Biblio

Phishing emails have affected users seriously due to the enormous increasing in numbers and exquisite camouflage. Users spend much more effort on distinguishing the email properties, therefore current phishing email detection system demands more creativity and consideration in filtering for users. The proposed research tries to adopt creative computing in detecting phishing emails for users through a combination of computing techniques and social engineering concepts. In order to achieve the proposed target, the fraud type is summarised in social engineering criteria through literature review; a semantic web database is established to extract and store information; a fuzzy logic control algorithm is constructed to allocate email categories. The proposed approach will help users to distinguish the categories of emails, furthermore, to give advice based on different categories allocation. For the purpose of illustrating the approach, a case study will be presented to simulate a phishing email receiving scenario.

In recent years, cyber security threats have become increasingly dangerous. Hackers have fabricated fake emails to spoof specific users into clicking on malicious attachments or URL links in them. This kind of threat is called a spear-phishing attack. Because spear-phishing attacks use unknown exploits to trigger malicious activities, it is difficult to effectively defend against them. Thus, this study focuses on the challenges faced, and we develop a Cloud-threat Inspection Appliance (CIA) system to defend against spear-phishing threats. With the advantages of hardware-assisted virtualization technology, we use the CIA to develop a transparent hypervisor monitor that conceals the presence of the detection engine in the hypervisor kernel. In addition, the CIA also designs a document pre-filtering algorithm to enhance system performance. By inspecting PDF format structures, the proposed CIA was able to filter 77% of PDF attachments and prevent them from all being sent into the hypervisor monitor for deeper analysis. Finally, we tested CIA in real-world scenarios. The hypervisor monitor was shown to be a better anti-evasion sandbox than commercial ones. During 2014, CIA inspected 780,000 mails in a company with 200 user accounts, and found 65 unknown samples that were not detected by commercial anti-virus software.

The development of internet comes with the other domain that is cyber-crime. The record and intelligently can be exposed to a user of illegal activity so that it has become important to make the technology reliable. Phishing techniques include domain of email messages. Phishing emails have hosted such a phishing website, where a click on the URL or the malware code as executing some actions to perform is socially engineered messages. Lexically analyzing the URLs can enhance the performance and help to differentiate between the original email and the phishing URL. As assessed in this study, in addition to textual analysis of phishing URL, email classification is successful and results in a highly precise anti phishing.

Spam Filtering is an adversary application in which data can be purposely employed by humans to attenuate their operation. Statistical spam filters are manifest to be vulnerable to adversarial attacks. To evaluate security issues related to spam filtering numerous machine learning systems are used. For adversary applications some Pattern classification systems are ordinarily used, since these systems are based on classical theory and design approaches do not take into account adversarial settings. Pattern classification system display vulnerabilities (i.e. a weakness that grants an attacker to reduce assurance on system's information) to several potential attacks, allowing adversaries to attenuate their effectiveness. In this paper, security evaluation of spam email using pattern classifier during an attack is addressed which degrade the performance of the system. Additionally a model of the adversary is used that allows defining spam attack scenario.

The modern malware poses serious security threats because of its evolved capability of using staged and persistent attack while remaining undetected over a long period of time to perform a number of malicious activities. The challenge for malicious actors is to gain initial control of the victim's machine by bypassing all the security controls. The most favored bait often used by attackers is to deceive users through a trusting or interesting email containing a malicious attachment or a malicious link. To make the email credible and interesting the cybercriminals often perform reconnaissance activities to find background information on the potential target. To this end, the value of information found on the discarded or stolen storage devices is often underestimated or ignored. In this paper, we present the partial results of analysis of one such hard disk that was purchased from the open market. The data found on the disk contained highly sensitive personal and organizational data. The results from the case study will be useful in not only understanding the involved risk but also creating awareness of related threats.

Checking remote data possession is of crucial importance in public cloud storage. It enables the users to check whether their outsourced data have been kept intact without downloading the original data. The existing remote data possession checking (RDPC) protocols have been designed in the PKI (public key infrastructure) setting. The cloud server has to validate the users' certificates before storing the data uploaded by the users in order to prevent spam. This incurs considerable costs since numerous users may frequently upload data to the cloud server. This study addresses this problem with a new model of identity-based RDPC (ID-RDPC) protocols. The authors present the first ID-RDPC protocol proven to be secure assuming the hardness of the standard computational Diffie-Hellman problem. In addition to the structural advantage of elimination of certificate management and verification, the authors ID-RDPC protocol also outperforms the existing RDPC protocols in the PKI setting in terms of computation and communication.
 

In this paper, we inspire from two analogies: the warfare kill zone and the airport check-in system, to tackle the issue of spam botnet detection. We add a new line of defense to the defense-in-depth model called the third line. This line is represented by a security framework, named the Spam Trapping System (STS) and adopts the prevent-then-detect approach to fight against spam botnets. The framework exploits the application sandboxing principle to prevent the spam from going out of the host and detect the corresponding malware bot. We show that the proposed framework can ensure better security against malware bots. In addition, an analytical study demonstrates that the framework offers optimal performance in terms of detection time and computational cost in comparison to intrusion detection systems based on static and dynamic analysis.

Phishing continues to remain a lucrative market for cyber criminals, mostly because of the vulnerable human element. Through emails and spoofed-websites, phishers exploit almost any opportunity using major events, considerable financial awards, fake warnings and the trusted reputation of established organizations, as a basis to gain their victims' trust. For many years, humans have often been referred to as the `weakest link' towards protecting information. To gain their victims' trust, phishers continue to use sophisticated looking emails and spoofed websites to trick them, and rely on their victims' lack of knowledge, lax security behavior and organizations' inadequate security measures towards protecting itself and their clients. As such, phishing security controls and vulnerabilities can arguably be classified into three main elements namely human factors (H), organizational aspects (O) and technological controls (T). All three of these elements have the common feature of human involvement and as such, security gaps are inevitable. Each element also functions as both security control and security vulnerability. A holistic framework towards combatting phishing is required whereby the human feature in all three of these elements is enhanced by means of a security education, training and awareness programme. This paper discusses the educational factors required to form part of a holistic framework, addressing the HOT elements as well as the relationships between these elements towards combatting phishing. The development of this framework uses the principles of design science to ensure that it is developed with rigor. Furthermore, this paper reports on the verification of the framework.