Advances in Cyber Security

Due to the offering of many benefits, blockchain is a useful environment to build many applications in multiple fields such as cryptocurrency, Internet of Things (IoT), mobile applications and healthcare industry. However, it has a problem in ensuring the privacy of user data due to its public nature. Data on a blockchain is public and can reveal someone’s personal data or transactions. Many applications that venture in blockchain such as financial applications, Internet of Things (IoT) and healthcare applications can fall victim to revelation of personal data and linking attack. Many solutions such as automated access-control protocol that does not require a third party, a local miner operating in a local private blockchain that enforces users’ access control policy, a cryptographic protocol that lets contractual parties interact by using zero-knowledge proof, and computation of data query in a distributed way by using secure multi-party computation have been proposed to tackle this privacy issue in using blockchain. Hence, this paper provides a review on the current solutions that addresses the privacy issues of blockchain in different platforms. However, these solutions have some limitations that cannot be overlooked and proper measures must be taken to make blockchain to be able to better protect the privacy of its users. This paper also discusses the limitations of the solutions and looks into the aspects that need to be addressed.

With the proliferation of Internet of Things (IoT) and its influence in various use case scenarios, it can be expected that IoT services will create a global reach. Smart cities, smart grids, smart industries, smart wearables etc. are some examples of IoT services today. Besides all the benefits that IoT provide, security issues of these services and data generated by IoT are of major concern. Traditional security practices of authentication and authorization have been initially designed for security needs of centralized client/server models which are good to deal with human-machine interaction over the Internet. In centralized systems, normally devices and users are trusted for being in the same application domain. Moreover, such systems can become a bottleneck for a number of queries at the same time; or may become a single point of failure causing unavailability of connected devices that are totally relying on a single trusted party. This paper explores the IoT security issues and concerns. Moreover, it provides a review of centralized and decentralized IoT security solutions in terms of authentication and authorization. Additionally, it discusses how Blockchain technology can be leveraged to provide IoT security.

Authentication is one of the essential defense mechanisms to prevent unauthorized access to our personal gadgets. Several authentication schemes have been proposed over the years, such as passwords, PIN and biometrics. Although there are many types of authentication methods equipped in our devices, they still have their limitations. This study compares the different types of commonly used knowledge-based authentication systems and identifies the shortcomings of these authentication methods by thoroughly exploring their vulnerabilities. In this study, we propose an innovative idea that modifies the existing pattern-lock authentication method by using a combination of patterns, colors and randomization to authenticate users to their mobile device. This proposed method can prevent unauthorized users from shoulder-surfing and analyzing the static repeated patterns drawn by users on their mobile devices.

The major drawback of a centralised system is using a shared database among the network users. If a server failed to operate, then the whole system will be affected. Leakage of sensitive data such as name of user, home address and contact number is a big issue faced by most networking sites. In this research, a blockchain-based image sharing web application will be developed which makes the process of exchanging image more secure and reliable. Upon launching the application, users are strongly encouraged to publish their original image. Users can view all the published images on news feed. Besides, users are allowed to update their profile by changing the avatar and description of user profile. Since all images are stored by using InterPlanetary File System (IPFS), hence a little capacity is needed to save the related Uniform Resource Locator (URL) for retrieval purpose.

Proof of Work (PoW) protocol for cryptocurrency uses an excessive amount of electricity to secure the network. Many PoW coins do not have sufficient hashing power to secure itself. There are many alternatives to PoW, such as Proof of Stake (PoS), merge-mining etcetera, which uses much less electricity. However, these alternatives have some drawbacks either in terms of security, complexity, and scalability. In this paper, an alternative to Proof of Work (PoW) called “Proof of BID” (PoB) protocol introduced. PoB makes use of existing bitcoin PoW to secure all transactions, thus consuming virtually no electricity. PoB also addresses most of the drawbacks faced by PoW alternatives. We have disclosed a systematic method on how to effectively re-used bitcoin PoW to secure a blockchain with the same level of bitcoin security. A few designs issue to improve the blockchain scalability is given. We have explored various attack scenarios and suggested some remedies.

