Research Interests:
Research Interests:
As the Covid-19 outbreak spreads across the globe and has killed many lives, many applications have been created to track patients and fight this pandemic. However, several applications lack safety and privacy. This paper designs and... more
As the Covid-19 outbreak spreads across the globe and has killed many lives, many applications have been created to track patients and fight this pandemic. However, several applications lack safety and privacy. This paper designs and develops a mobile app to track patients with the Covid-19 or any other pandemic disease through using GPS in Iraq. Moreover, the app maintains a privacy for users by encrypting their personal data before sending them to the cloud using a MODE CBC AES block encryption algorithm. The app keeps the identity and location of the users, supports two language interfaces English and Arabic, and works in Android and iOS environments. Only the health care providers can decrypt these data and know about the patient's location. Also, to make the patient trusts the application, his/her information will be deleted after sending his/her negative test after 21 days. In addition, the app provides users with information regarding healthcare places in the case of emergency. For the evaluation of this app, a data was collected from 20 users, including males and females and their ages were between (20–50) in Mosul city. The results showed that the app works properly and the users are notified when they are in close with other registered infected people. In addition, the users found that the app was simple, easy to use, and useful to do contact safely. To convince the users to utilize this app, the app is provided with button trial option to try it.
Research Interests:
Information security is one of the most significant processes that must be taken into account when confidentially transferring information. This paper introduces a steganography technique using the edge detection method. It focused on... more
Information security is one of the most significant processes that must be taken into account when confidentially transferring information. This paper introduces a steganography technique using the edge detection method. It focused on three basic and important aspects’ payload, quality and security. Well-known edge detectors were used to generate as many edge pixels as possible to hide data and achieve the highest payload. The least significant bit (LSB) algorithm has been improved by extending the bits used to embed between 2-4 bits in smooth and sharp areas. To increase security, the transaction between the two parties is based on dividing the key and the cover image into several parts and agreeing on the type of edge detection.The experiments achieved the maximum load, for instance with a fuzzy edge detector, at first, embedding in 4 bitplanes if edge pixel and in 2 bitplanes if non-edge pixel, the peak signal-to-noise ratio (PSNR) increased from 43.580to 45.790. At second, embed...
In recent years, the trend has increased for the use of cloud computing, which provides broad capabilities with the sharing of resources, and thus it is possible to store and process data in the cloud remotely, but this (cloud) is... more
In recent years, the trend has increased for the use of cloud computing, which provides broad capabilities with the sharing of resources, and thus it is possible to store and process data in the cloud remotely, but this (cloud) is untrusted because some parties can connect to the network such as the internet and read or change data because it is not protected, therefore, protecting data security and privacy is one of the challenges that must be addressed when using cloud computing. Encryption is interested in the field of security, confidentiality and integrity of information that sent by a secure connection between individuals or institutions regardless of the method used to prepare this connection. But using the traditional encryption methods to encrypt the data before sending it will force the data provider to send his private key to the server to decrypt the data to perform computations on it. In this paper we present a proposal to secure banking data transmission through the cl...
Research Interests:
Many real world problems involve the simultaneous optimization of various and often conflicting objectives. Evolutionary algorithms seem to be the most attractive approaches for this class of problems, because they are usually population... more
Many real world problems involve the simultaneous optimization of various and often conflicting objectives. Evolutionary algorithms seem to be the most attractive approaches for this class of problems, because they are usually population based techniques that can find multiple compromise solution in a single run, and they do not require any hypotheses on the objective functions. Among other techniques, in the last decade a new paradigm based on the emulation of the immune system behavior has been proposed. Since the pioneer works, many different implementations have been proposed in literatures. This Paper presents a description of an intrusion detection approach modeled on the basis of three bio-inspired concepts namely, Negative selection, Positive selection and complement system. The Positive selection mechanism of the immune system can detect the attack patterns (nonself), while the Negative selection mechanism of the immune system can delete the Artificial lymphocyte (ALC) whic...
