انجمن رمز ایران Biannual Journal Monadi for Cyberspace Security (AFTA) 2476-3047 2476-3047 3 2 2015 3 1 Relay Selection for Secure Device to Device Communications 3 14 FA sonia naderi sonia_naderi_90@yahoo.com Y mohammadreza javan javan@shahroodut.ac.ir N In this paper, a cooperative scheme for secure device to device (D2D) communications underlaying cellular networks is proposed. In our scheme, the cellular base station (BS) wants to transmit its information to a cellular user (CU). Meanwhile, two devices want to communicate directly using the same spectrum used by cellular network with the help of some decode-and-forward (DF) relay nodes. In addition, there exists a malicious user which wants to eavesdrop on information transmission of D2D pair. The transmit power of the transmitter of the D2D pair (TD2D) and the relays is limited such that the outage performance of cellular network is satisfied. We study the performance of the proposed scheme, which is measured based on the outage probability, and obtain the closed form expression for the outage probability for the optimal relay selection scheme. Finally, the performance of the proposed scheme is evaluated using simulations. Device to Device (D2D) communications, physical (PHY) layer security, Decode and forward (DF) relay, Relay Selection, Outage Probability http://monadi.isc.org.ir/article-1-38-en.html http://monadi.isc.org.ir/article-1-38-en.pdf

انجمن رمز ایران Biannual Journal Monadi for Cyberspace Security (AFTA) 2476-3047 2476-3047 3 2 2015 3 1 Robustness Verification of Trust Systems 15 34 FA ladani@eng.ui.ac.ir Y amirjalali@eng.ui.ac.ir N Trust and reputation are known social concepts which have an important role in human society. Nowadays, these concepts are also employed in computer science as computational trust and reputation systems (TRSs) that are able to compute the trustworthiness rank of entities based on a collection of experiments and recommendations. Since it is expected that a dishonest entity has a lower trust, the trust values can help the entities to detect and isolate the malicious or selfish entities. TRSs have been applied in many modern computer systems, and also are the most important tool in soft security as the next generation of security mechanisms. Despite the importance and applications of these systems, they are vulnerable to some kind of attack in which the attacker deceives the system using a sequence of misleading behavior. These attacks enable the attacker to manipulate the computation of trust values in his favor. A vulnerable system not only can’t help detecting the malicious entities, but also may be used by them to empower their attack. Hence, robustness evaluation is a critical step before using TRSs. Simulation and formal verification are two main approaches for robustness evaluation of TRSs. Despite the wide usage of simulation in evaluation of TRSs, it is an approximation method that can be used to validate the behavior of the system just for some particular computation paths. In contrast, formal verification based methods provide guarantees for the validation of the whole computation paths of the given system, thus not only their results are exact and provable but also may be used to find whole possible attacks against a given system. Considering the advantages of verification based methods, there is a narrow but progressing trend for proposing such methods in recent years. In this paper, both formal and simulation based methods for robustness evaluation of TRSs are reviewed and compared with each other. Trust and reputation systems, robustness, quantitative verification, malicious attacks http://monadi.isc.org.ir/article-1-49-en.html http://monadi.isc.org.ir/article-1-49-en.pdf

انجمن رمز ایران Biannual Journal Monadi for Cyberspace Security (AFTA) 2476-3047 2476-3047 3 2 2015 3 1 Security Architecture Improving In Cloud Computing Basic Services 35 49 FA mdeypir@gmail.com Y r.yazdani@sndu.ac.ir N Organizations should use from enterprise security architectures to secure their information assets. ‎Security patterns are a good way to build and test new security mechanisms. Enterprise security pattern ‎as an instance of model-driven architecture offers a solution to recurring information systems security ‎problems. In this paper, we present a model-driven enterprise security pattern called Secure SaaS., which ‎the organizations could apply to protect their information assets when using SaaS. On the other hand ‎Cloud Computing is a approach for the efficient use of computational resources. cloud delivers ‎computing as a service. However, security concerns prevent many individuals and organizations from ‎using clouds. Second section of this paper focuses on the Security problem of Platform-as-a-Service ‎‎(PaaS) clouds including access control, privacy and service continuity while protecting both the service ‎provider and the user. Security problems of PaaS clouds are explored and classified. Countermeasures ‎are proposed and discussed. ‎ Enterprise Security Pattern , Cloud Computing, Security Architecture.‎ http://monadi.isc.org.ir/article-1-37-en.html http://monadi.isc.org.ir/article-1-37-en.pdf

انجمن رمز ایران Biannual Journal Monadi for Cyberspace Security (AFTA) 2476-3047 2476-3047 3 2 2015 3 1 Provida Method Based onSupport VectorMachinesForIntrusion DetectioninComputer Networks 51 64 FA narges salehpour salehpour_narges@yahoo.com Y Mohammad nazari farokhi N ebrahim nazari farokhi N Abstract One of the most important issues in securing computer networks is an Intrusion Detection System. Intrusion detection systems are searching for malicious behavior, deviation normal patterns and attacks on computer networks are discovered. This system recognizes the type of traffic allowed for unauthorized traffic. Since the today's data mining techniques to intrusion detection in computer networks are used. In this research is provided, a method for designing an intrusion detection system based on machine learning. One of the features of neural networks and machine learning systems, training is based on the training data. In this research is used for detecting the intrusion of machine learning to learn the features of the theory of Rough property that has a higher correlation coefficient is used. To train and evaluate has used the proposed approach the KDD CUP 99 dataset. This study, the accuracy of our method compares with feature-based learning algorithm, neural network self and decision tree. The simulation results show that the proposed system has high accuracy and speed of detection based on rough theory is right Intrusion detection systems, Support vector machine, Machine learning systems, Rough set theory. http://monadi.isc.org.ir/article-1-33-en.html http://monadi.isc.org.ir/article-1-33-en.pdf

انجمن رمز ایران Biannual Journal Monadi for Cyberspace Security (AFTA) 2476-3047 2476-3047 3 2 2015 3 1 A 65 82 FA mahin.mirjalili@gmail.com Y alireza.nowrozi@gmail.com N mitra.alidoosti@gmail.com N آزمون‌نفوذ, آسیب‌پذیری‌های تحت وب, پویشگر http://monadi.isc.org.ir/article-1-36-en.html http://monadi.isc.org.ir/article-1-36-en.pdf

انجمن رمز ایران Biannual Journal Monadi for Cyberspace Security (AFTA) 2476-3047 2476-3047 3 2 2015 3 1 83 98 FA Nasoor Bagheri Rajaee Teacher Training University martyr nbagheri@srttu.edu N Reza Aghamohammadi Education and training Re.aghamohammadi@gmail.com Y احراز هویت, رمزنگاری سبک‌ وزن, LPN, Authentication, RFID, HB http://monadi.isc.org.ir/article-1-30-en.html http://monadi.isc.org.ir/article-1-30-en.pdf