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Katz, Jonathan, Shin, Ji Sun.  2005.  Modeling Insider Attacks on Group Key-exchange Protocols. Proceedings of the 12th ACM Conference on Computer and Communications Security. :180–189.

Protocols for authenticated key exchange (AKE) allow parties within an insecure network to establish a common session key which can then be used to secure their future communication. It is fair to say that group AKE is currently less well understood than the case of two-party AKE; in particular, attacks by malicious insiders –- a concern specific to the group setting –- have so far been considered only in a relatively "ad-hoc" fashion. The main contribution of this work is to address this deficiency by providing a formal, comprehensive model and definition of security for group AKE which automatically encompasses insider attacks. We do so by defining an appropriate ideal functionality for group AKE within the universal composability (UC) framework. As a side benefit, any protocol secure with respect to our definition is secure even when run concurrently with other protocols, and the key generated by any such protocol may be used securely in any subsequent application.In addition to proposing this definition, we show that the resulting notion of security is strictly stronger than the one proposed by Bresson, et al. (termed "AKE-security"), and that our definition implies all previously-suggested notions of security against insider attacks. We also show a simple technique for converting any AKE-secure protocol into one secure with respect to our definition.

Ingols, Kyle, Chu, Matthew, Lippmann, Richard, Webster, Seth, Boyer, Stephen.  2009.  Modeling Modern Network Attacks and Countermeasures Using Attack Graphs. 2009 Annual Computer Security Applications Conference. :117–126.
By accurately measuring risk for enterprise networks, attack graphs allow network defenders to understand the most critical threats and select the most effective countermeasures. This paper describes substantial enhancements to the NetSPA attack graph system required to model additional present-day threats (zero-day exploits and client-side attacks) and countermeasures (intrusion prevention systems, proxy firewalls, personal firewalls, and host-based vulnerability scans). Point-to-point reachability algorithms and structures were extensively redesigned to support "reverse" reachability computations and personal firewalls. Host-based vulnerability scans are imported and analyzed. Analysis of an operational network with 84 hosts demonstrates that client-side attacks pose a serious threat. Experiments on larger simulated networks demonstrated that NetSPA's previous excellent scaling is maintained. Less than two minutes are required to completely analyze a four-enclave simulated network with more than 40,000 hosts protected by personal firewalls.
Becher, M., Freiling, F.C., Hoffmann, J., Holz, T., Uellenbeck, S., Wolf, C..  2011.  Mobile Security Catching Up? Revealing the Nuts and Bolts of the Security of Mobile Devices Security and Privacy (SP), 2011 IEEE Symposium on. :96-111.

We are currently moving from the Internet society to a mobile society where more and more access to information is done by previously dumb phones. For example, the number of mobile phones using a full blown OS has risen to nearly 200% from Q3/2009 to Q3/2010. As a result, mobile security is no longer immanent, but imperative. This survey paper provides a concise overview of mobile network security, attack vectors using the back end system and the web browser, but also the hardware layer and the user as attack enabler. We show differences and similarities between "normal" security and mobile security, and draw conclusions for further research opportunities in this area.

Huang, Bai-Ruei, Lin, Chang Hong, Lee, Chia-Han.  2012.  Mobile augmented reality based on cloud computing. and Identification Anti-counterfeiting, Security. :1—5.
In this paper, we implemented a mobile augmented reality system based on cloud computing. This system uses a mobile device with a camera to capture images of book spines and sends processed features to the cloud. In the cloud, the features are compared with the database and the information of the best matched book would be sent back to the mobile device. The information will then be rendered on the display via augmented reality. In order to reduce the transmission cost, the mobile device is used to perform most of the image processing tasks, such as the preprocessing, resizing, corner detection, and augmented reality rendering. On the other hand, the cloud is used to realize routine but large quantity feature comparisons. Using the cloud as the database also makes the future extension much more easily. For our prototype system, we use an Android smart phone as our mobile device, and Chunghwa Telecoms hicloud as the cloud.
Zoe McCarthy, University of Illinois at Urbana-Champaign, Timothy Bretl, University of Illinois at Urbana-Champaign.  2012.  Mechanics and Manipulation of Planar Elastic Kinematic Chains. IEEE International Conference on Robotics and Automation.

This paper presents a control strategy based on model learning for a self-assembled robotic “swimmer”. The swimmer forms when a liquid suspension of ferro-magnetic micro-particles and a non-magnetic bead are exposed to an alternating magnetic field that is oriented perpendicular to the liquid surface. It can be steered by modulating the frequency of the alternating field. We model the swimmer as a unicycle and learn a mapping from frequency to forward speed and turning rate using locally-weighted projection regression. We apply iterative linear quadratic regulation with a receding horizon to track motion primitives that could be used for path following. Hardware experiments validate our approach.