Research Interests:
While data is used in cooperative milieus for information extraction; Thus, it is vulnerable to security threats concerning ownership rights and data abusing. Due to unauthorized access to the data that may alter the originality, it... more
While data is used in cooperative milieus for information extraction; Thus, it is vulnerable to security threats concerning ownership rights and data abusing. Due to unauthorized access to the data that may alter the originality, it results in significant losses of the organization. The relational databases which are free on-hand are used by research society for mining new information regarding their research works. These databases are vulnerable to security issues. The reliability of the data source must be authenticated before using it for any application purpose. Thus, to check the ownership and reliability of data, watermarking is applied to the data. Watermarking is used for the protection of the possession rights of shared Relational Data and for providing the solution for manipulating and tampering of data.
The web has turned into a principal part of our conventional social and financial activities. The web isn't significant for singular clients just yet additionally for associations, since associations that offer web-based exchanging... more
The web has turned into a principal part of our conventional social and financial activities. The web isn't significant for singular clients just yet additionally for associations, since associations that offer web-based exchanging can accomplish an upper hand by serving overall customers. Webworks arriving at clients all around the globe with no commercial center limitations and with successful utilization of internet business. Consequently, Internet customers may be defenceless against different kinds of web risks, that may cause financial damages, information forgery, brand reputation mischief, the sacrifice of private information, and loss of customers' confidence in online business and electronic banking. Thusly, the reasonableness of the Internet for business exchanges becomes dubious. Phishing is seen as a design of web peril which is classified as the forte of mimicking a website of a legitimate undertaking proposing to gain a client's private accreditations, for...
Research Interests:
Electronic systems are considered one of the most important pillars in the development of the work of any institution, especially the systems related to the administrative and financial aspects. In this research, an electronic system for... more
Electronic systems are considered one of the most important pillars in the development of the work of any institution, especially the systems related to the administrative and financial aspects. In this research, an electronic system for salaries for the Nineveh Investment Commission (NIC) was designed and implemented model using the language (C#), A central database was built using a Database Management System (SQL), This system was based on a local wireless network to share work by adopting (Client/Server) model to connect the computers, the proposed system includes very important features such as the open system data that enables the user to add and amend the percentages of the basic and secondary salary components, automatic calculation of the salary by specifying the employee service specifications and the certificate obtained, fixed and variable allocations and deductions, calculating all leave, Determining annual bonuses and promotions and organizing them to makes it easy for the user to know who is eligible, update and calculate them, in this system several levels of system users were built. A report was added for the employee's last salary certificate with detailed reports on salaries and the system was strengthened with the feature of backing up to prevent the database from Damage and referred to at any time. The system was tested on real data to issuing salary reports for three months. As the system met with great desire and reliability in its use by conducting a questionnaire to measure the usability of the system on the specialists.
Research Interests:
The aim of this study, is the diagnosis of Congenital Dislocation of the Hip (CDH) from routine X-Ray Image by measuring the retardation of the growth center of the head of femur bone in the abnormal joint in comparison with the normal... more
The aim of this study, is the diagnosis of Congenital Dislocation of the Hip (CDH) from routine X-Ray Image by measuring the retardation of the growth center of the head of femur bone in the abnormal joint in comparison with the normal side in cases of ...
With the development of communication technologies for mobile devices and electronic communications, and went to the world of e-government, e-commerce and e-banking. It became necessary to control these activities from exposure to... more
With the development of communication technologies for mobile devices and
electronic communications, and went to the world of e-government, e-commerce and
e-banking. It became necessary to control these activities from exposure to intrusion
or misuse and to provide protection to them, so it's important to design powerful and
efficient systems-do-this-purpose.
It this paper it has been used several varieties of algorithm selection passive
immune algorithm selection passive with real values, algorithm selection with passive
detectors with a radius fixed, algorithm selection with passive detectors, variablesized intrusion detection network type misuse where the algorithm generates a set of
detectors to distinguish the self-samples.