This paper presents a Context-Based Blockchain Platform Definition and Analysis Methodology (MetaBlockX) to analyse and identify the best blockchain platform to specific context. Nowadays the number of existing platforms is enormous, in this way, assessing and identifying which best suits to context and service needs is a great challenge. In addition, each use case has its specifics, which can vary from prophecy in a certain programming language or need to keep data private, or even response time and delay to process the data. In this way a holistic and well-documented analysis is required to identify such a blockchain development platform that is proposed at this paper.

Digital image watermarking techniques have enabled imperceptible information in images to be hidden to ensure the information can be extracted later from those images. For any watermarking scheme, there are four main requirements which are imperceptibility, Robustness, capacity and security. Recently, hybrid Singular Value Decomposition (SVD) based watermarking schemes in the transform domain have significantly gained a lot of attention. This is due to the characteristics of SVD and the wavelet. Most of these schemes were tested under different conditions using grey images only. However, due to the growth of digital technology and the huge use of the colour images, it is important to consider the colour images in the watermarking area. Three different SVD-based image watermarking schemes with different wavelet transforms are selected in this paper to be tested and evaluated for colour images. Two colour models are used to represent the colour images to perform the embedding and the extraction watermarking process to study these colour models’ performances and effectiveness in the watermarking area. These colour models are RGB and YCbCr. All these colour models’ channels are used as an embedding channel and then are evaluated under different attacks types. The experimental results of the selected Wavelet SVD-based watermarking schemes proved that the embedding in the RGB and YCbCr colour channels are achieved high imperceptibility. These colour channels also showed good robustness against different attacks such as cropping, cutting, rotation and JPEG compression.

The recent proliferation of smart home environments offers new and transformative circumstances for various domains with a commitment to enhancing the quality of life and experience of their inhabitants. However, most of these environments combine different gadgets offered by multiple stakeholders in a dynamic and decentralized manner, which in turn presents new challenges from the perspective of digital investigation. In addition, a plentiful amount of data records got generated because of the day-to-day interactions between smart home’s gadgets and homeowners, which poses difficulty in managing and analyzing such data. The analysts should endorse new digital investigation approaches and practices to tackle the current limitations in traditional digital investigations when used in these environments. The digital evidence in such environments can be found inside the records of log-files that store the historical events and various actions occurred inside the smart home. Threat hunting can leverage the collective nature of these gadgets, the vengeful artifacts observed on smart home environments can be shared between each other to gain deeper insights into the best way for responding to new threats, which in turn can be valuable in reducing the impact of breaches. Nevertheless, this approach depends mainly on the readiness of smart homeowners to share their own personal usage logs that have been extracted from their smart home environments. However, they might disincline to employ such service due to the sensitive nature of the information logged by their personal gateways. In this paper, we presented an approach to enable smart homeowners to share their usage logs in a privacy-preserving manner. A distributed threat hunting approach has been developed to elicit the various threat reputations with effective privacy guarantees. The proposed approach permits the composition of diverse threat classes without revealing the logged records to other involved parties. Furthermore, a scenario was proposed to depict a proactive threat Intelligence sharing for the detection of potential threats in smart home environments with some experimental results.

As many organizations are adopting cloud computing as this allows them to be more agile, flexible and efficient. Nevertheless, as with any new technologies, cloud computing also suffers from various issues especially in security and privacy. Distributed Denial of Service (DDoS) attack saturates server resources, e.g. web server, by flooding it with fake requests. This renders the server inaccessible to legitimate users. Nevertheless, if the server is hosted as a cloud service, DDoS attack will not be effective due to the elasticity nature of the cloud server. Thus, a new variant of the DDoS attack, called Economic Denial of Sustainability (EDoS) attack, has emerged. Since the cloud service is based on “pay-per-use” model, EDoS attack endeavors to scale up the resource usage over time to the point the purveyor of the server is financially incapable of sustaining the service due to the incurred unaffordable usage charges. The implication of EDoS attack is a major security implication as more elastic cloud services are being deployed. A new mechanism, EDoS Mitigation Mechanism (EMM), is proposed to address these shortcomings using OpenFlow and statistical techniques, i.e. Hellinger Distance and Entropy. The experiments clearly showed that EMM is able to detect and mitigate EDoS attacks effectively without the need for additional resource requirements.

