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2020 | Book

UnderTracker: Binary Hardening Through Execution Flow Verification Read chapter Read first chapter

Secure Knowledge Management In Artificial Intelligence Era

8th International Conference, SKM 2019, Goa, India, December 21–22, 2019, Proceedings

Editors: Sanjay K. Sahay, Nihita Goel, Vishwas Patil, Murtuza Jadliwala

Publisher: Springer Singapore

Book Series : Communications in Computer and Information Science

Part of: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

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About this book

This book constitutes the refereed proceedings of the 8th International Conference On Secure Knowledge Management In Artificial Intelligence Era, SKM 2019, held in Goa, India, in December 2019.

The 12 full papers presented were carefully reviewed and selected from 34 submissions. They were organized according to the following topical sections: cyber security; security and artifcial intelligence; access control models; and social networks.

Table of Contents

Frontmatter

Cyber Security

Frontmatter
UnderTracker: Binary Hardening Through Execution Flow Verification
Abstract
Programs are developed in a manner so that they execute and fulfill their intended purpose. In doing so, programmers trust the language to help them achieve their goals. Binary hardening is one such concept, which prevents program behavior deviation and conveys the intention of the programmer. Therefore, to maintain the integrity of the program, measures need to be taken to prevent code-tampering. The proposed approach enforces code verification from instruction-to-instruction by using the programmer’s intended control flow. UnderTracker enforces execution flow at the instruction cache by utilizing the read-only data-cache available in the program. The key idea is to place a control transfer code in data-cache and to call it from instruction cache via labels. UnderTracker injects labels into the binary without affecting the semantics of the program. After the code execution starts, it verifies every control point’s legality before passing the control to the next instruction, by passively monitoring the execution flow. This paper proposes an efficient technique, called UnderTracker, to strengthen the binary integrity of an I/O intensive running program, with the nominal overhead of only 5–6% on top of the normal execution.
Rajesh Shrivastava, Chittaranjan Hota, Govind Mittal, Zahid Akhtar
Toward Relationship Based Access Control for Secure Sharing of Structured Cyber Threat Intelligence
Abstract
Cyber Threat Intelligence (CTI) represents cyber threat information which are critical to an organization. Structured Threat Information Expression (STIX) and Trusted Automated Exchange of Intelligence Information (TAXII) provide a standard to represent and share CTI in an efficient, structured and machine readable manner. In this paper, we provide a CTI sharing scenario in an organizational context and develop a Relationship Based Access Control (ReBAC) implementation to securely share CTI structured in STIX. We further discuss an organization’s scope for future analyses and actions on shared CTI.
Md. Farhan Haque, Ram Krishnan
Decepticon: A Hidden Markov Model Approach to Counter Advanced Persistent Threats
Abstract
Deception has been proposed in the literature as an effective defense mechanism to address Advanced Persistent Threats (APT). However, administering deception in a cost-effective manner requires a good understanding of the attack landscape. The attacks mounted by APT groups are highly diverse and sophisticated in nature and can render traditional signature based intrusion detection systems useless. This necessitates the development of behavior oriented defense mechanisms. In this paper, we develop Decepticon (Deception-based countermeasure) a Hidden Markov Model based framework where the indicators of compromise (IoC) are used as the observable features to aid in detection. This framework would help in selecting an appropriate deception script when faced with APTs or other similar malware and trigger an appropriate defensive response. The effectiveness of the model and the associated framework is demonstrated by considering ransomware as the offending APT in a networked system.
Rudra Prasad Baksi, Shambhu J. Upadhyaya
A Survey on Ransomware Detection Techniques
Abstract
Ransomware is among the most dangerous malware prevailing in today’s world. Once infected, the malware either encrypts the data or lock the system screen, and prevents the owner from accessing his data and system until some ransom money is paid, resulting in multi-million dollars of cyber-extortion annually. Additionally, there is no guarantee that the owner would regain access to the seized data after payment is made. Ransomware attacks keep troubling the cybersecurity community; researchers are working towards developing efficient techniques for the detection and prevention of ransomware attacks. In this paper, we are attempting to review the existing solutions based on the methodology adopted and validate them using specific performance metrics.
C. V. Bijitha, Rohit Sukumaran, Hiran V. Nath