Practical Experiments showed the process to achieve a high rate of detection in
the system designer using data NSL-KDD with 12 field without vulnerability to
change the radius of the detector or change the number of reagents were obtained as
the ratio between detection (0.984, 0.998, 0.999) and the ratio between a false alarm
(0.003, 0.002, 0.001). Contrary to the results of experiments conducted on data NSLKDD with 41 field contact, which affected the rate of detection by changing the
radius and the number of the detector as it has been to get the proportion of uncovered
between (0.44, 0.824, 0.992) and the percentage of false alarm between (0.5, 0.175,
0.003).
electronic communications, and went to the world of e-government, e-commerce and
e-banking. It became necessary to control these activities from exposure to intrusion
or misuse and to provide protection to them, so it's important to design powerful and
efficient systems-do-this-purpose.
It this paper it has been used several varieties of algorithm selection passive
immune algorithm selection passive with real values, algorithm selection with passive
detectors with a radius fixed, algorithm selection with passive detectors, variablesized intrusion detection network type misuse where the algorithm generates a set of
detectors to distinguish the self-samples.
Practical Experiments showed the process to achieve a high rate of detection in
the system designer using data NSL-KDD with 12 field without vulnerability to
change the radius of the detector or change the number of reagents were obtained as
the ratio between detection (0.984, 0.998, 0.999) and the ratio between a false alarm
(0.003, 0.002, 0.001). Contrary to the results of experiments conducted on data NSLKDD with 41 field contact, which affected the rate of detection by changing the
radius and the number of the detector as it has been to get the proportion of uncovered
between (0.44, 0.824, 0.992) and the percentage of false alarm between (0.5, 0.175,
0.003).
Research Interests:
The goal of this study, is to use Mask Technique and Center Detection for developmental dysplasia of the Hip (DDH) diagnosis [7] which aims at calculating center and diameter of Head of Femur to diagnose some of the effects of... more
The goal of this study, is to use Mask Technique and Center Detection for developmental dysplasia of the Hip (DDH) diagnosis [7] which aims at calculating center and diameter of Head of Femur to diagnose some of the effects of Developmental Dysplasia of the Hip (DDH) on the hip joint. This study uses the Mask Technique and Center detection to complete the calculation of the acetabular angle and the distance of the head of femur from acetabulum. These two new criteria give the doctor very valuable information in the diagnosis of DDH and its degree. An algorithm is designed to do the following steps: 1. Exploring the details of the X-Ray and cutting out the necessary parts (acetabular bone and head of femur) for the desired side (right or left) instead of using the complete image. 2. Enhance the cropped parts by using Contrast linear stretching, Median filter and Canny edge detection. 3. Search for the center of the head of femur and calculate its diameter. 4. Measure the angle of acetabular bone and measure the distance from head of femur to acetabular bone. At last the features are extracted (Center of head of femur, Intensity value of the center, Diameter of head of femur, angle of acetabulum and distance from head of femur to the acetabulum, place in acetabulum bone). We applied this system in computer using Matlab 7.0 programming Langue.
Research Interests:
Simultaneously with the development of networks, and with the increasing volume of unsolicited bulk e-mail especially advertising, indiscriminately has generated a need for reliable anti-spam filters. The problem for the traditional... more
Simultaneously with the development of networks, and with the increasing volume of unsolicited bulk e-mail especially advertising, indiscriminately has generated a need for reliable anti-spam filters. The problem for the traditional method of spam filtering cannot effectively identify the unknown and variation characteristics, therefore recently the researchers look at the artificial immune system exists diversity, immune memory, adaptive and self learning ability. The spam detection model describes an e-mail filtering is accomplished by extracting the characteristics of spam and ham (legitimate e-mail messages that is generally desired and isn't considered spam) that is been acquired from trained data set by feature extraction techniques. These techniques allowed to select subset of relevant, non redundant and most contributing features to have an added benefit in accuracy and reduced time complexity. The extracted features of spam and ham are then make a two types of antigen detectors, to enter then in series of cloning and mutation immune operations to built an immune memory of spam and ham. The experimental result confirms that the proposed model has a very high detection rate reach at 1 and a very low false alarm rate reach at 0 when using low numbers of feature extraction. General Terms Artificial Immune System (AIS), Feature Extraction Techniques and Security.
