DSM: Delayed Signature Matching in Deep Packet Inspection

Deep Packet Inspection (DPI) is widely used in network management and network security systems. The core part of existing DPI is signature matching, and many researchers focus on improving the signature-matching algorithms. In this paper, we work from a different angle: The scheduling of signature matching. We propose a Delayed Signature Matching (DSM) method, in which we do not always immediately match received packets to the signatures since there may be not enough packets received yet. Instead, we predefine some rules, and evaluate the packets against these rules first to decide when to start signature matching and which signatures to match. The predefined rules are convenient to create and maintain since they support custom expressions and statements and can be created in a text rule file. The correctness and performance of the DSM method are theoretically analyzed as well. Finally, we implement a prototype of the DSM method in the open-source DPI library nDPI, and find that it can reduce the signature-matching time about 30∼84% in different datasets, with even smaller memory consumption. Note that the abstract syntax trees (ASTs) used to implement DSM rule evaluation are usually symmetric, and the DSM method supports asymmetric (i.e., single-direction) traffic as well.

Diffusion and economic growth fuzzy intelligent system based on DSGE model

In general, there are a lot of uncertainties in uncertain information, natural language, and human knowledge. The conclusion can be better deduced by using an approximate reasoning method, while a fuzzy intelligent system can deal with uncertain data and rule evaluation information systems. In order to better explore diffusion and economic growth, this paper constructs a fuzzy intelligent system based on the DSGE model and uses this system to analyze diffusion and economic growth. In order to verify the feasibility of this system, we test the response time and accuracy of the system. In addition, we also use the system to simulate diffusion and economic growth. The results show that with the increase of the task amount, the gap between the actual response time and the expected response time of the fuzzy intelligent system based on the DSGE model increases. When the task quantity is 20, the expected response time is 2.31 and the actual response time is 2.24. When the task quantity is 40, the expected response time is 2.5 and the actual response time is 2.36. The larger the task quantity is, the faster the response time of a fuzzy intelligent system based on the DSEG model is. Therefore, the fuzzy intelligent system based on the DSEG model has good performance and can analyze diffusion and economic growth well.

An Adaptive Hybrid Ant Colony Optimization Algorithm for The Classification Problem

Classification is an important data analysis and data mining technique. Taking into account the comprehensibility of the classifier generated, an adaptive hybrid ant colony optimization algorithm called A_HACO is proposed which can effectively solve classification problem and get the comprehensible classification rules at the same time. The algorithm incorporates the artificial bee colony optimization strategy into the ant colony algorithm. The ant colony global optimization process is used to adaptively select the appropriate rule evaluation function for the data set given. Based on the classification rules obtained, the artificial bee colony optimization strategy is used to tackle the continuous attributes for further optimization of classification rules. This approach is evaluated experimentally using different standard real datasets, and compared with some proposed related classification algorithms. It shows that A_HACO can adaptively select the appropriate rule evaluation function and has better accuracy compared with related works.

RANCANG BANGUN SISTEM PENDETEKSI KEBAKARAN DINI BERBASIS LOGIKA FUZZY MENGGUNAKAN MULTISENSOR

At Indonesia, cases of residential house fires are still rampant. This resulted in considerable losses for the population of Indonesia. If there is no prevention or countermeasure, it is possible that the danger of a house fires will continue. Therefore, this system exists to create a condition where the system is able to detect the potential that will bring a fire hazard. In this system using a method that is the application of a multisensory system in detecting the presence of fire, smoke and temperature in the room. The sensors used include KY-026 fire sensor, MQ-9 smoke sensor and DS18B20 temperature sensor. Then the system also implements an intelligent system that is fuzzy logic to process sensor reading data. The three sensor inputs will be processed through the fuzzification stage, rule evaluation and the deffuzification. The output of this system is in the form of firm values, namely the values 1 to 5 from the results of the multisensory defuzzification in each module. So the error of the defuzzification average is 0.99% after being compared with the MATLAB output. This system is expected to be able to provide early warning of the threat of fire, reduce the risk of casualties, and be able to be implemented to a wider scale or scope.

Diamonds Colour Measurements

As a rule, evaluation of diamond colour is carrying out visually, because creation of the measuring devices is a complex problem due to influence of defects in diamonds (irregularity of coloration, cracks and graphite inclusions). And elimination of this influence is a very difficult task. In this work, an analysis of visual diamond colour evaluation methods and assessment of known devices for objective diamond colour measurements is carried out. As a result, an installation for measuring diamond colour is offered, which as much as possible meets the visual evaluation conditions.