Call for Papers on "Cognitive Computing and Human Understandable Artificial Intelligence"

Guest Editors

• Dr. Sachi Nandan Mohanty
  VIT-AP University, Amaravati, Andhra Pradesh
  sachinandan09@gmail.com
• Prof. Sven Groppe
  Institute of Information Systems (IFIS), University of Lübeck, Lübeck, Germany
  groppe@ifs.uni-luebeck.de
• Prof. Alvora Rocha
  Department of Informatics Engineering University of Porto, Portugal
  amrrocha@gmail.com

Introduction

Cognitive computing, inspired by the functioning of the human brain and cognitive processes, has emerged as a transformative field with wide-ranging applications in artificial intelligence (AI), machine learning, and natural language processing. The interdisciplinary nature of cognitive computing draws from psychology, neuroscience, computer science, linguistics, and philosophy to develop systems capable of understanding, reasoning, and learning in a human-like manner. This special issue aims to explore recent advancements and challenges in cognitive computing, focusing on modeling human knowledge, problem-solving, learning, semantic computing, decision-making, cognitive architecture, artificial general intelligence (AGI), human-level AI, and LLM applications.

Topics of Interest

Submission Guidelines

Authors are invited to submit original research articles, review papers, or case studies addressing the aforementioned topics or related areas. All submissions will undergo a rigorous peer-review process to ensure the quality and relevance of accepted manuscripts.

Important Dates

Submission Deadline: 10th October 2024
Notification of Acceptance: 10th January 2025
Expected Publication: 15th February 2025

Submission Instructions

Authors should submit their manuscripts through the online submission system of the New Generation Computing (NGCO) journal. Please refer to the journal's website for formatting guidelines and submission instructions.

Please select “Yes” for the question “Does this manuscript belong to a special issue?” and then select the special issue “S.I. : Cognitive Computing and Human Understandable Artificial Intelligence" in the submission system.

We look forward to receiving your contributions and fostering insightful discussions on the advancements and challenges in cognitive computing.

For more, visit: https://link.springer.com/journal/354/updates/27324472

Call for Papers on "Multimedia Data and Network Security"

Guest Editors

• Dr. Zahid Akhtar
  Department of Network and Computer Security, State University of New York Polytechnic Institute, Utica, NY, USA

Introduction

In the digital era, multimedia data have become integral to our daily lives, permeating various platforms and networks. The multimedia data proliferation coupled with the increasing complexity of network infrastructures has brought unprecedented challenges and opportunities in the realm of security and integrity of such data and networks. This Special Issue aims to explore the pressing challenges and innovations in protecting multimedia data and the networks through which it is transmitted. High-quality, original research contributions are invited to present cutting-edge methodologies, frameworks, and technologies designed to enhance multimedia data security. Researchers, academicians, and practitioners are encouraged to contribute and foster the dissemination of the latest findings, stimulate innovative ideas, and shape future research directions in the field of multimedia data and network security.

Submission Guidelines

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Computers is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

Benefits of Publishing

• Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
• Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
• Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
• External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
• e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

For more, visit: https://www.mdpi.com/journal/computers/special_issues/J7G444HZ9C

Call for Papers on "Deepfakes, Fake News and Multimedia Manipulation from Generation to Detection (2nd Edition)"

Guest Editors

• Dr. Zahid Akhtar
  Department of Network and Computer Security, State University of New York Polytechnic Institute, Utica, NY, USA
  zahid.akhtar@sunypoly.edu

Introduction

Machine-learning-based techniques are being utilized to generate hyper-realistic manipulated facial multimedia content known as DeepFakes. While these technologies have potential positive uses in entertainment, the malicious use of such technologies poses significant threats. This includes creating indecent content, spreading fake news, subverting elections, facilitating social engineering, and financial fraud. Moreover, manipulated content can deceive both humans and automated face-recognition-based biometric systems. The rise of advanced hardware, powerful smart devices, user-friendly apps (such as FaceApp and ZAO), and open-source machine learning codes (like Generative Adversarial Networks) has made it easy for non-experts to create manipulated multimedia content. Techniques include face swapping, modifying facial attributes (e.g., age, gender), morphing, and animating facial expressions.
Topics of interest in this Special Issue include but are not limited to:

Submission Guidelines

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Computers is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

Benefits of Publishing

• Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
• Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
• Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
• External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
• e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

For more, visit: https://www.mdpi.com/journal/jimaging/special_issues/GB55G013ZK

Call for Papers on "Security-Pattern Recognition and Validation"

Guest Editors

• Prof. George A. Papakostas
  Department of Computer Science, International Hellenic University, Thessaloniki, Greece
• Dr. Zahid Akhtar
  Department of Network and Computer Security, State University of New York Polytechnic Institute, Utica, NY, USA

Special Issue Introduction

Security-pattern recognition and validation are pivotal in safeguarding digital systems and ensuring data integrity across various domains. This Special Issue invites researchers and practitioners to share their expertise on recognizing and validating security patterns, addressing crucial challenges, and proposing innovative solutions.