Zoe McCarthy, University of Illinois at Urbana-Champaign, Timothy Bretl, University of Illinois at Urbana-Champaign.  2012.  Mechanics and Manipulation of Planar Elastic Kinematic Chains. 2012 IEEE International Conference on Robotics and Automation.

In this paper, we study quasi-static manipulation of a planar kinematic chain with a fixed base in which each joint is a linearly-elastic torsional spring. The shape of this chain when in static equilibrium can be represented as the solution to a discrete-time optimal control problem, with boundary conditions that vary with the position and orientation of the last link. We prove that the set of all solutions to this problem is a smooth manifold that can be parameterized by a single chart. For manipulation planning, we show several advantages of working in this chart instead of in the space of boundary conditions, particularly in the context of a sampling-based planning algorithm. Examples are provided in simulation.

Timothy Bretl, University of Illinois at Urbana-Champaign, Zoe McCarthy, University of Illinois at Urbana-Champaign.  2012.  Mechanics and Quasi-Static Manipulation of Planar Elastic Kinematic Chains. IEEE Transactions on Robotics. 29(1)

In this paper, we study quasi-static manipulation of a planar kinematic chain with a fixed base in which each joint is a linearly elastic torsional spring. The shape of this chain when in static equilibrium can be represented as the solution to a discretetime optimal control problem, with boundary conditions that vary with the position and orientation of the last link. We prove that the set of all solutions to this problem is a smooth three-manifold that can be parameterized by a single chart. Empirical results in simulation show that straight-line paths in this chart are uniformly more likely to be feasible (as a function of distance) than straightline paths in the space of boundary conditions. These results, which are consistent with an analysis of visibility properties, suggest that the chart we derive is a better choice of space in which to apply a sampling-based algorithm for manipulation planning. We describe such an algorithm and show that it is easy to implement.

Qian, Kai, Dan Lo, Chia-Tien, Guo, Minzhe, Bhattacharya, Prabir, Yang, Li.  2012.  Mobile security labware with smart devices for cybersecurity education. IEEE 2nd Integrated STEM Education Conference. :1—3.

Smart mobile devices such as smartphones and tablets have become an integral part of our society. However, it also becomes a prime target for attackers with malicious intents. There have been a number of efforts on developing innovative courseware to promote cybersecurity education and to improve student learning; however, hands-on labs are not well developed for smart mobile devices and for mobile security topics. In this paper, we propose to design and develop a mobile security labware with smart mobile devices to promote the cybersecurity education. The integration of mobile computing technologies and smart devices into cybersecurity education will connect the education to leading-edge information technologies, motivate and engage students in security learning, fill in the gap with IT industry need, and help faculties build expertise on mobile computing. In addition, the hands-on experience with mobile app development will promote student learning and supply them with a better understanding of security knowledge not only in classical security domains but also in the emerging mobile security areas.

Mazurek, Michelle L., Komanduri, Saranga, Vidas, Timothy, Bauer, Lujo, Christin, Nicolas, Cranor, Lorrie Faith, Kelley, Patrick Gage, Shay, Richard, Ur, Blase.  2013.  Measuring Password Guessability for an Entire University. Proceedings of the 2013 ACM SIGSAC Conference on Computer &\#38; Communications Security. :173–186.
Despite considerable research on passwords, empirical studies of password strength have been limited by lack of access to plaintext passwords, small data sets, and password sets specifically collected for a research study or from low-value accounts. Properties of passwords used for high-value accounts thus remain poorly understood. We fill this gap by studying the single-sign-on passwords used by over 25,000 faculty, staff, and students at a research university with a complex password policy. Key aspects of our contributions rest on our (indirect) access to plaintext passwords. We describe our data collection methodology, particularly the many precautions we took to minimize risks to users. We then analyze how guessable the collected passwords would be during an offline attack by subjecting them to a state-of-the-art password cracking algorithm. We discover significant correlations between a number of demographic and behavioral factors and password strength. For example, we find that users associated with the computer science school make passwords more than 1.5 times as strong as those of users associated with the business school. while users associated with computer science make strong ones. In addition, we find that stronger passwords are correlated with a higher rate of errors entering them. We also compare the guessability and other characteristics of the passwords we analyzed to sets previously collected in controlled experiments or leaked from low-value accounts. We find more consistent similarities between the university passwords and passwords collected for research studies under similar composition policies than we do between the university passwords and subsets of passwords leaked from low-value accounts that happen to comply with the same policies.
Titus Barik, Arpan Chakraborty, Brent Harrison, David L. Roberts, Robert St. Amant.  2013.  Modeling the Concentration Game with ACT-R. The 12th International Conference on Cognitive Modeling.