Distributed Denial of Service (DDoS) attack is considered as one of the major security threats to the cloud computing environment. This attack hampers the adoption and deployment of cloud computing. DDoS Attack is an explicit attempt by an attacker to prevent and deny access to shared services or resources on a server in a cloud environment by legitimate users of cloud computing. This kind of attack targets victim servers by sending massive volumes of traffic from multiple sources to consume all the victim server resources. This paper discussed various defense mechanisms for defending DDoS. The main objective of this paper is to evaluate different mechanisms that help to defend DDoS attacks. This paper highlights the importance of statistical anomaly-based approaches in detecting DDoS attacks.

In recent years, the number of Internet users and devices are rapidly increased. For this reason, the Internet Assigned Number Authority (IANA) launched a new protocol called Internet Protocol version six (IPv6) next generation. The IPv6 provides new features that fit the internet revolution. IPv6 is equipped with new protocols such as Neighbor Discovery Protocol (NDP) and Internet Control Messages protocol version six (ICMPv6). In fact, ICMPv6 is considered as the backbone of the IPv6 protocol since it is responsible for many key functions like the NDP process. In addition, the NDP protocol is a stateless protocol that gives the lack of authentication to NDP messages, which is vulnerable to many types of attacks such as Distributed Denial of Services (DDoS) and Denial of Services (DoS) flooding attacks. In this type of attacks, the attacker sends an enormous volume of abnormal traffic to increase network congestion and break down the network. Under those circumstances, the first line of defense in a network has been supplemented by additional devices and tools that supervise the network activities and monitor the network traffic behaviors as well as to stop unauthorized intrusions. Overall, the aim of this review paper is to give pure thoughts about the IPv6 features and the most important related protocols like ICMPv6 protocol and NDP protocol. Also, this article discusses DDoS and DoS attack based on ICMPv6 protocol. Likewise, this article gives a comprehensive review of the IPv6 Intrusion Detection Systems based on DDoS & DoS attacks with their features and security limitations.

Supervised machine learning is a method to predict a class for labeled data, to improve different QoS metrics of several scopes such as educational, industrial and medical etc. This paper presents in-deep study focusing on four supervised classifiers were used widely to distinguish or categorize TCP/IP network traffic model and how they can be employed, these four are Naïve Bayes, Probabilistic Neural Network, Support Vector Machine and C4.5 decision tree. The classifiers are compared with regard to three significant metrics namely classification accuracy, classification speed and memory consumption. The implementation results of simulation and comparisons show that C4.5 decision tree introduce best results with high accuracy up to 99.6% using the benchmark dataset consist of 24863 packets compared to the rest three tested classifiers.

Mobile phones or smartphones are rapidly becoming the primary and essential communication device in people’s lives that cannot be replaced by other communication devices, because of the portability, the size, and the multifunctionality provided in it. Nowadays, mobile phones are being used in almost every aspect of life and work as your personal assistant e.g. meeting reminders. It monitors your daily activities and gives suggestions accordingly e.g. health applications. With the help of smartphone online transactions can be performed, meetings can be conducted via video conferencing. It contains your personal files, emails, bank information, and your social network accounts record. It also contains information related to the credentials, which are stored in its memory. Despite all the benefits, there is a great threat to private information, in the case when mobile is snatched, misplaced, or in the use of an unauthorized user. An attacker can steal the user’s private data and can misuse it without the owner’s consent. Although the traditional authentication methods are in use, they have several limitations. In this paper, an authentication system is proposed that uses a combination of user behavior and touchscreen which can seamlessly capture the user’s tapping behavior. The information obtained from the touch screen sensors reflects the unique tapping behavior of each user. Moreover, machine learning is utilized to perform the classification for the user’s authentication.

