196 research outputs found
On the Complexity of -Closeness Anonymization and Related Problems
An important issue in releasing individual data is to protect the sensitive
information from being leaked and maliciously utilized. Famous privacy
preserving principles that aim to ensure both data privacy and data integrity,
such as -anonymity and -diversity, have been extensively studied both
theoretically and empirically. Nonetheless, these widely-adopted principles are
still insufficient to prevent attribute disclosure if the attacker has partial
knowledge about the overall sensitive data distribution. The -closeness
principle has been proposed to fix this, which also has the benefit of
supporting numerical sensitive attributes. However, in contrast to
-anonymity and -diversity, the theoretical aspect of -closeness has
not been well investigated.
We initiate the first systematic theoretical study on the -closeness
principle under the commonly-used attribute suppression model. We prove that
for every constant such that , it is NP-hard to find an optimal
-closeness generalization of a given table. The proof consists of several
reductions each of which works for different values of , which together
cover the full range. To complement this negative result, we also provide exact
and fixed-parameter algorithms. Finally, we answer some open questions
regarding the complexity of -anonymity and -diversity left in the
literature.Comment: An extended abstract to appear in DASFAA 201
Computational Complexity Characterization of Protecting Elections from Bribery
The bribery problem in election has received considerable attention in the
literature, upon which various algorithmic and complexity results have been
obtained. It is thus natural to ask whether we can protect an election from
potential bribery. We assume that the protector can protect a voter with some
cost (e.g., by isolating the voter from potential bribers). A protected voter
cannot be bribed. Under this setting, we consider the following bi-level
decision problem: Is it possible for the protector to protect a proper subset
of voters such that no briber with a fixed budget on bribery can alter the
election result? The goal of this paper is to give a full picture on the
complexity of protection problems. We give an extensive study on the protection
problem and provide algorithmic and complexity results. Comparing our results
with that on the bribery problems, we observe that the protection problem is in
general significantly harder. Indeed, it becomes -complete even for
very restricted special cases, while most bribery problems lie in NP. However,
it is not necessarily the case that the protection problem is always harder.
Some of the protection problems can still be solved in polynomial time, while
some of them remain as hard as the bribery problem under the same setting.Comment: 28 Pages. The Article has been accepted in the 26th International
Computing and Combinatorics Conference (COCOON 2020
Combinatorial Voter Control in Elections
Voter control problems model situations such as an external agent trying to
affect the result of an election by adding voters, for example by convincing
some voters to vote who would otherwise not attend the election. Traditionally,
voters are added one at a time, with the goal of making a distinguished
alternative win by adding a minimum number of voters. In this paper, we
initiate the study of combinatorial variants of control by adding voters: In
our setting, when we choose to add a voter~, we also have to add a whole
bundle of voters associated with . We study the computational
complexity of this problem for two of the most basic voting rules, namely the
Plurality rule and the Condorcet rule.Comment: An extended abstract appears in MFCS 201
A Multivariate Complexity Analysis of the Material Consumption Scheduling Problem
The NP-hard MATERIAL CONSUMPTION SCHEDULING Problem and closely related
problems have been thoroughly studied since the 1980's. Roughly speaking, the
problem deals with minimizing the makespan when scheduling jobs that consume
non-renewable resources. We focus on the single-machine case without
preemption: from time to time, the resources of the machine are (partially)
replenished, thus allowing for meeting a necessary pre-condition for processing
further jobs, each of which having individual resource demands. We initiate a
systematic exploration of the parameterized (exact) complexity landscape of the
problem, providing parameterized tractability as well as intractability
results. Doing so, we mainly investigate how parameters related to the resource
supplies influence the computational solvability. Thereby, we get a deepened
understanding of the algorithmic complexity of this fundamental scheduling
problem.Comment: Accepted for publication in The Thirty-Fifth AAAI Conference on
Artificial Intelligence (AAAI-21
A multivariate complexity analysis of the material consumption scheduling problem
The NP-hard problem Material Consumption Scheduling and related problems have been thoroughly studied since the 1980âs. Roughly speaking, the problem deals with scheduling jobs that consume non-renewable resourcesâeach job has individual resource demands. The goal is to minimize the makespan. We focus on the single-machine case without preemption: from time to time, the resources of the machine are (partially) replenished, thus allowing for meeting a necessary precondition for processing further jobs. We initiate a systematic exploration of the parameterized computational complexity landscape of Material Consumption Scheduling , providing parameterized tractability as well as intractability results. Doing so, we mainly investigate how parameters related to the resource supplies influence the problemâs computational complexity. This leads to a deepened understanding of this fundamental scheduling problem
Graph editing to a given degree sequence
We investigate the parameterized complexity of the graph editing problem called Editing to a Graph with a Given Degree Sequence where the aim is to obtain a graph with a given degree sequence Ï by at most k vertex deletions, edge deletions and edge additions. We show that the problem is W[1]-hard when parameterized by k for any combination of the allowed editing operations. From the positive side, we show that the problem can be solved in time 2O(k(Îâ+k)2)n2logâĄn for n -vertex graphs, where Îâ=maxâĄÏ, i.e., the problem is FPT when parameterized by k+Îâ. We also show that Editing to a Graph with a Given Degree Sequence has a polynomial kernel when parameterized by k+Îâ if only edge additions are allowed, and there is no polynomial kernel unless NPâco-NP/poly for all other combinations of the allowed editing operations
The effect of homogeneity on the computational complexity of combinatorial data anonymization
Manipulating opinion diffusion in social networks
We consider opinion diffusion in binary influence networks, where at each step one or more agents update their opinions so as to be in agreement with the majority of their neighbors. We consider several ways of manipulating the majority opinion in a stable outcome, such as bribing agents, adding/deleting links, and changing the order of updates, and investigate the computational complexity of the associated problems, identifying tractable and intractable cases
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