This paper describes the development of subsymbolic ACT-R models for the Concentration game. Performance data is taken from an experiment in which participants played the game un- der two conditions: minimizing the number of mismatches/ turns during a game, and minimizing the time to complete a game. Conflict resolution and parameter tuning are used to implement an accuracy model and a speed model that capture the differences for the two conditions. Visual attention drives exploration of the game board in the models. Modeling re- sults are generally consistent with human performance, though some systematic differences can be seen. Modeling decisions, model limitations, and open issues are discussed. 

Chang Liu, Hicks, M., Shi, E..  2013.  Memory Trace Oblivious Program Execution. Computer Security Foundations Symposium (CSF), 2013 IEEE 26th. :51-65.

Cloud computing allows users to delegate data and computation to cloud service providers, at the cost of giving up physical control of their computing infrastructure. An attacker (e.g., insider) with physical access to the computing platform can perform various physical attacks, including probing memory buses and cold-boot style attacks. Previous work on secure (co-)processors provides hardware support for memory encryption and prevents direct leakage of sensitive data over the memory bus. However, an adversary snooping on the bus can still infer sensitive information from the memory access traces. Existing work on Oblivious RAM (ORAM) provides a solution for users to put all data in an ORAM; and accesses to an ORAM are obfuscated such that no information leaks through memory access traces. This method, however, incurs significant memory access overhead. This work is the first to leverage programming language techniques to offer efficient memory-trace oblivious program execution, while providing formal security guarantees. We formally define the notion of memory-trace obliviousness, and provide a type system for verifying that a program satisfies this property. We also describe a compiler that transforms a program into a structurally similar one that satisfies memory trace obliviousness. To achieve optimal efficiency, our compiler partitions variables into several small ORAM banks rather than one large one, without risking security. We use several example programs to demonstrate the efficiency gains our compiler achieves in comparison with the naive method of placing all variables in the same ORAM.

Colbaugh, R., Glass, K..  2013.  Moving target defense for adaptive adversaries. Intelligence and Security Informatics (ISI), 2013 IEEE International Conference on. :50-55.

Machine learning (ML) plays a central role in the solution of many security problems, for example enabling malicious and innocent activities to be rapidly and accurately distinguished and appropriate actions to be taken. Unfortunately, a standard assumption in ML - that the training and test data are identically distributed - is typically violated in security applications, leading to degraded algorithm performance and reduced security. Previous research has attempted to address this challenge by developing ML algorithms which are either robust to differences between training and test data or are able to predict and account for these differences. This paper adopts a different approach, developing a class of moving target (MT) defenses that are difficult for adversaries to reverse-engineer, which in turn decreases the adversaries' ability to generate training/test data differences that benefit them. We leverage the coevolutionary relationship between attackers and defenders to derive a simple, flexible MT defense strategy which is optimal or nearly optimal for a broad range of security problems. Case studies involving two distinct cyber defense applications demonstrate that the proposed MT algorithm outperforms standard static methods, offering effective defense against intelligent, adaptive adversaries.

Liu, S., Hong, Y., Viterbo, E..  2014.  On measures of information theoretic security. 2014 IEEE Information Theory Workshop (ITW 2014). :309–310.
While information-theoretic security is stronger than computational security, it has long been considered impractical. In this work, we provide new insights into the design of practical information-theoretic cryptosystems. Firstly, from a theoretical point of view, we give a brief introduction into the existing information theoretic security criteria, such as the notions of Shannon's perfect/ideal secrecy in cryptography, and the concept of strong secrecy in coding theory. Secondly, from a practical point of view, we propose the concept of ideal secrecy outage and define a outage probability. Finally, we show how such probability can be made arbitrarily small in a practical cryptosystem.
Balkesen, C., Teubner, J., Alonso, G., Ozsu, M.T..  2014.  Main-Memory Hash Joins on Modern Processor Architectures. Knowledge and Data Engineering, IEEE Transactions on. PP:1-1.