Numerous security researchers have a growing interest in the vulnerabilities of the in-vehicle Controller Area Network (CAN) bus system to cyber-attacks. The adversaries can leverage these vulnerabilities in manipulating vehicle functions and harming the drivers’ safety. Some security mechanisms proposed for CAN bus in detecting anomalies have favoured over the one-class classification, where it constructs a decision boundary from normal instances. Nevertheless, the accuracy performance of the classifier is highly influenced by the data representation. Judging from this fact, this paper analyses the advantage of utilizing different feature scaling technique as in to obtain higher classification accuracy of the classifier algorithms. To serve this purpose, the CAN bus datasets in this paper are scaled using standardization, min-max, and quantile, and are evaluated using one-class classifier model used in automotive CAN bus. The results exhibit that integrating different feature scaling techniques could greatly enhance the classification accuracy of the classifiers.

With the flooding of a large variety of isolated blockchain solutions into the technological world, one major challenge is to enable efficient interoperable interchain and intrachain exchanges. The dearth of inter-operating among these eclectic tokens is hindering the profits that can be earned by potential investors. The myriads of tokens that are flooding into the blockchain ecosystem need to interoperate amongst each other. This paper proposes a mechanism to provide better atomic intrachain token swaps. Our blockchain solution can assist the exchange of these eclectic heterogeneous tokens securely, using digital signatures and hashed time lock contracts, which reduces the problem of interoperability. This paper presents a solution which is token standard agnostic and provides effective intrinsic smart contracts facilitating token exchange and thus reducing the counterparty risk.

In this paper authors introduce an algorithm to simplification of UEFI firmware reverse engineering via limiting the amount of code examined on Intel-based systems, which is based on proprietary UEFI protocols searching. The provided implementation of the algorithm is tested on few platforms that are Gigabyte BRIX, Razer Blade Stealth and Intel NUC based on 7th Generation Intel(R) Processor Families. As a result, UEFI modules that contain references to proprietary protocols were defined.

This pilot study was done to evaluate the picture superiority effect on the memorability and usability of BlindLogin based on the Usability-Deployability-Security (UDS) Model and to compare the results with other graphical password authentication systems found in literature. The results from this pilot study indicated that the visually impaired users generally thought that BlindLogin was better than the textual password based on all the UDS Model usability criteria. The results further indicated that BlindLogin was significantly better than textual passwords in four usability criteria (Memorywise Effortless, Infrequent Errors, Efficient to Use and Physically Effortless). For Memorywise-Effortless, BlindLogin (p < 0.012) is more significant than Image PassTiles (p < 0.013) and much more significant than Object PassTiles (p < 0.045). For Infrequent Errors, BlindLogin (p < 0.015) is almost as significant as Passpoints (p < 0.013). The security of BlindLogin was also assessed by tabulating the password space and launching a dictionary attack and a brute-force attack using the capabilities of the cloud. The results showed that it would take about 48188.59 years to brute-force a BlindLogin password using the capabilities of the cloud, which is better than DAS (541.8 years) and Grid Selection (541.8 years). As currently graphical authentication systems designed for the visually impaired have yet to be found in literature, BlindLogin has been shown to be a memorable and usable graphical authentication system for visually impaired users as compared to other graphical password systems which was designed only for sighted users on the mobile platform.

Currently, the Wireless Ad-Hoc Networks (WAHN) are becoming very common due to the advancements in the Internet of Things (IoT) technologies. For WAHN, there are many available technologies such as ZigBee, Z-Wave, Threads, Bluetooth Low Energy (BLE) etc. Despite of the improvements in IoT technologies, multicasting pure mesh-based routing is still a major problem that needs to be resolved. In view of the aforesaid, this research will propose a multicast mesh-based communication network architecture and protocol having topology autoconfiguration features. Subsequently, for this study, the use case will be the hospital (being the most critical place dealing with emergencies). Furthermore, for the aforesaid use case, the BLE is supposed to be the most suitable technology being low power and easily available (in smart phone and gadgets). Initially, the BLE was introduced in Bluetooth version 4.0 and its features got matured in the advance version 4.2 and 5. BLE 5 has the capability for mesh topology that has increased the network coverage and enhanced end to end diversity of the Bluetooth based ad-hoc networks. Likewise, in this paper, the emphasis will be on proposing a pure mesh-based routing protocol capable of multicasting and topology autoconfiguration for BLE 5 enabled network for the hospital.

