Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of network topology have been generated to observe the effectiveness of proposed algorithms on different network architectures. The results reveal that RF performs better than KNN in a single topology, and both have close performance in other topologies.
One of the most important problems that faces the concrete industry in Iraq is the deterioration due to internal sulfate attack , since it reduces the compressive strength and increases the expansion of concrete. Consequently, the concrete structure may be damage .The effects of total and total effective sulfate contents on high strength concrete (HSC) have been studied in the present study. The research studied the effect of sulfate content in cement , sand and gravel , as well as comparing the total sulfate content with the total effective SO3 content. Materials used were divided into two groups of SO3 in cement ,three groups of SO3 in sand ,and two groups of SO3 in gravel. The results show that considering the total effective sulfate con
... Show MoreThe Pulse Coupled Oscillator (PCO) has attracted substantial attention and widely used in wireless sensor networks (WSNs), where it utilizes firefly synchronization to attract mating partners, similar to artificial occurrences that mimic natural phenomena. However, the PCO model might not be applicable for simultaneous transmission and data reception because of energy constraints. Thus, an energy-efficient pulse coupled oscillator (EEPCO) has been proposed, which employs the self-organizing method by combining biologically and non-biologically inspired network systems and has proven to reduce the transmission delay and energy consumption of sensor nodes. However, the EEPCO method has only been experimented in attack-free networks without
... Show MoreOne of the most important problems that faces the concrete industry in Iraq is the deterioration due to internal sulfate attack , since it reduces the compressive strength and increases the expansion of concrete. Consequently, the concrete structure may be damage .The effects of total and total effective sulfate contents on high strength concrete (HSC) have been studied in the present study.
The research studied the effect of sulfate content in cement , sand and gravel , as well as comparing the total sulfate content with the total effective SO3 content. Materials used were divided into two groups of SO3 in cement ,three groups of SO3 in sand ,and two groups of SO
... Show MoreIn this paper, a random transistor-transistor logic signal generator and a synchronization circuit are designed and implemented in lab-scale measurement device independent–quantum key distribution systems. The random operation of the weak coherent sources and the system’s synchronization signals were tested by a time to digital convertor.
In this paper, RBF-based multistage auto-encoders are used to detect IDS attacks. RBF has numerous applications in various actual life settings. The planned technique involves a two-part multistage auto-encoder and RBF. The multistage auto-encoder is applied to select top and sensitive features from input data. The selected features from the multistage auto-encoder is wired as input to the RBF and the RBF is trained to categorize the input data into two labels: attack or no attack. The experiment was realized using MATLAB2018 on a dataset comprising 175,341 case, each of which involves 42 features and is authenticated using 82,332 case. The developed approach here has been applied for the first time, to the knowledge of the authors, to dete
... Show MoreMost recent studies have focused on using modern intelligent techniques spatially, such as those
developed in the Intruder Detection Module (IDS). Such techniques have been built based on modern
artificial intelligence-based modules. Those modules act like a human brain. Thus, they should have had the
ability to learn and recognize what they had learned. The importance of developing such systems came after
the requests of customers and establishments to preserve their properties and avoid intruders’ damage. This
would be provided by an intelligent module that ensures the correct alarm. Thus, an interior visual intruder
detection module depending on Multi-Connect Architecture Associative Memory (MCA)
The purpose of this work is to study the classification and construction of (k,3)-arcs in the projective plane PG(2,7). We found that there are two (5,3)-arcs, four (6,3)-arcs, six (7,3)arcs, six (8,3)-arcs, seven (9,3)-arcs, six (10,3)-arcs and six (11,3)-arcs. All of these arcs are incomplete. The number of distinct (12,3)-arcs are six, two of them are complete. There are four distinct (13,3)-arcs, two of them are complete and one (14,3)-arc which is incomplete. There exists one complete (15,3)-arc.