The ISC International Journal of Information Security

Abstract Wireless networks, Internet of Things (IoT), Internet of Everything (IoE), and smart homes have become extremely important terms in our present-day life. Most of the buildings, companies, institutions, and even homes depend on
these technologies for interaction, communication, automation, and everything surrounding humans. To understand the advanced topics in wireless networks and IoT devices, it is necessary to use one of the practical learning tools, called
Packet Tracer. This wireless network simulator is freely available by Cisco Networking Academy. In this paper, we will use Packet Tracer to design a smart home based on wireless and IoT devices and illustrate how to create different networking scenarios to make our homes more comfortable and convenient.

Abstract Botnets are recognized as one of the most dangerous threats to the Internet infrastructure. They are used for malicious activities such as launching distributed denial of service attacks, sending spam, and leaking personal information. Existing botnet detection methods produce a number of good ideas, but they are far from complete yet, since most of them cannot detect botnets in an early stage of their lifecycle; moreover, they depend on a particular command and control (C&C) protocol. In this paper, we address these issues and propose an online unsupervised method, called BotOnus, for botnet detection that does not require a priori knowledge of botnets. It extracts a set of flow feature vectors from the network traffic at the end of each time period, and then groups them to some flow clusters by a novel online fixed-width clustering algorithm. Flow clusters that have at least two members, and their intra-cluster similarity is above a similarity threshold, are identified as suspicious botnet clusters, and all hosts in such clusters are identified as bot infected. We demonstrate the effectiveness of BotOnus to detect various botnets including HTTP-, IRC-, and P2P-based botnets using a testbed network. The results of experiments show that it can successfully detect various botnets with an average detection rate of 94.33% and an average false alarm rate of 3.74%.

Abstract Code reuse attacks such as return oriented programming and jump oriented programming are the most popular exploitation methods among attackers. A large number of practical and non-practical defenses are proposed that differ in their overhead, the source code requirement, detection rate and implementation dependencies. However, a usual aspect among these methods is consideration of the common behaviour of code reuse attacks, which is the construction of a gadget chain. Therefore, the implication of a gadget and the minimum size of an attack chain are a matter of controversy. Conservative or relaxed thresholds may cause false positive and false negative alarms, respectively. The main contribution of this paper is to provide a tricky aspect of code reuse techniques, called tiny code reuse attacks (Tiny-CRA) that demonstrates the ineffectiveness of the threshold based detection methods. We show that with bare minimum assumptions, Tiny-CRA can reduce the size of a gadget chain in shuch a way that no distinction can be detected between normal behavior of a program and a code-reuse execution. To do so, we exhibit our Tiny-CRA primitives and introduce a useful gadget set available in libc. We demonstrate the effectiveness of our approach by implementing nine different shell-codes and exploiting real-world buffer overflow vulnerability in HT Editor 2.0.20.

Abstract Many security protocols have the aim of authenticating one agent acting as initiator to another agent acting as responder and vice versa. Sometimes, the authentication fails because of executing several parallel sessions of a protocol, and because an agent may play both the initiator and responder role in parallel sessions. We take advantage of the notion of transition systems to specify authentication for parallel multiple session's execution. To model the authentication, two main notions called 1. agent's scope and 2. agent's recognizability are introduced, which consider the difference of ability of agents due to their different roles in the protocol and different access to keys and secrets. To formalize above notions, a process algebra provided by some primitives for manipulating cryptographic messages is used. We formalize some security protocols and examine our definition of authentication for them. We just discuss the symmetric key case.

