A New Signature-Based Algorithms for Computing Gr?bner Bases

Gao, Volny and Wang （2010） gave a simple criterion for signature-based algorithms to compute GrSbner bases. It gives a unified frame work for computing GrSbner bases for both ideals and syzygies, the latter is very important in free resolutions in homological algebra. Sun and Wang （2011） later generalized the GVW criterion to a more general situation （to include the F5 Algorithm）. Signature-based algorithms have become increasingly popular for computing GrSbner bases. The current paper introduces a concept of factor pairs that can be used to detect more useless J-pairs than the generalized GVW criterion, thus improving signature-based algorithms.

HDLIDP: A Hybrid Deep Learning Intrusion Detection and Prevention Framework

Distributed denial-of-service(DDoS)attacks are designed to interrupt network services such as email servers and webpages in traditional computer networks.Furthermore,the enormous number of connected devices makes it difficult to operate such a network effectively.Software defined networks(SDN)are networks that are managed through a centralized control system,according to researchers.This controller is the brain of any SDN,composing the forwarding table of all data plane network switches.Despite the advantages of SDN controllers,DDoS attacks are easier to perpetrate than on traditional networks.Because the controller is a single point of failure,if it fails,the entire network will fail.This paper offers a Hybrid Deep Learning Intrusion Detection and Prevention(HDLIDP)framework,which blends signature-based and deep learning neural networks to detect and prevent intrusions.This framework improves detection accuracy while addressing all of the aforementioned problems.To validate the framework,experiments are done on both traditional and SDN datasets;the findings demonstrate a significant improvement in classification accuracy.

Features of Virus Detection Mechanism in Microsoft Security Essentials (Microsoft Forefront Endpoint Protection)

In this paper, a signature-based selective mechanism in detecting virus signatures in executable files was found and investigated. A pattern under which the Microsoft Security Essentials antivirus software not detecting a virus signature deliberately placed in files was revealed.

Speeding Up the GVW Algorithm via a Substituting Method

The GVW algorithm is an effcient signature-based algorithm for computing Gr?bner bases.In this paper, the authors consider the implementation of the GVW algorithm by using linear algebra,and speed up GVW via a substituting method. As it is well known that, most of the computing time of a Gr?bner basis is spent on reductions of polynomials. Thus, linear algebraic techniques, such as matrix operations, have been used extensively to speed up the implementations. Particularly, one-direction(also called signature-safe) reduction is used in signature-based algorithms, because polynomials(or rows in matrices) with larger signatures can only be reduced by polynomials(rows) with smaller signatures. The authors propose a new method to construct sparser matrices for signature-based algorithms via a substituting method. Speci?cally, instead of only storing the original polynomials in GVW, the authors also record many equivalent but sparser polynomials at the same time. In matrix construction, denser polynomials are substituted by sparser equivalent ones. As the matrices get sparser, they can be eliminated more effciently. Two speci?cal algorithms, Block-GVW and LMGVW, are presented, and their combination is the Sub-GVW algorithm. The correctness of the new proposed method is proved, and the experimental results demonstrate the effciency of this new method.