Biblio

As the demand for effective information protection grows, security has become the primary concern in protecting such data from attackers. Cryptography is one of the methods for safeguarding such information. It is a method of storing and distributing data in a specific format that can only be read and processed by the intended recipient. It offers a variety of security services like integrity, authentication, confidentiality and non-repudiation, Malicious. Confidentiality service is required for preventing disclosure of information to unauthorized parties. In this paper, there are no ideal hash functions that dwell in digital signature concepts is proved.

Android Operating System becomes a major target for malicious attacks. Static analysis approach is widely used to detect malicious applications. Most of existing studies on static analysis frameworks are limited to certain features. This paper presents an Android Static Analysis Framework (ASAF) which models the overall static analysis phases and approaches for Android applications. ASAF can be implemented for different purposes including Android malicious apps detection. The proposed framework utilizes a parsing tool, Android Static Parse (ASParse) which is also introduced in this paper. Through the extendibility of the ASParse tool, future research studies can easily extend the parsed features and the parsed files to perform parsing based on their specific requirements and goals. Moreover, a case study is conducted to illustrate the implementation of the proposed ASAF.

In this paper, an effective Advanced Persistent Threat (APT) attack response system was proposed. Reference to the NIST Cyber Security Framework (CRF) was made to present the most cost-effective measures. It has developed a system that detects and responds to real-time AM-HIDS (Anti Malware Host Intrusion Detection System) that monitors abnormal change SW of PCs as a prevention of APT. It has proved that the best government-run security measures are possible to provide an excellent cost-effectiveness environment to prevent APT attacks.

SCADA systems are being constantly migrated to modern information and communication technologies (ICT) -based systems named cyber-physical systems. Unfortunately, this allows attackers to execute exploitation techniques into these architectures. In addition, ransomware insertion is nowadays the most popular attacking vector because it denies the availability of critical files and systems until attackers receive the demanded ransom. In this paper, it is analysed the risk impact of ransomware insertion into SCADA systems and it is suggested countermeasures addressed to the protection of SCADA systems and its components to reduce the impact of ransomware insertion.

The popularity of cloud hosting services also brings in new security challenges: it has been reported that these services are increasingly utilized by miscreants for their malicious online activities. Mitigating this emerging threat, posed by such "bad repositories" (simply Bar), is challenging due to the different hosting strategy to traditional hosting service, the lack of direct observations of the repositories by those outside the cloud, the reluctance of the cloud provider to scan its customers' repositories without their consent, and the unique evasion strategies employed by the adversary. In this paper, we took the first step toward understanding and detecting this emerging threat. Using a small set of "seeds" (i.e., confirmed Bars), we identified a set of collective features from the websites they serve (e.g., attempts to hide Bars), which uniquely characterize the Bars. These features were utilized to build a scanner that detected over 600 Bars on leading cloud platforms like Amazon, Google, and 150K sites, including popular ones like groupon.com, using them. Highlights of our study include the pivotal roles played by these repositories on malicious infrastructures and other important discoveries include how the adversary exploited legitimate cloud repositories and why the adversary uses Bars in the first place that has never been reported. These findings bring such malicious services to the spotlight and contribute to a better understanding and ultimately eliminating this new threat.

This paper proposes a methodology to assess cyber-related risks and to identify critical assets both at power grid and substation levels. The methodology is based on a two-pass engine model. The first pass engine is developed to identify the most critical substation(s) in a power grid. A mixture of Analytical hierarchy process (AHP) and (N-1) contingent analysis is used to calculate risks. The second pass engine is developed to identify risky assets within a substation and improve the vulnerability of a substation against the intrusion and malicious acts of cyber hackers. The risk methodology uniquely combines asset reliability, vulnerability and costs of attack into a risk index. A methodology is also presented to improve the overall security of a substation by optimally placing security agent(s) on the automation system.
 

This paper proposes a methodology to assess cyber-related risks and to identify critical assets both at power grid and substation levels. The methodology is based on a two-pass engine model. The first pass engine is developed to identify the most critical substation(s) in a power grid. A mixture of Analytical hierarchy process (AHP) and (N-1) contingent analysis is used to calculate risks. The second pass engine is developed to identify risky assets within a substation and improve the vulnerability of a substation against the intrusion and malicious acts of cyber hackers. The risk methodology uniquely combines asset reliability, vulnerability and costs of attack into a risk index. A methodology is also presented to improve the overall security of a substation by optimally placing security agent(s) on the automation system.

This paper proposes a methodology to assess cyber-related risks and to identify critical assets both at power grid and substation levels. The methodology is based on a two-pass engine model. The first pass engine is developed to identify the most critical substation(s) in a power grid. A mixture of Analytical hierarchy process (AHP) and (N-1) contingent analysis is used to calculate risks. The second pass engine is developed to identify risky assets within a substation and improve the vulnerability of a substation against the intrusion and malicious acts of cyber hackers. The risk methodology uniquely combines asset reliability, vulnerability and costs of attack into a risk index. A methodology is also presented to improve the overall security of a substation by optimally placing security agent(s) on the automation system.