FPC: A New Approach to Firewall Policies Compression

Firewalls are crucial elements that enhance network security by examining the field values of every packet and deciding whether to accept or discard a packet according to the firewall policies. With the development of networks, the number of rules in firewalls has rapidly increased, consequently degrading network performance. In addition, because most real-life firewalls have been plagued with policy conflicts, malicious traffics can be allowed or legitimate traffics can be blocked. Moreover, because of the complexity of the firewall policies, it is very important to reduce the number of rules in a firewall while keeping the rule semantics unchanged and the target firewall rules conflict-free. In this study, we make three major contributions. First, we present a new approach in which a geometric model, multidimensional rectilinear polygon, is constructed for the firewall rules compression problem. Second, we propose a new scheme, Firewall Policies Compression (FPC), to compress the multidimensional firewall rules based on this geometric model. Third, we conducted extensive experiments to evaluate the performance of the proposed method. The experimental results demonstrate that the FPC method outperforms the existing approaches, in terms of compression ratio and efficiency while maintaining conflict-free firewall rules

A Survey on Approximation in Parameterized Complexity: Hardness and Algorithms

Parameterization and approximation are two popular ways of coping with NP-hard problems. More recently, the two have also been combined to derive many interesting results. We survey developments in the area both from the algorithmic and hardness perspectives, with emphasis on new techniques and potential future research directions

On Efficiently Solvable Cases of Quantum k-SAT

The constraint satisfaction problems k-SAT and Quantum k-SAT (k-QSAT) are canonical NP-complete and QMA_1-complete problems (for k >= 3), respectively, where QMA_1 is a quantum generalization of NP with one-sided error. Whereas k-SAT has been well-studied for special tractable cases, as well as from a parameterized complexity perspective, much less is known in similar settings for k-QSAT. Here, we study the open problem of computing satisfying assignments to k-QSAT instances which have a "matching" or "dimer covering"; this is an NP problem whose decision variant is trivial, but whose search complexity remains open. Our results fall into three directions, all of which relate to the "matching" setting: (1) We give a polynomial-time classical algorithm for k-QSAT when all qubits occur in at most two clauses. (2) We give a parameterized algorithm for k-QSAT instances from a certain non-trivial class, which allows us to obtain exponential speedups over brute force methods in some cases by reducing the problem to solving for a single root of a single univariate polynomial. (3) We conduct a structural graph theoretic study of 3-QSAT interaction graphs which have a "matching". We remark that the results of (2), in particular, introduce a number of new tools to the study of Quantum SAT, including graph theoretic concepts such as transfer filtrations and blow-ups from algebraic geometry; we hope these prove useful elsewhere

Cooperative area surveillance strategies using multiple unmanned systems

Recently, the U.S. Department of Defense placed the technological development of intelligence, surveillance, and reconnaissance (ISR) tools at the top of its priority list. Area surveillance that takes place in an urban setting is an ISR tool of special interest. Unmanned aerial vehicles (UAVs) are ideal candidates to perform area surveillance because they are inexpensive and they do not require a human pilot to be aboard. Multiple unmanned systems increase the rate of information flow from the target region and maintain up to date information. The purpose of the research described in this dissertation is to develop and test a system that coordinates multiple UAVs on a wide area coverage surveillance mission. The research presented in this document implements a waypoint generator for multiple aerial vehicles that is especially suited for large area surveillance. The system chooses initial locations for the vehicles and generates a set of balanced sub-trees which cover the region of interest (ROI) for the vehicles. The sub-trees are then optimally combined to form a single minimal tree that spans the entire region. The system transforms the tree path into a series of waypoints suitable for the aerial vehicles. The output of the system is a set of waypoints for each vehicle assigned to the coverage task. Results from computer simulation and flight testing are presented.Ph.D.Committee Chair: Dr. George Vachtsevanos; Committee Member: Ayanna Howard; Committee Member: Dr. Thomas Michaels; Committee Member: Eric Johnson; Committee Member: Linda Will