Abstract Nowadays, botnets are considered as essential tools for planning serious cyber attacks. Botnets are used to perform various malicious activities such as DDoS attacks and sending spam emails. Different approaches are presented to detect botnets; however most of them may be ineffective when there are only a few infected hosts in monitored network, as they rely on similarity in bots activities to detect the botnet. In this paper, we present a host-based method that can detect individual bot-infected hosts. This approach is based on botnet life-cycle, which includes common symptoms of almost all types of botnet despite their differences. We analyze network activities of each process running on the host and propose some heuristics to distinguish behavioral patterns of bot process from legitimate ones based on statistical features of packet sequences and evaluating an overall security risk for it. To show the effectiveness of the approach, a tool named BotRevealer has been implemented and evaluated using real botnets and several popular applications. The results show that in spite of diversity of botnets, BotRevealer can effectively detect the bot process among other active processes.

Abstract In this study, we propose a secure communication scheme based on the synchronization of two identical fractional-order chaotic systems. The fractional-order derivative is in Caputo sense, and for synchronization, we use a robust sliding-mode control scheme. The designed sliding surface is taken simply due to using special technic for fractional-order systems. Also, unlike most manuscripts, the fractional-order derivatives of state variables can be chosen differently. The stability of the error system is proved using the Lyapunov stability of fractional-order systems. Numerical simulations illustrate the ability and effectiveness of the proposed method. Moreover, synchronization results are applied to secure communication using the masking method. The security analysis demonstrates that the introduced algorithm has a large keyspace, high sensitivity to encryption keys, higher security, and the acceptable performance speed.

Abstract In the biclique attack, a shorter biclique usually results in less data complexity, but at the expense of more computational complexity. The early abort technique can be used in partial matching part of the biclique attack in order to slightly reduce the computations. In this paper, we make use of this technique, but instead of slight improvement in the computational complexity, we keep the amount of this complexity the same and reduce the data complexity enormously by a shorter biclique.
With this approach, we analysed full-round of LBlock, and also LBlock with modified key schedule (which was designed to resist biclique attack) both with data complexity 2^12, while the data complexity of the best biclique attack on the former was 2^52 and for the latter there is no attack on the full-round cipher, so far. Then we proposed a new key schedule that is more resistant against biclique cryptanalysis, though the low diffusion of the cipher makes it vulnerable to this attack regardless of the strength of the key schedule. Also using this method, we analyzed TWINE-80 with 2^12 data complexity. The lowest data complexity for the prior attack on the TWINE-80 was 2^60. In all the attacks presented in this paper, the computational complexities are slightly improved in comparison to the existing attacks.

Abstract An important issue in P2P networks is the existence of malicious nodes that decreases the performance of such networks. Reputation system in which nodes are ranked based on their behavior, is one of the proposed solutions to detect and isolate malicious (low ranked) nodes. Gossip Trust is an interesting previously proposed algorithm for reputation aggregation in P2P networks based on the concept of gossip. Despite its important contribution, this algorithm has deficiencies especially with high number of nodes that leads to high execution time and low accuracy in the results. In this paper, a grouped Gossip based Reputation Aggregation (GGRA) algorithm is proposed. In GGRA, Gossip Trust is executed in each group between group members and between groups instead of executing in the whole network. Due to the reduction in the number of nodes and using strongly connected graph instead of a weakly one, gossip algorithm in GGRA is executed quickly. With grouping, not only reputation aggregation is expected to be more scalable, but also because of the decrement in the number of errors of the gossiped communication, the results get more accurate. The evaluation of the proposed algorithm and its comparison with Gossip Trust confirms the expected results.

Abstract Wireless Sensor Networks (WSNs) offer inherent packet redundancy since each point within the network area is covered by more than one sensor node. This phenomenon, which is known as sensors co-coverage, is used in this paper to detect unauthenticated events. Unauthenticated event broadcasting in a WSN imposes network congestion, worsens the packet loss rate, and increases the network energy congestion. In the proposed method, the more the safe, the less the unsafe (MSLU) method, each secure occurred event must be confirmed by various sensor nodes; otherwise the event is dropped. Indeed, the proposed method tends to forward event occurrence reports that are detected by various sensor nodes. The proposed method is evaluated by means of simulation as well as analytical modeling. A wide range of simulations, which are carried out using NS-2, show that the proposed method detects more than 85% of unauthenticated events. This comes at the cost of the network end-to-end delay of 20% because the proposed method does not impose delay on incoming packets. In addition, the proposed method is evaluated by means of an analytical model based on queuing networks. The model accurately estimates the network performance utilizing the proposed unauthenticated event detection method.

