TY - CONF
AB - Resolving distributed attacks benefits from collaboration between networks. We present three approaches for the same multi-domain defensive action that can be applied in such an alliance: 1) Counteract Everywhere, 2) Minimize Countermeasures, and 3) Minimize Propagation. First, we provide a formula to compute efficiency of a defense; then we use this formula to compute the efficiency of the approaches under various circumstances. Finally, we discuss how task execution order and timing influence defense efficiency. Our results show that the Minimize Propagation approach is the most efficient method when defending against the chosen attack.
AU - Koning, Ralph
AU - Polevoy, Gleb
AU - Meijer, Lydia
AU - de Laat, Cees
AU - Grosso, Paola
ID - 17667
KW - computer network security
KW - multinetwork environments
KW - multidomain defensive action
KW - task execution order
KW - timing influence defense efficiency
KW - distributed attacks
KW - collaborative security defence approach
KW - minimize propagation approach
KW - minimize countermeasure approach
KW - counteract everywhere approach
KW - Conferences
KW - Cloud computing
KW - Computer crime
KW - Edge computing
KW - Security
KW - Defense Approaches
KW - Multi-Domain Defense
KW - Collaborative Defense
KW - Defense Algorithms
KW - Computer Networks
SN - null
T2 - 2019 6th IEEE International Conference on Cyber Security and Cloud Computing (CSCloud)/ 2019 5th IEEE International Conference on Edge Computing and Scalable Cloud (EdgeCom)
TI - Approaches for Collaborative Security Defences in Multi Network Environments
ER -
TY - THES
AB - This thesis investigates approximate pure Nash equilibria in different game-theoretic models. In such an outcome, no player can improve her objective by more than a given factor through a deviation to another strategy. In the first part, we investigate two variants of Congestion Games in which the existence of pure Nash equilibria is guaranteed through a potential function argument. However, the computation of such equilibria might be hard. We construct and analyze approximation algorithms that enable the computation of states with low approximation factors in polynomial time. To show their guarantees we use sub games among players, bound the potential function values of arbitrary states and exploit a connection between Shapley and proportional cost shares. Furthermore, we apply and analyze sampling techniques for the computation of approximate Shapley values in different settings. In the second part, we concentrate on the existence of approximate pure Nash equilibria in games in which no pure Nash equilibria exist in general. In the model of Coevolving Opinion Formation Games, we bound the approximation guarantees for natural states nearly independent of the specific definition of the players' neighborhoods by applying a concept of virtual costs. For the special case of only one influential neighbor, we even show lower approximation factors for a natural strategy. Then, we investigate a two-sided Facility Location Game among facilities and clients on a line with an objective function consisting of distance and load. We show tight bounds on the approximation factor for settings with three facilities and infinitely many clients. For the general scenario with an arbitrary number of facilities, we bound the approximation factor for two promising candidates, namely facilities that are uniformly distributed and which are paired.
AU - Feldotto, Matthias
ID - 8080
TI - Approximate Pure Nash Equilibria in Congestion, Opinion Formation and Facility Location Games
ER -
TY - CONF
AB - We characterise the set of dominant strategy incentive compatible (DSIC), strongly budget balanced (SBB), and ex-post individually rational (IR) mechanisms for the multi-unit bilateral trade setting. In such a setting there is a single buyer and a single seller who holds a finite number k of identical items. The mechanism has to decide how many units of the item are transferred from the seller to the buyer and how much money is transferred from the buyer to the seller. We consider two classes of valuation functions for the buyer and seller: Valuations that are increasing in the number of units in possession, and the more specific class of valuations that are increasing and submodular.
Furthermore, we present some approximation results about the performance of certain such mechanisms, in terms of social welfare: For increasing submodular valuation functions, we show the existence of a deterministic 2-approximation mechanism and a randomised e/(1-e) approximation mechanism, matching the best known bounds for the single-item setting.
