Propagation, Detection and Containment of Mobile Malware.

Today's enterprise systems and networks are frequent targets of malicious attacks, such as worms, viruses, spyware and intrusions that can disrupt, or even disable critical services. Recent trends suggest that by combining spyware as a malicious payload with worms as a delivery mechanism, malicious programs can potentially be used for industrial espionage and identity theft. The problem is compounded further by the increasing convergence of wired, wireless and cellular networks, since virus writers can now write malware that can crossover from one network segment to another, exploiting services and vulnerabilities specific to each network. This dissertation makes four primary contributions. First, it builds more accurate malware propagation models for emerging hybrid malware (i.e., malware that use multiple propagation vectors such as Bluetooth, Email, Peer-to-Peer, Instant Messaging, etc.), addressing key propagation factors such as heterogeneity of nodes, services and user mobility within the network. Second, it develops a proactive containment framework based on group-behavior of hosts against such malicious agents in an enterprise setting. The majority of today's anti-virus solutions are reactive, i.e., these are activated only after a malicious activity has been detected at a node in the network. In contrast, proactive containment has the potential of closing the vulnerable services ahead of infection, and thereby halting the spread of the malware. Third, we study (1) the current-generation mobile viruses and worms that target SMS/MMS messaging and Bluetooth on handsets, and the corresponding exploits, and (2) their potential impact in a large SMS provider network using real-life SMS network data. Finally, we propose a new behavioral approach for detecting emerging malware targeting mobile handsets. Our approach is based on the concept of generalized behavioral patterns instead of traditional signature-based detection. The signature-based methods are not scalable for deployment in mobile devices due to limited resources available on today's typical handsets. Further, we demonstrate that the behavioral approach not only has a compact footprint, but also can detect new classes of malware that combine some features from existing classes of malware.Ph.D.Computer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/60849/1/abose_1.pd

Simulating realistic network worm traffic for worm warning system design and testing

Reproducing the effects of large-scale worm attacks in a laboratory setup in a realistic and reproducible manner is an important issue for the development of worm detection and defense systems. In this paper, we describe a worm simulation model we are developing to accurately model the largescale spread dynamics of a worm and many aspects of its detailed effects on the network. We can model slow or fast worms with realistic scan rates on realistic IP address spaces and selectively model local detailed network behavior. We show how it can be used to generate realistic input traffic for a working prototype worm detection and tracking system, the Dartmouth ICMP BCC: System/Tracking and Fusion Engine (DIB:S/TRAFEN), allowing performance evaluation of the system under realistic conditions. Thus, we can answer important design questions relating to necessary detector coverage and noise filtering without deploying and operating a full system. Our experiments indicate that the tracking algorithms currently implemented in the DIB:S/TRAFEN system could detect attacks such as Code Red v2 and Sapphire/Slammer very early, even when monitoring a quite limited portion of the address space, but more sophisticated algorithms are being constructed to reduce the risk of false positives in the presence of significant “background noise ” scanning

Novel Analytical Modelling-based Simulation of Worm Propagation in Unstructured Peer-to-Peer Networks

