis submitted in fulfilment of a PhD in Digital Forensics and Cybercrime Investigation in the School of Computer Science, University College Dublin in October 201

    Information security concerns around enterprise bring your own device adoption in South African higher education institutions

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    The research carried out in this thesis is an investigation into the information security concerns around the use of personally-owned mobile devices within South African universities. This concept, which is more commonly known as Bring Your Own Device or BYOD has raised many data loss concerns for organizational IT Departments across various industries worldwide. Universities as institutions are designed to facilitate research and learning and as such, have a strong culture toward the sharing of information which complicates management of these data loss concerns even further. As such, the objectives of the research were to determine the acceptance levels of BYOD within South African universities in relation to the perceived security risks. Thereafter, an investigation into which security practices, if any, that South African universities are using to minimize the information security concerns was carried out by means of a targeted online questionnaire. An extensive literature review was first carried out to evaluate the motivation for the research and to assess advantages of using Smartphone and Tablet PC’s for work related purposes. Thereafter, to determine security concerns, other surveys and related work was consulted to determine the relevant questions needed by the online questionnaire. The quantity of comprehensive academic studies concerning the security aspects of BYOD within organizations was very limited and because of this reason, the research took on a highly exploratory design. Finally, the research deliberated on the results of the online questionnaire and concluded with a strategy for the implementation of a mobile device security strategy for using personally-owned devices in a work-related environment

    Improved Detection for Advanced Polymorphic Malware

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    Malicious Software (malware) attacks across the internet are increasing at an alarming rate. Cyber-attacks have become increasingly more sophisticated and targeted. These targeted attacks are aimed at compromising networks, stealing personal financial information and removing sensitive data or disrupting operations. Current malware detection approaches work well for previously known signatures. However, malware developers utilize techniques to mutate and change software properties (signatures) to avoid and evade detection. Polymorphic malware is practically undetectable with signature-based defensive technologies. Today’s effective detection rate for polymorphic malware detection ranges from 68.75% to 81.25%. New techniques are needed to improve malware detection rates. Improved detection of polymorphic malware can only be accomplished by extracting features beyond the signature realm. Targeted detection for polymorphic malware must rely upon extracting key features and characteristics for advanced analysis. Traditionally, malware researchers have relied on limited dimensional features such as behavior (dynamic) or source/execution code analysis (static). This study’s focus was to extract and evaluate a limited set of multidimensional topological data in order to improve detection for polymorphic malware. This study used multidimensional analysis (file properties, static and dynamic analysis) with machine learning algorithms to improve malware detection. This research demonstrated improved polymorphic malware detection can be achieved with machine learning. This study conducted a number of experiments using a standard experimental testing protocol. This study utilized three advanced algorithms (Metabagging (MB), Instance Based k-Means (IBk) and Deep Learning Multi-Layer Perceptron) with a limited set of multidimensional data. Experimental results delivered detection results above 99.43%. In addition, the experiments delivered near zero false positives. The study’s approach was based on single case experimental design, a well-accepted protocol for progressive testing. The study constructed a prototype to automate feature extraction, assemble files for analysis, and analyze results through multiple clustering algorithms. The study performed an evaluation of large malware sample datasets to understand effectiveness across a wide range of malware. The study developed an integrated framework which automated feature extraction for multidimensional analysis. The feature extraction framework consisted of four modules: 1) a pre-process module that extracts and generates topological features based on static analysis of machine code and file characteristics, 2) a behavioral analysis module that extracts behavioral characteristics based on file execution (dynamic analysis), 3) an input file construction and submission module, and 4) a machine learning module that employs various advanced algorithms. As with most studies, careful attention was paid to false positive and false negative rates which reduce their overall detection accuracy and effectiveness. This study provided a novel approach to expand the malware body of knowledge and improve the detection for polymorphic malware targeting Microsoft operating systems

    Command & Control: Understanding, Denying and Detecting - A review of malware C2 techniques, detection and defences

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    In this survey, we first briefly review the current state of cyber attacks, highlighting significant recent changes in how and why such attacks are performed. We then investigate the mechanics of malware command and control (C2) establishment: we provide a comprehensive review of the techniques used by attackers to set up such a channel and to hide its presence from the attacked parties and the security tools they use. We then switch to the defensive side of the problem, and review approaches that have been proposed for the detection and disruption of C2 channels. We also map such techniques to widely-adopted security controls, emphasizing gaps or limitations (and success stories) in current best practices.Comment: Work commissioned by CPNI, available at c2report.org. 38 pages. Listing abstract compressed from version appearing in repor

    Studying a Virtual Testbed for Unverified Data

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    It is difficult to fully know the effects a piece of software will have on your computer, particularly when the software is distributed by an unknown source. The research in this paper focuses on malware detection, virtualization, and sandbox/honeypot techniques with the goal of improving the security of installing useful, but unverifiable, software. With a combination of these techniques, it should be possible to install software in an environment where it cannot harm a machine, but can be tested to determine its safety. Testing for malware, performance, network connectivity, memory usage, and interoperability can be accomplished without allowing the program to access the base operating system of a machine. After the full effects of the software are understood and it is determined to be safe, it could then be run from, and given access to, the base operating system. This thesis investigates the feasibility of creating a system to verify the security of unknown software while ensuring it will have no negative impact on the host machine