AU - Lazos, Philip
AU - Goldberg, Paul
AU - Skopalik, Alexander
AU - Gerstgrasser, Matthias
AU - de Keijzer, Bart
ID - 5471
T2 - Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence (AAAI)
TI - Multi-unit Bilateral Trade
ER -
TY - CONF
AB - Competing firms tend to select similar locations for their stores. This phenomenon, called the principle of minimum differentiation, was captured by Hotelling with a landmark model of spatial competition but is still the object of an ongoing scientific debate. Although consistently observed in practice, many more realistic variants of Hotelling's model fail to support minimum differentiation or do not have pure equilibria at all. In particular, it was recently proven for a generalized model which incorporates negative network externalities and which contains Hotelling's model and classical selfish load balancing as special cases, that the unique equilibria do not adhere to minimum differentiation. Furthermore, it was shown that for a significant parameter range pure equilibria do not exist. We derive a sharp contrast to these previous results by investigating Hotelling's model with negative network externalities from an entirely new angle: approximate pure subgame perfect equilibria. This approach allows us to prove analytically and via agent-based simulations that approximate equilibria having good approximation guarantees and that adhere to minimum differentiation exist for the full parameter range of the model. Moreover, we show that the obtained approximate equilibria have high social welfare.
AU - Feldotto, Matthias
AU - Lenzner, Pascal
AU - Molitor, Louise
AU - Skopalik, Alexander
ID - 10281
T2 - Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems
TI - From Hotelling to Load Balancing: Approximation and the Principle of Minimum Differentiation
ER -
TY - CONF
AB - We study the classic bin packing problem in a fully-dynamic setting, where new items can arrive and old items may depart. We want algorithms with low asymptotic competitive ratio while repacking items sparingly between updates. Formally, each item i has a movement cost c_i >= 0, and we want to use alpha * OPT bins and incur a movement cost gamma * c_i, either in the worst case, or in an amortized sense, for alpha, gamma as small as possible. We call gamma the recourse of the algorithm. This is motivated by cloud storage applications, where fully-dynamic bin packing models the problem of data backup to minimize the number of disks used, as well as communication incurred in moving file backups between disks. Since the set of files changes over time, we could recompute a solution periodically from scratch, but this would give a high number of disk rewrites, incurring a high energy cost and possible wear and tear of the disks. In this work, we present optimal tradeoffs between number of bins used and number of items repacked, as well as natural extensions of the latter measure.
AU - Feldkord, Björn
AU - Feldotto, Matthias
AU - Gupta, Anupam
AU - Guruganesh, Guru
AU - Kumar, Amit
AU - Riechers, Sören
AU - Wajc, David
ED - Chatzigiannakis, Ioannis
ED - Kaklamanis, Christos
ED - Marx, Dániel
ED - Sannella, Donald
ID - 2484
SN - 1868-8969
T2 - 45th International Colloquium on Automata, Languages, and Programming (ICALP 2018)
TI - Fully-Dynamic Bin Packing with Little Repacking
VL - 107
ER -
TY - CONF
AB - We consider a market where final products or services are compositions of a number of basic services. Users are asked to evaluate the quality of the composed product after purchase. The quality of the basic service influences the performance of the composed services but cannot be observed directly. The question we pose is whether it is possible to use user evaluations on composed services to assess the quality of basic services. We discuss how to combine aggregation of evaluations across users and disaggregation of information on composed services to derive valuations for the single components. As a solution we propose to use the (weighted) average as aggregation device in connection with the Shapley value as disaggregation method, since this combination fulfills natural requirements in our context. In addition, we address some occurring computational issues: We give an approximate solution concept using only a limited number of evaluations which guarantees nearly optimal results with reduced running time. Lastly, we show that a slightly modified Shapley value and the weighted average are still applicable if the evaluation profiles are incomplete.