Security and Artificial Intelligence

Frontmatter
Indian New Currency Denomination Identification System with Audio Feedback Using Convolution Neural Networks for Visually Challenged and Elderly People
Abstract
The visually challenged people lack the ability to perform activities for daily living in general and instrumental daily living activities in particular. The major problems faced by visually challenged people and elderly people with low vision in pursuing money transactions are to distinguish between an original and fake currency note and identify the correct denomination of the given currency note. This paper proposes a hand held portable device that implements a currency recognition algorithm developed using customized Convolution neural networks. The proposed device has the ability to distinguish between original and fake currency notes and recognize the denomination of the currency notes. Further, it sends the information regarding the currency denomination by an audio feedback to the visually challenged user thus enabling him to do money transactions on his own. The performance of the proposed system is verified under real time by giving it to the actual user and the accuracy of the proposed system is found to be 97.4% executed within 10 s of time.
Padma Vasavi Kalluru
Secure and Energy-Efficient Key-Agreement Protocol for Multi-server Architecture
Abstract
Authentication schemes are practiced globally to verify the legitimacy of users and servers for the exchange of data in different facilities. Generally, the server verifies a user to provide resources for different purposes. But due to the large network system, the authentication process has become complex and therefore, time-to-time different authentication protocols have been proposed for the multi-server architecture. However, most of the protocols are vulnerable to various security attacks and their performance is not efficient. In this paper, we propose a secure and energy-efficient remote user authentication protocol for multi-server systems. The results show that the proposed protocol is comparatively \(\sim \)44% more efficient and needs \(\sim \)38% less communication cost. We also demonstrate that with only two-factor authentication, the proposed protocol is more secure from the earlier related authentication schemes.
Trupil Limbasiya, Sanjay K. Sahay

Access Control Models

Frontmatter
A Formal Specification of Access Control in Android
Abstract
A formal specification of any access control system enables deeper understanding of that system and facilitates performing security analysis. In this paper, we provide a comprehensive formal specification of the Android mobile operating system’s access control system, a widely used mobile OS. Prior work is limited in scope, in addition recent developments in Android concerning dynamic runtime permissions require rethinking of its formalization. Our formal specification includes two parts, the User-Initiated Operations (UIOs) and Application-Initiated Operations (AIOs), which are segregated based on the entity that initiates those operation. Formalizing ACiA allowed us to discover many peculiar behaviors in Android’s access control system. In addition to that, we discovered two significant issues with permissions in Android which were reported to Google.
Samir Talegaon, Ram Krishnan
Security Analysis of Unified Access Control Policies
Abstract
In the modern computing era, access to resources is often restricted through contextual information and the attributes of users, objects and various other entities. Attribute-Based Access Control (ABAC) can capture those requirements as a policy, but it is not yet adopted like Role Based Access Control (RBAC) due to lack of a comprehensive administrative model. In the last few years, several efforts have been made to combine ABAC with RBAC, but they are limited to specification and enforcement only. Recently, we have presented a unified framework along with a role based administrative model that enables specification, enforcement and maintenance of unified access control policies, such as ABAC, RBAC and Meta-Policy Based Access Control (MPBAC). This paper describes role-based administrative model components and then present a methodology which uses a fixed-point based approach for verifying the security properties (like safety and liveness) of those policies in the presence of the administrative model. We also analyse the impact of ABAC, RBAC, MPBAC and administrative model components on the time taken for security analysis. Experimental results demonstrate that the proposed approach is scalable as well as effective.
Mahendra Pratap Singh, Shamik Sural, Vijayalakshmi Atluri, Jaideep Vaidya
On the Feasibility of RBAC to ABAC Policy Mining: A Formal Analysis
Abstract
Given a Role-Based Access Control (RBAC) system along with supporting attribute data, the process of automated migration to an Attribute-Based Access Control (ABAC) system is a particular instance of the ABAC policy-mining problem. In this paper, we formulate and investigate the feasibility problem of RBAC to ABAC policy mining. Specifically, the ABAC RuleSet Existence problem is introduced formally for the first time in RBAC context. In case of infeasibility, the notion of ABAC RuleSet Infeasibility Correction is formalized and a solution developed utilizing role-based attributes.
Shuvra Chakraborty, Ravi Sandhu, Ram Krishnan