Research Interests:
The attackers do not want their Malicious software (or malwares) to be reviled by anti-virus analyzer. In order to conceal their malware, malware programmers are getting utilize the anti reverse engineering techniques and code changing... more
The attackers do not want their Malicious software (or malwares) to be reviled by anti-virus analyzer. In order to conceal their malware, malware programmers are getting utilize the anti reverse engineering techniques and code changing techniques such as the packing, encoding and encryption techniques. Malware writers have learned that signature based detectors can be easily evaded by "packing" the malicious payload in layers of compression or encryption. State-of-the-art malware detectors have adopted both static and dynamic techniques to recover the payload of packed malware, but unfortunately such techniques are highly ineffective. If the malware is packed or encrypted, then it is very difficult to analyze. Therefore, to prevent the harmful effects of malware and to generate signatures for malware detection, the packed and encrypted executable codes must initially be unpacked. The first step of unpacking is to detect the packed executable files. The objective is to efficiently and accurately distinguish between packed and non-packed executables, so that only executables detected as packed will be sent to an general unpacker, thus saving a significant amount of processing time. The generic method of this paper show that it achieves very high detection accuracy of packed executables with a low average processing time. In this paper, a packed file detection technique based on complexity measured by several algorithms, and it has tested using a packed and unpacked dataset of file type .exe. The preliminary results are very promising where achieved high accuracy with enough performance. Where it achieved about 96% detection rate on packed files and 93% detection rate on unpacked files. The experiments also demonstrate that this generic technique can effectively prepared to detect unknown, obfuscated malware and cannot be evaded by known evade techniques.
Research Interests:
The use of artificial immune systems in intrusion detection is an appealing concept for two reasons. Firstly, the human immune system provides the human body with a high level of protection from invading pathogens, in a robust,... more
The use of artificial immune systems in intrusion
detection is an appealing concept for two reasons. Firstly, the
human immune system provides the human body with a high
level of protection from invading pathogens, in a robust, selforganized and distributed manner. Secondly, current
techniques used in computer security are not able to cope with
the dynamic and increasingly complex nature of computer
systems and their security.
The objective of our system is to combine several
immunological metaphors in order to develop a forbidding
IDS. The inspiration come from: (1) Adaptive immunity
which is characterized by learning, adaptability, and memory
and is broadly divided into two branches: humoral and cellular
immunity. And (2) The analogy of the human immune systems
multilevel defense could be extended further to the intrusion
detection system itself. This is also the objective of intrusion
detection which need multiple detection mechanisms to obtain
a very high detection rate with a very low false alarm rate.
detection is an appealing concept for two reasons. Firstly, the
human immune system provides the human body with a high
level of protection from invading pathogens, in a robust, selforganized and distributed manner. Secondly, current
techniques used in computer security are not able to cope with
the dynamic and increasingly complex nature of computer
systems and their security.
The objective of our system is to combine several
immunological metaphors in order to develop a forbidding
IDS. The inspiration come from: (1) Adaptive immunity
which is characterized by learning, adaptability, and memory
and is broadly divided into two branches: humoral and cellular
immunity. And (2) The analogy of the human immune systems
multilevel defense could be extended further to the intrusion
detection system itself. This is also the objective of intrusion
detection which need multiple detection mechanisms to obtain
a very high detection rate with a very low false alarm rate.
Research Interests:
Most signature−based antivirus products are effective to detect known malwares but not unknown malwares or malwares' variants, which make them often lag behind malwares. Also most antivirus approaches are complex for two reasons. First,... more
Most signature−based antivirus products are effective to detect known malwares but not unknown malwares or malwares' variants, which make them often lag behind malwares. Also most antivirus approaches are complex for two reasons. First, lots of malicious and benign codes as training dataset are difficult to collect. Second, they would consume lots of times when training classifiers. Immunity PE Malware Detection System (IPEMDS) was designed to give computer systems PE homeostatic capabilities analogous to those of the human immune system. Because the constraints of living and computational systems are very different, however, we cannot create a useful computer security mechanism by merely imitating biology. IPEMDS approach has been first to choose a set of requirements similar to those of the immune system. It then created abstractions that captured some of the important characteristics of biological homeostatic systems and then used these abstractions to guide the design of two levels of defense called them IPEMDS. The goal of IPEMDS are to obtain high detection rate and a very low false positive. IPEMDS enter in a challenge to a chief this goal from depending only on a finite numbers of benign files to classify between a new benign and malware executable files, and both of them unseen before by IPEMDS.