AU - Feldotto, Matthias
AU - Haake, Claus-Jochen
AU - Skopalik, Alexander
AU - Stroh-Maraun, Nadja
ID - 2831
SN - 978-1-4503-5916-0
T2 - Proceedings of the 13th Workshop on Economics of Networks, Systems and Computation (NetEcon 2018)
TI - Disaggregating User Evaluations Using the Shapley Value
ER -
TY - GEN
AU - Koop, Samuel
ID - 3851
TI - Congestion Games mit gewichteten Strategien
ER -
TY - CONF
AB - Consider mitigating the effects of denial of service or of malicious traffic in networks by deleting edges. Edge deletion reduces the DoS or the number of the malicious flows, but it also inadvertently removes some of the desired flows. To model this important problem, we formulate two problems: (1) remove all the undesirable flows while minimizing the damage to the desirable ones and (2) balance removing the undesirable flows and not removing too many of the desirable flows. We prove these problems are equivalent to important theoretical problems, thereby being important not only practically but also theoretically, and very hard to approximate in a general network. We employ reductions to nonetheless approximate the problem and also provide a greedy approximation. When the network is a tree, the problems are still MAX SNP-hard, but we provide a greedy-based 2l-approximation algorithm, where l is the longest desirable flow. We also provide an algorithm, approximating the first and the second problem within {\$}{\$}2 {\backslash}sqrt{\{} 2{\backslash}left| E {\backslash}right| {\}}{\$}{\$}and {\$}{\$}2 {\backslash}sqrt{\{}2 ({\backslash}left| E {\backslash}right| + {\backslash}left| {\backslash}text {\{}undesirable flows{\}} {\backslash}right| ){\}}{\$}{\$}, respectively, where E is the set of the edges of the network. We also provide a fixed-parameter tractable (FPT) algorithm. Finally, if the tree has a root such that every flow in the tree flows on the path from the root to a leaf, we solve the problem exactly using dynamic programming.
AU - Polevoy, Gleb
AU - Trajanovski, Stojan
AU - Grosso, Paola
AU - de Laat, Cees
ED - Kim, Donghyun
ED - Uma, R. N.
ED - Zelikovsky, Alexander
ID - 17651
KW - flow
KW - Red-Blue Set Cover
KW - Positive-Negative Partial Set Cover
KW - approximation
KW - tree
KW - MAX SNP-hard
KW - root
KW - leaf
KW - dynamic programming
KW - FPT
SN - 978-3-030-04651-4
T2 - Combinatorial Optimization and Applications
TI - Removing Undesirable Flows by Edge Deletion
ER -
TY - JOUR
AB - Software Defined Networks (SDN) and Network Function Virtualisation (NFV) provide the basis for autonomous response and mitigation against attacks on networked computer infrastructures. We propose a new framework that uses SDNs and NFV to achieve this goal: Secure Autonomous Response Network (SARNET). In a SARNET, an agent running a control loop constantly assesses the security state of the network by means of observables. The agent reacts to and resolves security problems, while learning from its previous decisions. Two main metrics govern the decision process in a SARNET: impact and efficiency; these metrics can be used to compare and evaluate countermeasures and are the building blocks for self-learning SARNETs that exhibit autonomous response. In this paper we present the software implementation of the SARNET framework, evaluate it in a real-life network and discuss the tradeoffs between parameters used by the SARNET agent and the efficiency of its actions.
AU - Koning, R.
AU - de Graaff, B.
AU - Polevoy, Gleb
AU - Meijer, R.
AU - de Laat, C.
AU - Grosso, P.
ID - 17666
JF - Future Generation Computer Systems
KW - Software defined networks
KW - Network function virtualization
KW - Cyber attacks
KW - Cyber security
KW - Defense efficiency
KW - Overlay networks
SN - 0167-739X
TI - Measuring the efficiency of SDN mitigations against attacks on computer infrastructures
ER -
TY - JOUR
AB - We study a new class of games which generalizes congestion games andits bottleneck variant. We introduce congestion games with mixed objectives to modelnetwork scenarios in which players seek to optimize for latency and bandwidths alike.We characterize the (non-)existence of pure Nash equilibria (PNE), the convergenceof improvement dynamics, the quality of equilibria and show the complexity of thedecision problem. For games that do not possess PNE we give bounds on the approx-imation ratio of approximate pure Nash equilibria.
AU - Feldotto, Matthias
AU - Leder, Lennart
AU - Skopalik, Alexander
ID - 669
IS - 4
JF - Journal of Combinatorial Optimization
SN - 1382-6905
TI - Congestion games with mixed objectives
VL - 36
ER -