Social Networks

Frontmatter
An Investigation of Misinformation Harms Related to Social Media During Humanitarian Crises
Abstract
During humanitarian crises, people face dangers and need a large amount of information in a short period of time. Such need creates the base for misinformation such as rumors, fake news or hoaxes to spread within and outside the affected community. It could be unintended misinformation with unconfirmed details, or intentional disinformation created to trick people for benefits. It results in information harms that can generate serious short term or long-term consequences. Although some researchers have created misinformation detection systems and algorithms, examined the roles of involved parties, examined the way misinformation spreads and convinces people, very little attention has been paid to the types of misinformation harms. In the context of humanitarian crises, we propose a taxonomy of information harms and assess people’s perception of risk regarding the harms. Such a taxonomy can act as the base for future research to quantitatively measure the harms in specific contexts. Furthermore, perceptions of related people were also investigated in four specifically chosen scenarios through two dimensions: Likelihood of occurrence and Level of impacts of the harms.
Thi Tran, Rohit Valecha, Paul Rad, H. Raghav Rao
The Effect of Threat and Proximity on Cyber-Rumor Sharing
Abstract
Today’s society faces a paramount challenge from cyber-rumors that become rapidly viral and transform into more harmful impacts in social networks. The problem of cyber-rumors is further exacerbated in the health crisis context. In the healthcare literature, it has been well established that threat situations facilitate citizens’ behavior including cyber-rumor sharing. In this paper, we argue that in the healthcare context, both the threat attribute and cyber-rumor sharing are likely to be influenced by the proximity to health crisis. We argue that proximity is an important indicator of newsworthiness and shareworthiness in social media. In accordance, we investigate how the concept of proximity affects diffusion characteristics of cyber-rumor messages. We address the following research questions associated with cyber-rumor sharing in the context of Zika virus: How does proximity affect the threat appeal in a cyber-rumor message? How does proximity influence cyber-rumor sharing? The results indicate the negative effect of spatial and temporal distance on threat appeal, and the negative effect of spatial distance on cyber-rumor sharing. Such an investigation allows us to quickly identify the emergence of viral rumor messages and monitor the ongoing development of these messages in a timely manner.
Rohit Valecha, Tejaswi Volety, K. Hazel Kwon, H. Raghav Rao
Securing Trust in Online Social Networks
Abstract
Trust in Online Social Networks (OSN) is a contentious topic. On one hand, there is an increasing reliance on them for trustworthy information and on the other, wariness to believe anything on it. Although the providers of OSNs have tried multiple ways to boost the trustworthiness of the information posted on their websites and weed out millions of fake accounts, the problem is largely unsolved and poses a formidable challenge. This paper examines the problem is some detail, discusses existing solutions to the problem using Machine Learning and other techniques and concludes by discussing some more ideas on enhancing the trustworthiness of the OSNs.
Vishnu S. Pendyala
Backmatter
Metadata
Title
Secure Knowledge Management In Artificial Intelligence Era
Editors
Sanjay K. Sahay
Nihita Goel
Vishwas Patil
Murtuza Jadliwala
Copyright Year
2020
Publisher
Springer Singapore
Electronic ISBN
978-981-15-3817-9
Print ISBN
978-981-15-3816-2
DOI
https://doi.org/10.1007/978-981-15-3817-9

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