Spanning a wide spectrum of topics, this issue aims to explore cutting-edge research in security-pattern recognition and validation. Some of the key areas to be covered include:

• Machine learning and deep learning approaches for security-pattern recognition
• Pattern-based anomaly detection and intrusion detection systems
• Biometric pattern recognition and authentication techniques
• Behavioral analysis for security event detection and response
• Pattern-based malware detection and classification
• Cryptographic pattern recognition and validation methods
• Security-pattern validation frameworks and methodologies
• Real-world applications and case studies showcasing the effectiveness of security-pattern recognition techniques
• Performance evaluation and benchmarking of security-pattern recognition systems
• Emerging trends and future directions in security-pattern recognition and validation

Academics, research students and professionals are invited to submit original work. Extended conference papers are also welcome, provided they have been revised and contain at least 50% new content.

Keywords

Pattern recognition, validation, security issues

Submission Deadline

31 August 2024

Submission Information

For Author Instructions, please refer to Author Instructions.
For Online Submission, please login at Submission Portal.

Contacts: Yoyo Bai, Assistant Editor, assistant-editor@jsssjournal.com

For more, visit: https://www.oaepublish.com/specials/jsss.1993

Call for Papers on "Privacy-Preserving Techniques for Data Collection and Analysis in Ambient Intelligence Networks"

Guest Editors

• Dr. Mehdi Gheisari (Managing GE)
  Department of Computer Science, Islamic Azad University, Tehran, Iran
• Dr. Subhendu Kumar Pani (First Co-GE)
  Krupajal Engineering College, Biju Patnaik University of Technology, India
• Dr. Kamalakanta Muduli (Second Co-GE)
  Department of Mechanical Engineering, The Papua New Guinea University of Technology, Papua New Guinea

Introduction

Privacy preserving technologies let marketers continue to use data driven systems while giving users the ability to safeguard the privacy of personally identifiable information they give to and are managed by service providers or apps. Statistical analysis has been made possible by privacy preserving methods including homomorphic encryption, SMC, and differential privacy. Finding a balance between data privacy and statistical accuracy is one of the difficulties in privacy preserving computation. They include methods that allow data analysis and sharing without jeopardising the security and integrity of the data, such as homomorphic encryption, federated learning, differential privacy, and safe multiparty computation. Theoretically, firms can retain and increase access to important data while protecting individuals’ privacy thanks to privacy preserving analytics approaches. Maintaining privacy is crucial when handling sensitive data inside a company. It is made up of techniques and procedures intended to shield data during processing and analysis from unwanted access, use, or disclosure. The goal of privacy preservation processing techniques is to obscure or even completely remove the connection between sensitive data and its original owner without impairing the data ability to offer insightful information about a particular occurrence of interest.

Data can be encoded using encryption to ensure that only authorised users can decipher it. But encryption is not enough to protect information on its own. Data integrity, encryption, auditing, and access control are all used to protect data in databases. The ubiquitous access to multiple equipment and devices on service providers is the aim of the Internet of Things. IoT based gadgets, yet, can expose a user to different security and privacy risks. The main goal of privacy preservation strategies is to safeguard data transfers of any kind between parties. Data privacy is the capacity for individuals to control that can access their personal information and the safeguarding of personal data from unauthorised parties. A large machine learning model has the potential to memorise the training set, which is risky for privacy. Measurement of privacy loss and control over data access are necessary for maintaining privacy. Because of its mathematical accuracy, differential privacy is usually regarded as the gold standard of privacy protection.

In general, privacy refers to the freedom from interruption or intrusion and the right to be left alone. The right to some control over the collection and use of your personal information is termed as information privacy. Ensuring that sensitive data, such financial or medical records, is only accessed by authorised individuals is one example of data privacy. Biometric authentication or access control methods like usernames and passwords can be used to accomplish this. Another example of data privacy is data encryption. Concerns about gathering, storing, and keeping data, as well as data transfers that fall under relevant rules and legislation like GDPR and HIPAA, are the main emphasis of data privacy. Throughout the data lifecycle, data security refers to safeguarding data from loss, corruption, and unauthorised access. It would be challenging for the individual to recognize the mistakes in their thinking. We welcome submissions from a variety of fields and viewpoints, such as but not limited to: Privacy-Preserving Techniques for Data Collection and Analysis in Ambient Intelligence Networks.

The topics relevant to this special issue include but are not limited to:

• A thorough examination of privacy preserving technologies created for social media websites.
• Effective third-party auditing that protects privacy for ambient intelligence systems.
• Raw data collecting for IoT that protects privacy without the need for a reliable authority.
• Predicting human behaviour with non-intrusive, privacy preserving internet of things aided surveillance.
• A cloud environment data privacy preserving model based on deep neural networks and a differential methodology.
• Software defined Internet of Things fog intrusion detection framework with privacy preserving features.
• A sanitization strategy for data mining in a socially dispersed context while protecting privacy.
• Green computing tools for privacy aware data aggregation in IoT based healthcare.
• Mobile sensing using cloud enabled privacy preserving collaborative learning.
• A user authentication system for wireless sensor networks that protects privacy and can be verified, based on internet of things security.
• An anonymous plan for collecting data in IoT based healthcare services systems while protecting privacy.
• Human computer connection that is both private and secure while acknowledging widespread healthcare surveillance.

Special Issue Timeline

• Submission Deadline: January 25, 2025
• Author Notification: March 30, 2025
• Revised Submission: May 31, 2025
• Final Acceptance: July 25, 2025

For more, visit: https://www.cai.sk/ojs/index.php/cai/announcement/view/23