Abstract The Tor network is probably one of the most popular online anonymity systems in the world. It has been built based on the volunteer relays from all around the world. It has a strong scientific basis which is structured very well to work in low latency mode that makes it suitable for tasks such as web browsing. Despite the advantages, the low latency also makes Tor insecure against timing and traffic analysis attacks, which are the most dominant attacks on Tor network in recent past years. In this paper, first all kinds of attacks on Tor network will be classified and then timing and traffic analysis attacks will be described in more details. Then we present a new circuit scheduling for Tor network in order to preserve two properties, fairness and randomness. Both properties are trying to make pattern and timing analysis attacks more difficult and even in some cases impractical. Our scheduler distorts timing patterns and size of packets in a random way (randomness) without imposing artificial delays or paddings (fairness). Finally, by using our new scheduler, one of the most powerful attacks in this area is debilitated, and by it is shown that analyzing traffic patterns and size of packets will be more difficult to manage.

Abstract A certificateless (CL) signcryption scheme is a cryptographic primitive that provides user authentication and message confidentiality at the same time. CL signcryption schemes (as a type of certificateless encryption scheme) have solved problems concerning malicious server presentation, and the server who issues users' partial private keys and certificates cannot obtain users' signing keys. Therefore, the CL signcryption scheme is an excellent choice for protecting users' signing keys and providing user authentication and message confidentiality. Moreover, signcryption schemes have lower computational costs than signature and encryption schemes.
The present study presents a short and efficient CL signcryption scheme based on the hyperelliptic curve (HC). Applying HC as the calculation base for designing the presented CL signcryption scheme reduces key-length from 160 bits to 80. The presented CL signcryption scheme is shorter than other recently-proposed ones with regard to communication overhead with its less than one-third shorter length compared to the shortest of the others. Moreover, it is more efficient than other recently-proposed CL signcryption schemes in the user-side computational cost, including the \textit{key generation} and \textit{user key generation} phases that have been halved in total. Finally, the security of the presented CL signcryption scheme was analyzed in the random oracle (RO) model based on the hardness of the point factorization problem (PFP) on HC.

Abstract Today, the Internet of Things (IoT) is one of the emerging technologies that enable the connection and transfer of information through communication networks. The main idea of the IoT is the widespread presence of objects such as mobile devices, sensors, and RFID. With the increase in traffic volume in urban areas, the existing intelligent urban traffic management system based on IoT can be vital. Therefore, this paper focused on security in urban traffic based on using RFID. In our scheme, RFID tags chose as the purpose of this article. We, in this paper, present a mutual authentication protocol that leads to privacy based on hybrid cryptography. Also, an authentication process with RFID tags is proposed that can be read at high speed. The protocol has attempted to reduce the complexity of computing. At the same time, the proposed method can withstand attacks such as spoofing of tag and reader, tag tracking, and replay attack.

Abstract The present paper is intended to present a robust multiplicative video watermarking scheme. In this regard, the video signal is segmented into 3-D blocks like cubes, and then, the 3-D wavelet transform is applied to each block. The low frequency components of the wavelet coefficients are then used for data embedding to make the process robust against both malicious and unintentional attacks. The hidden message is inserted through multiplying/dividing these coefficients by a constant parameter which controls the power of the watermark. The watermark extraction relies on a maximum likelihood-based procedure, observing the distribution of the watermarked coefficients. The performance of the proposed scheme has been verified via simulations and found to be superior to some of the well-known existing video watermarking methods.