Millions of users world-wide are sharing content using Peer-to-Peer (P2P) networks, such as Skype and Bit Torrent. While such new innovations undoubtedly bring benefits, there are nevertheless some associated threats. One of the main hazards is that P2P worms can penetrate the network, even from a single node and then spread rapidly. Understanding the propagation process of such worms has always been a challenge for researchers. Different techniques, such as simulations and analytical models, have been adopted in the literature. While simulations provide results for specific input parameter values, analytical models are rather more general and potentially cover the whole spectrum of given parameter values. Many attempts have been made to model the worm propagation process in P2P networks. However, the reported analytical models to-date have failed to cover the whole spectrum of all relevant parameters and have therefore resulted in high false-positives. This consequently affects the immunization and mitigation strategies that are adopted to cope with an outbreak of worms. The first key contribution of this thesis is the development of a susceptible, exposed, infectious, and Recovered (SEIR) analytical model for the worm propagation process in a P2P network, taking into account different factors such as the configuration diversity of nodes, user behaviour and the infection time-lag. These factors have not been considered in an integrated form previously and have been either ignored or partially addressed in state-of-the-art analytical models. Our proposed SEIR analytical model holistically integrates, for the first time, these key factors in order to capture a more realistic representation of the whole worm propagation process. The second key contribution is the extension of the proposed SEIR model to the mobile M-SEIR model by investigating and incorporating the role of node mobility, the size of the worm and the bandwidth of wireless links in the worm propagation process in mobile P2P networks. The model was designed to be flexible and applicable to both wired and wireless nodes. The third contribution is the exploitation of a promising modelling paradigm, Agent-based Modelling (ABM), in the P2P worm modelling context. Specifically, to exploit the synergies between ABM and P2P, an integrated ABM-Based worm propagation model has been built and trialled in this research for the first time. The introduced model combines the implementation of common, complex P2P protocols, such as Gnutella and GIA, along with the aforementioned analytical models. Moreover, a comparative evaluation between ABM and conventional modelling tools has been carried out, to demonstrate the key benefits of ease of real-time analysis and visualisation. As a fourth contribution, the research was further extended by utilizing the proposed SEIR model to examine and evaluate a real-world data set on one of the most recent worms, namely, the Conficker worm. Verification of the model was achieved using ABM and conventional tools and by then comparing the results on the same data set with those derived from developed benchmark models. Finally, the research concludes that the worm propagation process is to a great extent affected by different factors such as configuration diversity, user-behaviour, the infection time lag and the mobility of nodes. It was found that the infection propagation values derived from state-of-the-art mathematical models are hypothetical and do not actually reflect real-world values. In summary, our comparative research study has shown that infection propagation can be reduced due to the natural immunity against worms that can be provided by a holistic exploitation of the range of factors proposed in this work

The Dynamics of Internet Traffic: Self-Similarity, Self-Organization, and Complex Phenomena

The Internet is the most complex system ever created in human history. Therefore, its dynamics and traffic unsurprisingly take on a rich variety of complex dynamics, self-organization, and other phenomena that have been researched for years. This paper is a review of the complex dynamics of Internet traffic. Departing from normal treatises, we will take a view from both the network engineering and physics perspectives showing the strengths and weaknesses as well as insights of both. In addition, many less covered phenomena such as traffic oscillations, large-scale effects of worm traffic, and comparisons of the Internet and biological models will be covered.Comment: 63 pages, 7 figures, 7 tables, submitted to Advances in Complex System

Hybrid epidemic spreading - from Internet worms to HIV infection

Epidemic phenomena are ubiquitous, ranging from infectious diseases, computer viruses, to information dissemination. Epidemics have traditionally been studied as a single spreading process, either in a fully mixed population or on a network. Many epidemics, however, are hybrid, employing more than one spreading mechanism. For example, the Internet worm Conficker spreads locally targeting neighbouring computers in local networks as well as globally by randomly probing any computer on the Internet. This thesis aims to investigate fundamental questions, such as whether a mix of spreading mechanisms gives hybrid epidemics any advantage, and what are the implications for promoting or mitigating such epidemics. We firstly propose a general and simple framework to model hybrid epidemics. Based on theoretical analysis and numerical simulations, we show that properties of hybrid epidemics are critically determined by a hybrid tradeoff, which defines the proportion of resource allocated to local and global spreading mechanisms. We then study two distinct examples of hybrid epidemics: the Internet worm Conficker and the Human Immunodeficiency Virus (HIV) infection within the human body. Using Internet measurement data, we reveal how Conficker combines ineffective spreading mechanisms to produce a serious outbreak on the Internet. We propose a mathematical model that can accurately recapitulate the entire HIV infection course as observed in clinical trials. Our study provides novel insights into the two parallel infection channels of HIV, i.e. cell-free spreading and cell-to-cell spreading, and their joint effect on HIV infection and treatment. In summary, this thesis has advanced our understanding of hybrid epidemics. It has provided mathematical frameworks for future analysis. It has demonstrated, with two successful case studies, that such research can have a significant impact on important issues such as cyberspace security and human health