Existing main-memory hash join algorithms for multi-core can be classified into two camps. Hardware-oblivious hash join variants do not depend on hardware-specific parameters. Rather, they consider qualitative characteristics of modern hardware and are expected to achieve good performance on any technologically similar platform. The assumption behind these algorithms is that hardware is now good enough at hiding its own limitations-through automatic hardware prefetching, out-of-order execution, or simultaneous multi-threading (SMT)-to make hardware-oblivious algorithms competitive without the overhead of carefully tuning to the underlying hardware. Hardware-conscious implementations, such as (parallel) radix join, aim to maximally exploit a given architecture by tuning the algorithm parameters (e.g., hash table sizes) to the particular features of the architecture. The assumption here is that explicit parameter tuning yields enough performance advantages to warrant the effort required. This paper compares the two approaches under a wide range of workloads (relative table sizes, tuple sizes, effects of sorted data, etc.) and configuration parameters (VM page sizes, number of threads, number of cores, SMT, SIMD, prefetching, etc.). The results show that hardware-conscious algorithms generally outperform hardware-oblivious ones. However, on specific workloads and special architectures with aggressive simultaneous multi-threading, hardware-oblivious algorithms are competitive. The main conclusion of the paper is that, in existing multi-core architectures, it is still important to carefully tailor algorithms to the underlying hardware to get the necessary performance. But processor developments may require to revisit this conclusion in the future.

Ken Keefe, University of Illinois at Urbana-Champaign.  2014.  Making Sound Design Decisions Using Quantitative Security Metrics.

Presented at the Illinois SoS Bi-weekly Meeting, December 2014.

Welzel, Arne, Rossow, Christian, Bos, Herbert.  2014.  On Measuring the Impact of DDoS Botnets. Proceedings of the Seventh European Workshop on System Security. :3:1–3:6.

Miscreants use DDoS botnets to attack a victim via a large number of malware-infected hosts, combining the bandwidth of the individual PCs. Such botnets have thus a high potential to render targeted services unavailable. However, the actual impact of attacks by DDoS botnets has never been evaluated. In this paper, we monitor C&C servers of 14 DirtJumper and Yoddos botnets and record the DDoS targets of these networks. We then aim to evaluate the availability of the DDoS victims, using a variety of measurements such as TCP response times and analyzing the HTTP content. We show that more than 65% of the victims are severely affected by the DDoS attacks, while also a few DDoS attacks likely failed.

Jun Moon, University of Illinois at Urbana-Champaign, Tamer Başar, University of Illinois at Urbana-Champaign.  2014.  Minimax Control of MIMO Systems Over Multiple TCP-like Lossy Networks. 19th IFAC World Congress (IFAC 2014).

This paper considers a minimax control problem over multiple packet dropping channels. The channel losses are assumed to be Bernoulli processes, and operate under the transmission control protocol (TCP); hence acknowledgments of control and measurement drops are available at each time. Under this setting, we obtain an output feedback minimax controller, which are implicitly dependent on rates of control and measurement losses. For the infinite-horizon case, we first characterize achievable Hdisturbance attenuation levels, and then show that the underlying condition is a function of packet loss rates. We also address the converse part by showing that the condition of the minimum attainable loss rates for closed-loop system stability is a function of H disturbance attenuation parameter. Hence, those conditions are coupled with each other. Finally, we show the limiting behavior of the minimax controller under the disturbance attenuation parameter.

Sardana, Noel, Cohen, Robin.  2014.  Modeling Agent Trustworthiness with Credibility for Message Recommendation in Social Networks. Proceedings of the 2014 International Conference on Autonomous Agents and Multi-agent Systems. :1423–1424.

This paper presents a framework for multiagent systems trust modeling that reasons about both user credibility and user similarity. Through simulation, we are able to show that our approach works well in social networking environments by presenting messages to users with high predicted benefit.

David Nicol, University of Illinois at Urbana-Champaign, Vikas Mallapura, University of Illinois at Urbana-Champaign.  2014.  Modeling and Analysis of Stepping Stone Attacks. 2014 Winter Simulation Conference.

Computer exploits often involve an attacker being able to compromise a sequence of hosts, creating a chain of "stepping stones" from his source to ultimate target. Stepping stones are usually necessary to access well-protected resources, and also serve to mask the attacker’s location. This paper describes means of constructing models of networks and the access control mechanisms they employ to approach the problem of finding which stepping stone paths are easiest for an attacker to find. While the simplest formulation of the problem can be addressed with deterministic shortest-path algorithms, we argue that consideration of what and how an attacker may (or may not) launch from a compromised host pushes one towards solutions based on Monte Carlo sampling. We describe the sampling algorithm and some preliminary results obtained using it.

Liu, Qian, Bae, Juhee, Watson, Benjamin, McLaughhlin, Anne, Enck, William.  2014.  Modeling and Sensing Risky User Behavior on Mobile Devices. Proceedings of the 2014 Symposium and Bootcamp on the Science of Security. :33:1–33:2.