Abstract Confidentiality, unforgeability, and public verifiability are essential for secure multi-party communications. These communications play a vital role in real-world applications such as decentralized financial transactions, e-commerce, cloud computing, and web services, where authentication and privacy preservation are very important. In conventional cryptosystems, individual signcryption performed by each participant significantly increases the unsigncryption cost for the receiver. Multi-signcryption offers an efficient alternative by allowing multiple signers to jointly signcrypt a single message. This paper proposes a novel certificateless multi-signcryption scheme that eliminates the certificate management problem of traditional public key infrastructures and avoids the key escrow problem of identity-based cryptography. To reduce the computational cost associated with bilinear pairings over elliptic curves, the proposed scheme is designed in a pairing-free environment. This scheme achieves constant-time verification in the unsigncryption phase and is independent of the number of signers. Security is formally proven under the hardness assumptions of the Elliptic Curve Computational Diffie–Hellman Problem (ECCDHP) and the Elliptic Curve Discrete Logarithm Problem (ECDLP). The proposed scheme ensures confidentiality, unforgeability, and public verifiability, and it attains significantly lower computational costs than existing schemes. Hence, the proposed scheme can be used for secure group communications in resource-constrained environments where high performance is essential. 

Abstract In terms of security, MDS matrices are one of the best choices for diffusion layer of block ciphers. However, as these matrices grow in size, their software implementation becomes a challenge. In this paper, to benefit from the properties of MDS matrices and avoid the mentioned challenge, we use 4*4 MDS matrices to build some 16*16 matrices with low number of zero elements. We show that if these matrices are used as diffusion layer of software-based SPN structures, the resulting block ciphers have similar properties as AES in software implementation complexity (i.e. the number of required CPU instructions) and resistance against linear and differential attacks. Moreover, the best impossible differential and square distinguishers for the proposed 16*16 structures have similar length as SPN structures with 16*16 MDS matrices. Thus, the new structures outperform AES with respect to the impossible differential and square attacks. Additionally, we show that if the proposed SPN structure uses the AES key schedule, its results for the differential related-key attacks are better than those for AES. We also extend the idea and use 4*4 MDS matrices to design 24*24 and 32*32 matrices with acceptable properties for SPN structure design. Finally, we extend the idea to propose some matrices for Feistel structures with SP-type F-functions. We show that the resulting structures are more secure than the improved type-II GFS.

Abstract One of the security issues in data outsourcing is the enforcement of the data owner’s access control policies. This includes some challenges. The first challenge is preserving confidentiality of data and policies. One of the existing solutions is encrypting data before outsourcing which brings new challenges; namely, the number of keys required to access authorized resources, efficient policy updating, write access control enforcement, overhead of accessing/processing data at the user/owner side. Most of the existing solutions address only some of the challenges, while imposing high overhead on both owner and users. Though, policy management in the Role-Based Access Control (RBAC) model is easier and more efficient due to the existence of role hierarchical structure and role inheritance; most of the existing solutions address only enforcement of policies in the form of access control matrix. In this paper, we propose an approach to enforce RBAC policies on encrypted data outsourced to a service provider. We utilize Chinese Remainder Theorem for key management and role/permission assignment. Efficient user revocation, efficient role hierarchical structure updating, availability of authorized resources for users of new roles, and enforcement of write access control policies as well as static separation of duties, are of advantages of the proposed solution.

Abstract Electronic health record (EHR) system facilitates integrating patients' medical information and improves service productivity. However, user access to patient data in a privacy-preserving manner is still challenging problem. Many studies concerned with security and privacy in EHR systems. Rezaeibagha and Mu [1] have proposed a hybrid architecture for privacy-preserving accessing patient records in a cloud system. In their scheme, encrypted EHRs are stored in multiple clouds to provide scalability and privacy. In addition, they considered a role-based access control (RBAC) such that for any user, an EHR access policy must be determined. They also encrypt the EHRs by the public keys of all users. So, for a large amount of EHRs, this scheme is not efficient. Furthermore, using RBAC for access policy makes the policy changing difficult. In their scheme, users cannot search on encrypted EHRs based on diseases and some physicians must participate in the data retrieval by a requester physician. In this paper, we address these problems by considering a ciphertext-policy attribute-based encryption (CP-ABE) which is conceptually closer to the traditional access control methods such as RBAC. Our secure scheme can retrieve encrypted EHR based on a specific disease. Furthermore, the proposed scheme guarantees the user access control and the anonymity of the user or data owner during data retrieval. Moreover, our scheme is resistant against collusion between unauthorized retrievers to access the data. The analysis shows that our scheme is secure and efficient for cloud-based EHRs.