Developing spatio-temporal models of schistosomiasis transmission with climate change

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Bodies That Scatter: Sound, Cinema, Figure, Form

This dissertation argues for an understanding of “form” in two senses: as both the plasticity of the cinematic medium and the contour of the human body. Form is most often understood in relation to visible traits such as line, shape, or figure; whereas sound is described as being without form, as any number of sonorous metaphors attests (sound as aqueous, as “disembodied,” as invisible or indeterminate). Cinema, therefore, constituted as it is by sound and image, exhibits a tension between form and formlessness that manifests itself in contemporary films such as Her, Ratcatcher, Morvern Callar, We Need to Talk About Kevin, The Tree of Life, and Upstream Color at the level of the human body: corporeal boundaries blur as characters incorporate into new configurations. I conclude that we must reckon with the image in terms of sound, for thinking sonically allows us to see form—bodily and cinematic—as inherently protean. Unlike most scholarship on film sound that is predominantly formalist or historical in nature, my study takes an interdisciplinary approach that draws on theories of sound and image hailing from outside film studies proper, such as Nietzsche’s theorization of Greek tragedy, Jean-Luc Nancy’s ethics of listening, Deleuze’s exegesis on painter Francis Bacon, Nicole Brenez’s “figural” method of film criticism, and Karen Barad’s “agential realism.” I unite these ideas and others and bring them to bear on cinema, showing in the process what an attentiveness to sound has to offer not only film studies but also the humanities writ large

Conceptual Model and Architecture of MAFTIA

This deliverable builds on the work reported in [MAFTIA 2000] and [Powell and Stroud 2001]. It contains a further refinement of the MAFTIA conceptual model and a revised discussion of the MAFTIA architecture. It also introduces the work done in MAFTIA on verification and assessment of security properties, which is reported on in more detail in [Adelsbach and Creese 2003

Network Traffic Measurements, Applications to Internet Services and Security

The Internet has become along the years a pervasive network interconnecting billions of users and is now playing the role of collector for a multitude of tasks, ranging from professional activities to personal interactions. From a technical standpoint, novel architectures, e.g., cloud-based services and content delivery networks, innovative devices, e.g., smartphones and connected wearables, and security threats, e.g., DDoS attacks, are posing new challenges in understanding network dynamics. In such complex scenario, network measurements play a central role to guide traffic management, improve network design, and evaluate application requirements. In addition, increasing importance is devoted to the quality of experience provided to final users, which requires thorough investigations on both the transport network and the design of Internet services. In this thesis, we stress the importance of users’ centrality by focusing on the traffic they exchange with the network. To do so, we design methodologies complementing passive and active measurements, as well as post-processing techniques belonging to the machine learning and statistics domains. Traffic exchanged by Internet users can be classified in three macro-groups: (i) Outbound, produced by users’ devices and pushed to the network; (ii) unsolicited, part of malicious attacks threatening users’ security; and (iii) inbound, directed to users’ devices and retrieved from remote servers. For each of the above categories, we address specific research topics consisting in the benchmarking of personal cloud storage services, the automatic identification of Internet threats, and the assessment of quality of experience in the Web domain, respectively. Results comprise several contributions in the scope of each research topic. In short, they shed light on (i) the interplay among design choices of cloud storage services, which severely impact the performance provided to end users; (ii) the feasibility of designing a general purpose classifier to detect malicious attacks, without chasing threat specificities; and (iii) the relevance of appropriate means to evaluate the perceived quality of Web pages delivery, strengthening the need of users’ feedbacks for a factual assessment