Research Interests:
Many real world problems involve the simultaneous optimization of various and often conflicting objectives. Evolutionary algorithms seem to be the most attractive approaches for this class of problems, because they are usually population... more
Many real world problems involve the simultaneous optimization of various and often conflicting objectives. Evolutionary algorithms seem to be the most attractive approaches for this class of problems, because they are usually population based techniques that can find multiple compromise solution in a single run, and they do not require any hypotheses on the objective functions. Among other techniques, in the last decade a new paradigm based on the emulation of the immune system behavior has been proposed. Since the pioneer works, many different implementations have been proposed in literatures. This Paper presents a description of an intrusion detection approach modeled on the basis of three bio-inspired concepts namely, Negative selection, Positive selection and complement system. The Positive selection mechanism of the immune system can detect the attack patterns (nonself), while the Negative selection mechanism of the immune system can delete the Artificial lymphocyte (ALC) which interact with normal patterns (Self). The complement system is a kind of the effecter mechanism, which refers to a series of proteins circulating in the blood and bathing the fluids surrounding tissues. It establishes the idea that only those cells that recognize the antigens are selected to undergo two operators: cleave operator and bind operator are presented, cleave operator cleaves a complement cell into two sub-cells, while bind operator binds Najlaa B. Aldabagh & Mafaz M. Khalil 110 two cells together and forms a big cell. To obtain Complement detectors can recognize only the attack patterns from the NSL-KDD dataset.