The paper describes the development of a Wireless Sensor Network for Temperature and Humidity Monitoring System. The prototype is based on NodeMCU ESP8266 module that automatically record the current parameters and allowing the user to interact with the monitoring system wirelessly. A total of three wireless microcontrollers are used as sensor nodes and actuator node to form a wireless sensor network. Each node is connecting to online cloud storage that helps to receive, process and send the information to and from the desired nodes. The data communication from the wireless sensor nodes to the cloud database is done via MATLAB ThingSpeak. Within the monitoring system facility, the access network is based on ESP8266 Wi-Fi network, which are enabling the concept of Internet of Things. The monitoring system is deployed to the room exhaust ventilation system (REVS) which include 3G technology in it allowed the stand-alone REVS system monitoring remotely via web or mobile application at low cost. Experimental results show that the system is capable to use a unified approach to recording, displaying and controlling the temperature and humidity parameters through several IoT platforms: MATLAB ThingSpeak, ThingView App and REVS mobile application developed using MIT App inventor.

Modern data communication paradigm involves many unsolicited data transmissions that poses privacy issues given the proliferation of big data and artificial intelligence (A.I.). In 802.x protocol which dominate wireless communication; Wi-Fi enabled devices voluntarily embed devices MAC address during SSID discovery when connecting to access point (AP). Such vulnerability has been massively exploited for unauthorized devices tracking without user consents. This paper proposed an opportunistic attendance taking system (OATA) using MAC address probing as a proof of concepts to demonstrate the significance of this exploit. The intuition is that student’s attendance can be implied based on the MAC address of their mobile devices when approaching lecture hall installed with AP(s). The body of this work focuses on comparing the OATA to some prominent attendance taking methods in pervasiveness and accuracy. For the operational hypothesis, a non-synthetic dataset is used for experimental evaluation to simulate realness and to minimize hawthorn effect. OATA is designed to circumvent MAC address randomization that is used on modern IOS and Android OS for accurate tracking. The experimental results showed that OATA is highly accurate at capturing device’s presence; achieving true positive rate (TPr) of 0.938 and false positive rate (FPr) of 0.063 with fast convergence time. The significance of this study highlight the concerns that big data coupled with increasingly intelligent A.I. can divulge more information than originally intended. Consequently, user’s privacy is compromised as their personal communication devices are demonstrated to be potentially exploited for unsolicited location tracking.

Satellite communication is among those applications where data confidentiality is required, but at the same time, computational resources are limited as well as the delay is critical. For these types of applications, symmetric key encryption algorithms are preferred over asymmetric key algorithms, due to lower computational cost and faster speed of operation. Furthermore, due to various critical aspects of information security, using Perfect Forward Secrecy (PFS) in many communication applications is advantageous. There are two ways to achieve PFS; either a mechanism for new key generation is required, or some protocols are used for sharing new session keys before communication. Both of these ways, at minimum, append additional computational load and delay in communication, which are critical in satellite communication. This is probably the most significant barrier that satellites do not use PFS for every communication. This paper presents a novel encryption algorithm where a message key is generated such that later only Exclusive OR (XOR) operation can be used to produce the ciphertext. Hence, the proposed algorithm eliminates the need for two separate algorithms for message key generation and encryption for PFS. Security analysis and experimental results show that proposed encryption algorithm is not only secure but also faster and cheaper than the widely used AES-CTR encryption algorithm. Therefore it is suitable to be used in satellite communication for PFS.

