Phishing Detection with Image Retrieval Based on Improved Texton Correlation Descriptor

Anti-detection is becoming as an emerging challenge for anti-phishing.This paper solves the threats of anti-detection from the threshold setting condition.Enough webpages are considered to complicate threshold setting condition when the threshold is settled.According to the common visual behavior which is easily attracted by the salient region of webpages,image retrieval methods based on texton correlation descriptor(TCD)are improved to obtain enough webpages which have similarity in the salient region for the images of webpages.There are two steps for improving TCD which has advantage of recognizing the salient region of images:(1)This paper proposed Weighted Euclidean Distance based on neighborhood location(NLW-Euclidean distance)and double cross windows,and combine them to solve the problems in TCD;(2)Space structure is introduced to map the image set to Euclid space so that similarity relation among images can be used to complicate threshold setting conditions.Experimental results show that the proposed method can improve the effectiveness of anti-phishing and make the system more stable,and significantly reduce the possibilities of being hacked to be used as mining systems for blockchain.

Phishing Techniques in Mobile Devices

The rapid evolution in mobile devices and communication technology has increased the number of mobile device users dramatically. The mobile device has replaced many other devices and is used to perform many tasks ranging from establishing a phone call to performing critical and sensitive tasks like money payments. Since the mobile device is accompanying a person most of his time, it is highly probably that it includes personal and sensitive data for that person. The increased use of mobile devices in daily life made mobile systems an excellent target for attacks. One of the most important attacks is phishing attack in which an attacker tries to get the credential of the victim and impersonate him. In this paper, analysis of different types of phishing attacks on mobile devices is provided. Mitigation techniques—anti-phishing techniques—are also analyzed. Assessment of each technique and a summary of its advantages and disadvantages is provided. At the end, important steps to guard against phishing attacks are provided. The aim of the work is to put phishing attacks on mobile systems in light, and to make people aware of these attacks and how to avoid them.

Cloud Computing-Based Forensic Analysis for Collaborative Network Security Management System

Internet security problems remain a major challenge with many security concerns such as Internet worms, spam, and phishing attacks. Botnets, well-organized distributed network attacks, consist of a large number of bots that generate huge volumes of spam or launch Distributed Denial of Service （DDoS） attacks on victim hosts. New emerging botnet attacks degrade the status of Internet security further. To address these problems, a practical collaborative network security management system is proposed with an effective collaborative Unified Threat Management （UTM） and traffic probers. A distributed security overlay network with a centralized security center leverages a peer-to-peer communication protocol used in the UTMs collaborative module and connects them virtually to exchange network events and security rules. Security functions for the UTM are retrofitted to share security rules. In this paper, we propose a design and implementation of a cloud-based security center for network security forensic analysis. We propose using cloud storage to keep collected traffic data and then processing it with cloud computing platforms to find the malicious attacks. As a practical example, phishing attack forensic analysis is presented and the required computing and storage resources are evaluated based on real trace data. The cloud- based security center can instruct each collaborative UTM and prober to collect events and raw traffic, send them back for deep analysis, and generate new security rules. These new security rules are enforced by collaborative UTM and the feedback events of such rules are returned to the security center. By this type of close-loop control, the collaborative network security management system can identify and address new distributed attacks more quickly and effectively.