    Security of Smartphones at the Dawn of their Ubiquitousness

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    The importance of researching in the field of smartphone security is substantiated in the increasing number of smartphones, which are expected to outnumber common computers in the future. Despite their increasing importance, it is unclear today if mobile malware will play the same role for mobile devices as for common computers today. Therefore, this thesis contributes to defining and structuring the field mobile device security with special concern on smartphones and on the operational side of security, i.e., with mobile malware as the main attacker model. Additionally, it wants to give an understanding of the shifting boundaries of the attack surface in this emerging research field. The first three chapters introduce and structure the research field with the main goal of showing what has to be defended against today. Besides introducing related work they structure mobile device attack vectors with regard to mobile malicious software and they structure the topic of mobile malicious software itself with regard to its portability. The technical contributions of this thesis are in Chapters 5 to 8, classified according to the location of the investigation (on the device, in the network, distributed in device and network). Located in the device is MobileSandbox, a software for dynamic malware analysis. As another device-centric contribution we investigate on the efforts that have to be taken to develop an autonomously spreading smartphone worm. The results of these investigations are used to show that device-centric parts are necessary for smartphone security. Additionally, we propose a novel device-centric security mechanism that aims at reducing the attack surface of mobile devices to mobile malware. The network-centric investigations show the possibilities that a mobile network operator can use in its own mobile network for protecting the mobile devices of its clients. We simulate the effectiveness of different security mechanisms. Finally, the distributed investigations show the feasibility of distributed computation algorithms with security modules. We give prototypic implementations of protocols for secure multiparty computation as a modularized version with failure detector and consensus algorithms, and for fair exchange with guardian angels

    Security Policies That Make Sense for Complex Systems: Comprehensible Formalism for the System Consumer

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    Information Systems today rarely are contained within a single user workstation, server, or networked environment. Data can be transparently accessed from any location, and maintained across various network infrastructures. Cloud computing paradigms commoditize the hardware and software environments and allow an enterprise to lease computing resources by the hour, minute, or number of instances required to complete a processing task. An access control policy mediates access requests between authorized users of an information system and the system\u27s resources. Access control policies are defined at any given level of abstraction, such as the file, directory, system, or network, and can be instantiated in layers of increasing (or decreasing) abstraction. For the system end-user, the functional allocation of security policy to discrete system components, or subsystems, may be too complex for comprehension. In this dissertation, the concept of a metapolicy, or policy that governs execution of subordinate security policies, is introduced. From the user\u27s perspective, the metapolicy provides the rules for system governance that are functionally applied across the system\u27s components for policy enforcement. The metapolicy provides a method to communicate updated higher-level policy information to all components of a system; it minimizes the overhead associated with access control decisions by making access decisions at the highest level possible in the policy hierarchy. Formal definitions of policy often involve mathematical proof, formal logic, or set theoretic notation. Such policy definitions may be beyond the capability of a system user who simply wants to control information sharing. For thousands of years, mankind has used narrative and storytelling as a way to convey knowledge. This dissertation discusses how the concepts of storytelling can be embodied in computational narrative and used as a top-level requirements specification. The definition of metapolicy is further discussed, as is the relationship between the metapolicy and various access control mechanisms. The use of storytelling to derive the metapolicy and its applicability to formal requirements definition is discussed. The author\u27s hypothesis on the use of narrative to explain security policy to the system user is validated through the use of a series of survey instruments. The survey instrument applies either a traditional requirements specification language or a brief narrative to describe a security policy and asks the subject to interpret the statements. The results of this research are promising and reflect a synthesis of the disciplines of neuroscience, security, and formal methods to present a potentially more comprehensible knowledge representation of security policy

    Collaborative, Trust-Based Security Mechanisms for a National Utility Intranet

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    This thesis investigates security mechanisms for utility control and protection networks using IP-based protocol interaction. It proposes flexible, cost-effective solutions in strategic locations to protect transitioning legacy and full IP-standards architectures. It also demonstrates how operational signatures can be defined to enact organizationally-unique standard operating procedures for zero failure in environments with varying levels of uncertainty and trust. The research evaluates layering encryption, authentication, traffic filtering, content checks, and event correlation mechanisms over time-critical primary and backup control/protection signaling to prevent disruption by internal and external malicious activity or errors. Finally, it shows how a regional/national implementation can protect private communities of interest and foster a mix of both centralized and distributed emergency prediction, mitigation, detection, and response with secure, automatic peer-to-peer notifications that share situational awareness across control, transmission, and reliability boundaries and prevent wide-spread, catastrophic power outages
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