Guided by Technology Acceptance Model (TAM) and the lack of research on Open Source Cloud Computing (OSCC) in the Iraqi’s setting, the current endeavor posits and tests a model. The model encapsulates a number of perception-based, an attitudinal and intentional variable. Though, the aforementioned model is argued to correspond to a number of questions, which in turn, portray a gap in the literature. Particularly, the paper investigates the role of perception of the ease of use, usefulness and risk influences on attitude toward and the intention to adopt OSCC in the Iraqi’s settings. In addition, it conceptualized and tested the mediating role of user’s attitude. To that effect, a questionnaire was designed and deployed to examine the factors influencing intention to use the new technology of open source cloud computing. The obtained data were subjected to a number of statistical analyses. Particularly, the goodness of measure was assessed through conducting internal consistency test and factor analysis. The former test uncovered that the utilized constructs are reliable. The later analysis suggested the presence of only three variables. Moreover, the interrelationships between the resulted constructs of the framework were tested using multiple and heretical regression. Findings of these analyses suggest that consumers’ perception of OSCC has a weak effect on their intention to use it. Consumers’ attitudes were found to maintain more potent impact on their intention to utilize the new technology. Moreover, consumers’ attitude was unveiled to mediate the relationship between perception of OSCC and the intention to use OSCC. The study was concluded with a brief summary, its implications, and suggestion for future researcher.

End-user encounters security warnings on a daily basis in different web browsers. Effective security warning is critical to provide a secure environment to end-users to against attack. However, users always encounter problems and challenges when they encounter security warnings due to the poor warning dialogue interface. Element used in the warning interface is important to support users to make an effective decision. A poor warning design will lead a user to become a fraud victim. Hence, there is a need to design an effective warning dialogue by providing useful security features. Although the efficacy of security warning is depending on the interface of security feature, but also highly dependent on the user’s perception and understanding. This paper determine to investigates further from the end-user’s experience whilst encountering security warnings (i.e. Chrome browser context). An exploratory interview study with 65 participants was conducted to pursue in-depth information about the perceptiveness of users towards current security warnings in three different scenarios. The results show that elements such as icon, colour, wording used in the warning can impact the efficacy of the warning. All the user feedback indicated that there is still room for improvement on the current security warning.

The dependencies of the computer and the Internet keep increasing among the users. Thus, it poses to the increasing number of attacks as a result of using various application and tools. Security warning conveys an alert on the potential harm users might expose such as malware and any kind of attacks on their computer. In practice, most of the end users tend to ignore the security warning as it shows the messages repeatedly, although they have been exposed to many risks. A security warning dialogue is supposed to catch the user’s attention and comprehension however, because of users’ past experiences such habituation makes them became less focus. One-to-one interview session with 60 participants was conducted in order to gain further comprehension among the end users experiencing security warning and to investigate the usability issues of current security warning implementation. It is deemed of necessity to discover these usability issues in the current context of security warning presentations. The result revealed that the problems and challenges continue to persist such as difficulties to make a decision, difficulties to comprehend technical jargons, lack of attractiveness of current security warning and issues of habituation or repeated exposures of warnings.

In this paper, we show several vulnerabilities in the ordering mechanism of one of Malaysia’s online food ordering services company (which we will call “Company X”) website. In particular, we show that the system is open to several kinds of abuse, demonstrating two proof-of-concept attacks we carried out, as well as discuss more potentially disruptive theoretical attacks. We also suggest several countermeasures to rectify the issues, that are not only applicable to Company X website, but also to other similar online ordering systems.

This review paper is an attempt to cover the arising threats against information privacy and security in the attractive Social Network environment that represents a rich mine of user personal data. First, the paper discusses the information privacy, while many researches have been found in the relevant literature with respect to privacy in Social Networks, more efforts are needed especially on data leakages that happen to each entity including Social Network users, service providers, third and external parties, and how data linkages can produce useful information to these parties. Second, the paper discusses the information security focusing on the social engineering threats, while many efforts have been found in the relevant literature with respect to social engineering in the Internet in general, only few attempts cover the topic in the Social Network environment. In this paper, threats of fake accounts, identity theft, and spear phishing are discussed specifically in the Social Networks. Furthermore, the paper presents the roles of Social Network users and service providers to protect information privacy and prevent threats against information security. This review paper is an attempt to become a guideline to current information privacy and security threats in Social Network environment, and to pave the way for the researchers to investigate more solutions for these threats in future works.