Abstract Nowadays Radio Frequency Identification (RFID) systems have appeared in lots of identification and authentication applications. In some sensitive applications, providing secure and confidential communication is very important for end-users. To this aim, different RFID authentication protocols have been proposed, which have tried to provide security and privacy of RFID users. In this paper, we analyze the privacy of two recently proposed RFID authentication protocols in 2012 and 2013. We present several traceability attacks including traceability, backward traceability and forward traceability against the first protocol. We also show that, the second protocol not only suffers from Denial-of-Service (DoS) attack, but also it is vulnerable to traceability and backward traceability attacks. We present our privacy analysis based on a well-known formal RFID privacy model which has been proposed by Ouafi and Phan in 2008. Then, in order to overcome the weaknesses, we apply some modifications on these protocols and propose two modified versions.

Abstract The products of graphic design applications leave behind traces of digital information which can be used during a digital forensic investigation in cases where counterfeit documents have been created. This paper analyzes the digital forensics involved in the creation of counterfeit documents. This is achieved by first recognizing the digital forensic artifacts left behind from the use of graphic design applications, and then analyzing the files associated with these applications. When analyzing digital forensic artifacts generated by an application, the specific focus is on determining whether the graphic design application was installed, whether the application was used, and determining whether an association can be made between the application’s actions and such a digital crime. This is accomplished by locating such information from the registry, log files and prefetch files. The file analysis involves analyzing files associated with these applications for file signatures and metadata. In the end it becomes possible to determine if a system has been used for creating counterfeit documents or not.

Abstract Quantitative and model-based prediction of security in the architecture design stage facilitates early detection of design faults hence reducing modification costs in subsequent stages of software life cycle. However, an important question arises with respect to the accuracy of input parameters. In practice, security parameters can rarely be estimated accurately due to the lack of sufficient knowledge. This inaccuracy is ignored in most of the existing evaluation methods. The aim of this paper is to explicitly consider parameter uncertainty in the software security evaluation process. In particular, we use the Dempster-Shafer theory of evidence to formulate the uncertainties in input parameters and determine their effects on output measures. In the proposed method, security attacks are expressed using UML diagrams (i.e., misuse case and mal-activity diagrams) and security parameters are specified using the SecAM profile. UML/SecAM models are then transformed into attack trees, which allow quantifying the probability of security breaches. The applicability of the method is validated by a case study on an online marketing system.

Abstract The aim of phishing is tracing the users' s private information without their permission by designing a new website which mimics the trusted website. The specialists of information technology do not agree on a unique definition for the discriminative features that characterizes the phishing websites. Therefore, the number of reliable training samples in phishing detection problems is limited. Moreover, among the available training samples, there are abnormal samples that cause classification error. For instance, it is possible that there are phishing samples with similar features to legitimate ones and vice versa. A supervised feature extraction method, called weighted feature line embedding, is proposed in this paper to solve these problems. The proposed method virtually generates training samples by utilizing the feature line metric. Hence, it can solve the small sample size problem. Moreover, by assigning appropriate weights to each pair of feature points, it corrects the undesirable quality of abnormal samples. The features extracted by our method improve the performance of phishing website detection specially by using small training sets.