As mobile technology begins to dominate computing, understanding how their use impacts security becomes increasingly important. Fortunately, this challenge is also an opportunity: the rich set of sensors with which most mobile devices are equipped provide a rich contextual dataset, one that should enable mobile user behavior to be modeled well enough to predict when users are likely to act insecurely, and provide cognitively grounded explanations of those behaviors. We will evaluate this hypothesis with a series of experiments designed first to confirm that mobile sensor data can reliably predict user stress, and that users experiencing such stress are more likely to act insecurely.

Smith, Andrew, Vorobeychik, Yevgeniy, Letchford, Joshua.  2014.  Multi-Defender Security Games on Networks. SIGMETRICS Perform. Eval. Rev.. 41:4–7.

Stackelberg security game models and associated computational tools have seen deployment in a number of high- consequence security settings, such as LAX canine patrols and Federal Air Marshal Service. This deployment across essentially independent agencies raises a natural question: what global impact does the resulting strategic interaction among the defenders, each using a similar model, have? We address this question in two ways. First, we demonstrate that the most common solution concept of Strong Stackelberg equilibrium (SSE) can result in significant under-investment in security entirely because SSE presupposes a single defender. Second, we propose a framework based on a different solution concept which incorporates a model of interdependencies among targets, and show that in this framework defenders tend to over-defend, even under significant positive externalities of increased defense.

Janakiraman, Nithiyanantham, Nirmal Kumar, Palanisamy.  2014.  Multi-objective Module Partitioning Design for Dynamic and Partial Reconfigurable System-on-chip Using Genetic Algorithm. J. Syst. Archit.. 60:119–139.

This paper proposes a novel architecture for module partitioning problems in the process of dynamic and partial reconfigurable computing in VLSI design automation. This partitioning issue is deemed as Hypergraph replica. This can be treated by a probabilistic algorithm like the Markov chain through the transition probability matrices due to non-deterministic polynomial complete problems. This proposed technique has two levels of implementation methodology. In the first level, the combination of parallel processing of design elements and efficient pipelining techniques are used. The second level is based on the genetic algorithm optimization system architecture. This proposed methodology uses the hardware/software co-design and co-verification techniques. This architecture was verified by implementation within the MOLEN reconfigurable processor and tested on a Xilinx Virtex-5 based development board. This proposed multi-objective module partitioning design was experimentally evaluated using an ISPD’98 circuit partitioning benchmark suite. The efficiency and throughput were compared with that of the hMETIS recursive bisection partitioning approach. The results indicate that the proposed method can improve throughput and efficiency up to 39 times with only a small amount of increased design space. The proposed architecture style is sketched out and concisely discussed in this manuscript, and the existing results are compared and analyzed.

El-Koujok, M., Benammar, M., Meskin, N., Al-Naemi, M., Langari, R..  2014.  Multiple Sensor Fault Diagnosis by Evolving Data-driven Approach. Inf. Sci.. 259:346–358.

Sensors are indispensable components of modern plants and processes and their reliability is vital to ensure reliable and safe operation of complex systems. In this paper, the problem of design and development of a data-driven Multiple Sensor Fault Detection and Isolation (MSFDI) algorithm for nonlinear processes is investigated. The proposed scheme is based on an evolving multi-Takagi Sugeno framework in which each sensor output is estimated using a model derived from the available input/output measurement data. Our proposed MSFDI algorithm is applied to Continuous-Flow Stirred-Tank Reactor (CFSTR). Simulation results demonstrate and validate the performance capabilities of our proposed MSFDI algorithm.

Biplab Deka, University of Illinois at Urbana-Champaign, Alex A. Birklykke, Aalborg University, Henry Duwe, University of Illinois at Urbana-Champaign, Vikash K. Mansinghka, Massachusetts Institute of Technology, Rakesh Kumar, University of Illinois at Urbana-Champaign.  2014.  Markov Chain Algorithms: A Template for Building Future Robust Low-power Systems. Philosophical Transactions of the Royal Society A Mathematical, Physical and Engineering Sciences.

Although computational systems are looking towards post CMOS devices in the pursuit of lower power, the expected inherent unreliability of such devices makes it difficult to design robust systems without additional power overheads for guaranteeing robustness. As such, algorithmic structures with inherent ability to tolerate computational errors are of significant interest. We propose to cast applications as stochastic algorithms based on Markov chains (MCs) as such algorithms are both sufficiently general and tolerant to transition errors. We show with four example applications—Boolean satisfiability, sorting, low-density parity-check decoding and clustering—how applications can be cast as MC algorithms. Using algorithmic fault injection techniques, we demonstrate the robustness of these implementations to transition errors with high error rates. Based on these results, we make a case for using MCs as an algorithmic template for future robust low-power systems.