Research Interests:
This paper compares between two models: Common Genetic algorithm and the new Clonal selection theory in the field of Intrusion Detection. Genetic algorithms (GA) which is a model of genetic evolution, while Clonal selection theory (CST)... more
This paper compares between two models: Common Genetic algorithm and the new Clonal selection theory in the field of Intrusion Detection. Genetic algorithms (GA) which is a model of genetic evolution, while Clonal selection theory (CST) is from models of the natural immune system NIS, the two models are from two different fields of Artificial Intelligence AI but they have portion of shared operations and objectives. The comparison to be done by applying the two models on some records of Knowledge Discovery and Data mining tools which is known by the name KDD data sets (its records the data of the interring packets to the computer system from the internet), to produce population (in case of GA) or antibodies (in case of CST) can recognize these abnormal records. ﻤﺠﻤﻭﻋﺔ ﻋﻠﻰ ﺍﻟﺴﻼﻟﺔ ﺇﻨﺘﻘﺎﺀ ﻭﻨﻅﺭﻴﺔ ﺍﻟﺠﻴﻨﻴﺔ ﺍﻟﺨﻭﺍﺭﺯﻤﻴﺔ ﺒﻴﻥ ﻋﻤﻠﻴﺔ ﻤﻘﺎﺭﻨﺔ ﺒﻴﺎﻨﺎﺕ KDD ﺃ. ﺩ. ﺍﻟﺩﺒﺎﻍ ﺒﺩﻴﻊ ﻨﺠﻼﺀ ﻡ ﻤﺴﺎﻋﺩ ﺃﺴﺘﺎﺫ ﻭﺍﻟﺭﻴﺎﻀﻴﺎﺕ ﺍﻟﺤﺎﺴﺒﺎﺕ ﻋﻠﻭﻡ ﻜﻠﻴﺔ / ﺤﺎﺴﺒﺎﺕ ﻋﻠﻭﻡ ﺨﻠﻴل ﻤﺤﺴﻥ ﻤﻔﺎﺯ ﻤﺴﺎﻋﺩ ﻤﺩﺭﺱ ﺍﻟﻌﻠﻭﻡ ﻜﻠﻴﺔ / ﺤﻴﺎﺓ ﻋﻠﻭﻡ ﺍﻟﻤﻠﺨﺹ ﻨﻤﻭﺫﺠﺎﻥ ﻤﺎﺒﻴﻥ ﺍﻟﺒﺤﺙ ﻫﺫﺍ ﻴﻘﺎﺭﻥ : ﺍﻟـﺴﻼﻟﺔ ﺍﻨﺘﻘـﺎﺀ ﻭﻨـﻀﺭﻴﺔ ﺍﻟﻤﻌﺭﻭﻓﺔ ﺍﻟﺠﻴﻨﻴﺔ ﺍﻟﺨﻭﺍﺭﺯﻤﻴﺔ ﺍﻟﺘﻁﻔل ﻜﺸﻑ ﻤﺠﺎل ﻓﻲ ﺍﻟﺠﺩﻴﺩﺓ. ﺘﻌﺘﺒﺭ ﺤﻴﺙ ﺍﻟﺠﻴﻨﻴﺔ ﺍﻟﺨﻭﺍﺭﺯﻤﻴﺔ) GA (،ﺍﻟﺠﻴﻨﻲ ﻟﻠﺘﻁﻭﺭ ﻨﻤﻭﺫﺝ ﺒﻴﻨﻤﺎ ﺍﻟﺴﻼﻟﺔ ﺍﻨﺘﻘﺎﺀ ﻨﻅﺭﻴﺔ ﺘﻌﺘﺒﺭ) CST (ﺤﻘﻠﻴﻥ ﻤﻥ ﺃﻨﻬﻤﺎ ﺃﻱ ،ﺍﻟﻁﺒﻴﻌﻲ ﺍﻟﻤﻨﺎﻋﺔ ﻨﻅﺎﻡ ﻨﻤﺎﺫﺝ ﻤﻥ ﻤﺨﺘﻠﻔـﻴﻥ ﺍﻟﻤﺸﺘﺭﻜﺔ ﻭﺍﻻﻫﺩﺍﻑ ﺍﻟﻌﻤﻠﻴﺎﺕ ﺒﻌﺽ ﻟﺩﻴﻬﻤﺎ ﻭﻟﻜﻥ ﺍﻻﺼﻁﻨﺎﻋﻲ ﻟﻠﺫﻜﺎﺀ. ﺍﻟﻨﻤﻭﺫﺠﺎﻥ ﺒﺘﻁﺒﻴﻕ ﺍﻟﻤﻘﺎﺭﻨﺔ ﺘﻤﺕ ﺍﻟـ ﺒﻴﺎﻨﺎﺕ ﻤﺠﻤﻭﻋﺎﺕ ﺴﺠﻼﺕ ﺒﻌﺽ ﻋﻠﻰ KDD) ﺍﻟﺩﺍﺨﻠـﺔ ﺍﻟﺤﺯﻡ ﺒﻴﺎﻨﺎﺕ ﺘﺴﺠل ﺍﻟﺘﻲ ﻨﻅـﺎﻡ ﺇﻟـﻰ ﺍﻹﻨﺘﺭﻨﺕ ﺨﻼل ﻤﻥ ﺍﻟﺤﺎﺴﻭﺏ (ﺠﻴل ﻹﻨﺘﺎﺝ ،) ﺍﻟﺠﻴﻨﻴﺔ ﺍﻟﺨﻭﺍﺭﺯﻤﻴﺔ ﺤﺎﻟﺔ ﻓﻲ (ﺤﻴـﺔ ﻤﻀﺎﺩﺍﺕ ﺃﻭ Abs) ﺤﺎﻟﺔ ﻓﻲ ﺍﻟﺴﻼﻟﺔ ﺍﻨﺘﻘﺎﺀ ﻨﻅﺭﻴﺔ (ﺍﻟﻤﻬﺎﺠﻤﺔ ﺃﻭ ﻁﺒﻴﻌﻴﺔ ﺍﻟﻐﻴﺭ ﺍﻟﺴﺠﻼﺕ ﺘﻤﻴﺯ ﻴﻤﻜﻨﻬﻤﺎ .