Abstract Attribute-based encryption (ABE) is one of the recommended tools to secure real systems like the Internet of Things (IoT). Almost all the ABE schemes utilize bilinear map operations, known as pairings. The challenge with these schemes is that performing pairings results in high computation costs and IoT devices are typically resource-constrained, so, efficient pairing-free ABE schemes have been proposed to solve this issue. These schemes utilize classical cryptographic operations instead of heavy bilinear pairings. Recently, two pairing-free ciphertext-policy attribute-based encryption schemes have been proposed (by Das et al. and Sowjanya et al.). According to their claims, their schemes are secure against collusion attacks and provide indistinguishability in a selective-set security model. The first scheme also has been claimed to be secure against forgery attacks. In this paper, we show that the first scheme is vulnerable to ciphertext-only, collusion between four or more data users with specific features, and forgery attacks. We also show that the second scheme is vulnerable to a key recovery attack, which can lead to a collusion attack. So, even though they are highly efficient, they have some security vulnerabilities that can violate the claims of the authors.

Abstract There are many different ways of securing FPGAs to prevent successful reverse engineering. One of the common forms is obfuscation methods. In this paper, we proposed an approach based on obfuscation to prevent FPGAs from successful reverse engineering and, as a result, Hardware Trojan Horses (HTHs) insertion. Our obfuscation method is using ConFiGurable Look Up Tables (CFGLUTs). We suggest to insert CFGLUTs randomly or based on some optional parameters in the design. In this way, some parts of the design are on a secure memory, which contains the bitstream of the CFGLUTs so that the attacker does not have any access to it. We program the CFGLUTs in run-time to complete the bitstream of the FPGA and functionality of the design. If an attacker can reverse engineer the bitstream of the FPGA, he cannot detect the design because some part of it is composed of CFGLUTs, which their bitstream is on a secure memory. The first article uses CFGLUTs for securing FPGAs against HTHs insertion, which are results of reverse engineering. Our methods do not have any power and hardware overhead but 32 clock cycles time overhead.

Abstract Abstract- With the advancement and development of computer network technologies, the way for intruders has become smoother; therefore, to detect threats and attacks, the importance of intrusion detection systems (IDS) as one of the key elements of security is increasing. One of the challenges of intrusion detection systems is managing of the large amount of network traffic features. Removing unnecessary features is a solution to this problem. Using machine learning methods is one of the best ways to design an intrusion detection system. Focusing on this issue, in this paper, we propose a hybrid intrusion detection system using the decision tree and support vector machine (SVM) approaches. In our method, the feature selection is initially done by the C5.0 decision tree pruning, and then the features with the least predictor importance value are removed. After removing each feature, the least square support vector machine (LS-SVM) is applied. The set of features having the highest surface area under the Receiver Operating Characteristic (ROC) curve for LS-SVM are considered as final features. The experimental results on two KDD Cup 99 and UNSW-NB15 data sets show that the proposed approach improves true positive and false positive criteria and accuracy compared to the best prior work.

Abstract The aim of image steganalysis is to detect the presence of hidden messages in stego images. We propose a blind image steganalysis method in Contourlet domain and then show that the embedding process changes statistics of Contourlet coefficients. The suspicious image is transformed into Contourlet space, and then the statistics of Contourlet subbands coefficients are extracted as features. We use absolute Zernike moments and characteristic function moments of Contourlet subbands coefficients of the image to distinguish between the stego and non-stego images. Absolute Zernike moments are used to examine the randomness in the test image and characteristic function moments of Contourlet coefficients is used to form our feature set that can catch the changes made to the histogram of Contourlet coefficients. These features are fed to a nonlinear SVM classifier with an RBF kernel to distinguish between cover and stego images. We show that the embedding process distorts statistics of Contourlet coefficients, leading to detection of stego images. Experimental results confirm that the proposed features are highly sensitive to the change made by the embedding process. These results also reveal advantage of the proposed method over its counterpart steganalyzers, in cases of five popular JPEG steganography techniques.