Research Interests:
Studies of ant colonies have contributed in abundance to the set of intelligent algorithms. The modeling of pheromone depositing by ants in their search for the shortest paths to food sources resulted in the development of shortest path... more
Studies of ant colonies have contributed in abundance to the set of intelligent algorithms. The modeling of pheromone depositing by ants in their search for the shortest paths to food sources resulted in the development of shortest path optimization algorithms. Ant colony optimization (ACO) algorithms have been successfully applied to combinatorial optimization tasks especially to data mining classification problem. Internet and local networks have become everywhere. So organizations are increasingly employing various systems that monitor IT security breaches because intrusion events are growing day by day. Ant-based algorithms or ant colony optimization (ACO) algorithms can be applied to the data mining field to extract rule-based classifiers and have been applied successfully to combinatorial optimization problems. More recently, researches applied ACO to data mining classification problems, where they introduced a classification algorithm called Ant-Miner algorithm. The Ant-Miner algorithm is based on the behavior of ants in searching of food. The aim of this paper is to use an Ant Colony-based classification system (Ant_Miner algorithm) to extract a set of rules for detection and classification, and it obtained a hopeful classification accuracy.. .
Research Interests:
Research Interests:
Studies of ant colonies have contributed in abundance to the set of intelligent algorithms. The modeling of pheromone depositing by ants in their search for the shortest paths to food sources resulted in the development of shortest path... more
Studies of ant colonies have contributed in abundance to the set of intelligent algorithms. The modeling of pheromone depositing by ants in their search for the shortest paths to food sources resulted in the development of shortest path optimization algorithms. Ant colony optimization (ACO) algorithms have been successfully applied to combinatorial optimization tasks especially to data mining classification problem. Internet and local networks have become everywhere. So organizations are increasingly employing various systems that monitor IT security breaches because intrusion events are growing day by day. Ant-based algorithms or ant colony optimization (ACO) algorithms can be applied to the data mining field to extract rule-based classifiers and have been applied successfully to combinatorial optimization problems. More recently, researches applied ACO to data mining classification problems, where they introduced a classification algorithm called Ant-Miner algorithm. The Ant-Miner algorithm is based on the behavior of ants in searching of food. The aim of this paper is to use an Ant Colony-based classification system (Ant_Miner algorithm) to extract a set of rules for detection and classification, and it obtained a hopeful classification accuracy.
Research Interests:
Research Interests:
DOAJ Directory of Open Access Journals, SPARC Europe Award 2009 English. Free, full text, quality controlled scientific and scholarly journals, covering all subjects and many languages. ...
Research Interests:
DOAJ Directory of Open Access Journals, SPARC Europe Award 2009 English. Free, full text, quality controlled scientific and scholarly journals, covering all subjects and many languages. ...
Research Interests:
The goal of this study, is to use Mask Technique and Center Detection for developmental dysplasia of the Hip (DDH) diagnosis [7] which aims at calculating center and diameter of Head of Femur to diagnose some of the effects of... more
The goal of this study, is to use Mask Technique and Center Detection for developmental dysplasia of the Hip (DDH) diagnosis [7] which aims at calculating center and diameter of Head of Femur to diagnose some of the effects of Developmental Dysplasia of the Hip (DDH) on the hip joint. This study uses the Mask Technique and Center detection to complete the calculation of the acetabular angle and the distance of the head of femur from acetabulum. These two new criteria give the doctor very valuable information in the diagnosis of DDH and its degree. An algorithm is designed to do the following steps: 1. Exploring the details of the X-Ray and cutting out the necessary parts (acetabular bone and head of femur) for the desired side (right or left) instead of using the complete image. 2. Enhance the cropped parts by using Contrast linear stretching, Median filter and Canny edge detection. 3. Search for the center of the head of femur and calculate its diameter. 4. Measure the angle of acetabular bone and measure the distance from head of femur to acetabular bone. At last the features are extracted (Center of head of femur, Intensity value of the center, Diameter of head of femur, angle of acetabulum and distance from head of femur to the acetabulum, place in acetabulum bone). We applied this system in computer using Matlab 7.0 programming Langue.
Research Interests:
Research Interests:
Research Interests:
The previous decade has seen the growth of interest with networks and participatory social media that have brought users jointly in many originative ways. Many users play, categorize, work and socialize online, showing new forms of... more
The previous decade has seen the growth of interest with networks and participatory social media that have brought users jointly in many originative ways. Many users play, categorize, work and socialize online, showing new forms of cooperation, communication, and cleverness that were hard to imagine just a while ago. Social media refers to the interaction between people who create, share information and ideas in communities and virtual networks. Social media also helps reform business models, influence views and sentiments, and opens many possibilities for studying human interaction and mass conduct on an unprecedented level. This research employs visual representation of data and cluster algorithms for discovering patterns in the Facebook network to learn some of the behaviors practiced by community members. The results can be used to find out users directions to suggest appropriate advertisements for it, and cluster algorithms can be used to collect suspicious and inappropriate co...
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Tracking individuals in social networks is one of the challenging tasks in digital forensics. In social networks, individuals' behavior can be predicted or measured based on their online interactions. Moreover, the behavior of... more
Tracking individuals in social networks is one of the challenging tasks in digital forensics. In social networks, individuals' behavior can be predicted or measured based on their online interactions. Moreover, the behavior of individuals in real life can be a side effect of their online interactions. Therefore, it is important to investigate this issue in terms of the interactions among people. To this end, this paper suggests a novel framework for projecting a social network into a dynamic environment aiming to simulate a real-life situation. A dataset of users' interactions from Facebook is used in the simulations. The users along with their attributes are projected into a dynamic simulation environment. Then, a mobility model and a population distribution are incorporated into the simulation environment. The interactions among users in the dynamic environment are collected and compared to the interactions in the social network. The findings showed that the behavior of users was inherited from the social network. Based on these findings, the proposed approach reflected efficient performance and a strong ability to project a static network into a dynamic one. The idea of this work is applicable in rural applications for monitoring and tracking purposes.
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The attackers do not want their Malicious software (or malwares) to be reviled by anti-virus analyzer. In order to conceal their malware, malware programmers are getting utilize the anti reverse engineering techniques and code changing... more
The attackers do not want their Malicious software (or malwares) to be reviled by anti-virus analyzer. In order to conceal their malware, malware programmers are getting utilize the anti reverse engineering techniques and code changing techniques such as the packing, encoding and encryption techniques. Malware writers have learned that signature based detectors can be easily evaded by “packing” the malicious payload in layers of compression or encryption. State-of-the-art malware detectors have adopted both static and dynamic techniques to recover the payload of packed malware, but unfortunately such techniques are highly ineffective. If the malware is packed or encrypted, then it is very difficult to analyze. Therefore, to prevent the harmful effects of malware and to generate signatures for malware detection, the packed and encrypted executable codes must initially be unpacked. The first step of unpacking is to detect the packed executable files. The objective is to efficiently an...
Research Interests:
Research Interests:
Research Interests:
The diagnosis and prognosis of breast cancer is an important, real-world medical problem. As an intrusion detection problem is one of the applications of artificial immune system, in this paper proposes a novel scheme that uses a robust... more
The diagnosis and prognosis of breast cancer is an important, real-world medical problem. As an intrusion detection problem is one of the applications of artificial immune system, in this paper proposes a novel scheme that uses a robust immune system formed from clonal selection theory and principal component analysis for breast cancer diagnosis and Prognosis. Like the job done by Antigen Presenting Cells APCs in natural immune system, this work use PCA as an aided tool for immune cells in the selection for the most important features that can detect the cancer and forward them for the immune system in training phase which generates an artificial lymphocytes ALCs and save them as immune memory. It is important to note that the training phase was done on 20% of the dataset, whereas the testing phase was done on the remaining 80% of the data set which are considered as unknown cases for the ALCs. The study proved that the best results obtained when the PCA select minimum reasonable number of features, while in the training phase the diagnostic accuracy is 0.99 and the prognostic accuracy is 0.9, and the memories ALCs achieved in the testing phase a diagnostic accuracy 0.97 and prognostic accuracy 0.88.